# Stitch Technology Limited: full site content > Plain-text content of every Stitch service page, case study and insight article, for AI assistants and search tools. Summary and links: https://stitchtech.co/llms.txt === Site summary (llms.txt) === # Stitch Technology Limited > Stitch Technology Limited is an independent Auckland, New Zealand consultancy founded in 2019. It connects performance media, customer data platforms, marketing automation, data engineering and agentic AI, with marketing mix modelling through Stitch Predict. Its published service area includes New Zealand and Australia. ## Key facts - Stitch Technology Limited was founded in 2019. - Based at Ground Floor, 295 Parnell Road, Parnell, Auckland, New Zealand. - Serves clients in New Zealand and Australia. - Platforms implemented: Tealium, Segment, Hightouch, Customer.io, Braze, Snowflake, BigQuery, Google and Meta. - Braze ANZ Rising Star of the Year 2026 (Braze ANZ Partner Awards): https://stitchtech.co/insights/braze-anz-rising-star-2026 - +93% website users for Skills Group: https://stitchtech.co/case-studies/skills-group - 82x ROAS on Coastguard NZ lottery campaigns: https://stitchtech.co/case-studies/coastguard - 6.3x lead volume for Turners Cars: https://stitchtech.co/case-studies/turners - 8M profiled IDs in Tealium for Tourism New Zealand: https://stitchtech.co/case-studies/tourism-nz - Full plain-text content of every service page, case study and insight: https://stitchtech.co/llms-full.txt ## Identity - Legal name: Stitch Technology Limited - Trading name: Stitch - Domain: stitchtech.co - LinkedIn: https://www.linkedin.com/company/stitchtechnology/ - Address: Ground Floor, 295 Parnell Road, Parnell, Auckland 1052, Aotearoa New Zealand - Contact: info@stitchtech.co · +64 27 513 0110 ## Partner credentials - Tealium · Services Partner, Advanced, APJ (publicly listed) - Customer.io · Gold Agency Partner; APAC member, Customer.io Partner Advisory Board - Braze · Alloys Solutions Partner, Orbit tier - Hightouch · Certified partner, NZ - Segment · Certified partner, NZ ## Third-party profiles and coverage - [Tealium partner profile](https://tealium.com/partner/stitch-technology-nz/) - Stitch Technology's Tealium partner listing. - [Customer.io partner profile](https://customer.io/agency-partners/partner/stitch) - Stitch's Customer.io agency partner listing. - [StopPress coverage](https://stoppress.co.nz/awards/stitch-named-braze-anz-rising-star-of-the-year-2026/) - Reporting on Stitch being named Braze ANZ Rising Star of the Year 2026. - [Meet the founder: Stitch, NZ Marketing magazine (1 October 2026)](https://nzmarketingmag.co.nz/meet-the-founder-stitch/) - Profile of Stitch, why it was founded and how it works. ## Identity clarification This document describes Stitch Technology Limited at stitchtech.co. The similarly named business at stitch.cx is a separate organisation. Stitch Technology provides consultancy and implementation services; Stitch Predict is its productised marketing mix modelling offering. ## What Stitch does 1. Performance media 2. Marketing automation 3. Agentic AI and automation 4. CDP implementation 5. Data engineering 6. Marketing mix modelling ## Pages - [Home](https://stitchtech.co/) - [Case Studies](https://stitchtech.co/case-studies) - Project-specific evidence; results are not guarantees for other clients. - [Turners Cars](https://stitchtech.co/case-studies/turners) - 6.3x lead volume for Turners Cars through customer data unification, marketing automation and closed-loop attribution. Supreme Award 2022. - [Serko AI](https://stitchtech.co/case-studies/serko-ai) - Six-week Braze build for Serko AI's agentic travel assistant. Lifecycle layer behind a US beta launch in May 2026. - [Tourism New Zealand](https://stitchtech.co/case-studies/tourism-nz) - Global customer data infrastructure for Tourism New Zealand. Eight million profiled IDs in Tealium, driving a 13 per cent lift in operator revenue. - [Skills Group](https://stitchtech.co/case-studies/skills-group) - Three brands consolidated, chat assistant family in production, 93 per cent growth in website users for Skills Group across the first 90 days. - [Coastguard New Zealand](https://stitchtech.co/case-studies/coastguard) - 82x ROAS for Coastguard New Zealand's lottery campaigns through privacy-first measurement and first-party audience strategy. - [Sanderson Group](https://stitchtech.co/case-studies/sanderson-group) - 1,282x ROAS for Sanderson Group's Omokoroa development at $38 cost per lead. Built to sell sections, not just chase clicks. - [Stitch Predict](https://stitchtech.co/case-studies/stitch-predict) - Marketing mix modelling, productised. Deployed across the Stitch client portfolio. Used in board-level investment decisions at Turners. - [World Vision New Zealand](https://stitchtech.co/case-studies/world-vision) - Multi-year transformation for World Vision: Twilio Segment, Snowflake and Customer.io into one connected supporter platform. - [Mr Apple](https://stitchtech.co/case-studies/mr-apple) - 150 per cent database growth for Mr Apple across four Asian markets through unified customer data and lifecycle activation on Tealium. - [Real NZ](https://stitchtech.co/case-studies/real-nz) - Five-platform unification on Tealium for Real NZ, replacing fragmented tooling with one connected customer data layer. - [Juliette Hogan](https://stitchtech.co/case-studies/juliette-hogan) - 79x ROAS and 162 per cent year-on-year ecommerce growth for fashion label Juliette Hogan through paid acquisition and lifecycle. - [Trilogy International](https://stitchtech.co/case-studies/trilogy) - 14.1x ROAS for Trilogy International across the United States, Australia and home market launches. - [Lexus Urban Polo](https://stitchtech.co/case-studies/lexus-urban-polo) - 5.2x revenue lift and 4.1x ROAS for the Lexus Urban Polo across two markets through paid social and event-driven acquisition. - [Calocurb](https://stitchtech.co/case-studies/calocurb) - Conversion research, a homepage and product page redesign, and a Shoplift A/B testing programme for Calocurb, the world's first natural GLP-1 activator. A 40% peak lift on product page conversion rate. - [Services](https://stitchtech.co/services) - [Performance media](https://stitchtech.co/services/performance-media) - [Marketing automation](https://stitchtech.co/services/marketing-automation) - [Agentic AI](https://stitchtech.co/services/agentic-ai) - [CDP implementation](https://stitchtech.co/services/cdp-implementation) - [Data engineering](https://stitchtech.co/services/data-engineering) - [Marketing mix modelling](https://stitchtech.co/services/marketing-mix-modelling) - [Predict](https://stitchtech.co/predict) - [Stitch Predict demo](https://stitchtech.co/predict/demo) - Book a Stitch Predict demo. Bayesian MMM platform deployed across Stitch clients. NZD-priced, six to ten weeks to deployment. - [Partners](https://stitchtech.co/partners) - Platform credentials and implementation experience. - [Tealium partner](https://stitchtech.co/partners/tealium) - Stitch is a Tealium Services Partner (Advanced, APJ). The CDP team behind Tourism NZ's 8M profiled IDs and Real NZ's five-platform unification. - [Customer.io partner](https://stitchtech.co/partners/customer-io) - Stitch is a Customer.io Gold Agency Partner. Lifecycle automation for Turners since 2019, four-market activation for Mr Apple. - [Braze partner](https://stitchtech.co/partners/braze) - Stitch is a Braze Alloys Solutions Partner, Orbit tier. Lead Braze partner on Serko AI - dual sender, Transactional API, Liquid, Data Warehouse to Braze. - [Hightouch partner](https://stitchtech.co/partners/hightouch) - Stitch is a Hightouch Implementation Partner in NZ. Warehouse-native audience activation and identity resolution. - [Segment partner](https://stitchtech.co/partners/segment) - Stitch is a Segment Certified Partner. Event collection, identity resolution and reverse ETL for Turners - Segment to Snowflake to Customer.io. - [Google and Meta partner](https://stitchtech.co/partners/google-meta) - Stitch is a Google Partner and Meta Business Partner. 82x ROAS for Coastguard, 14.1x for Trilogy USA, 79x for Juliette Hogan. - [About](https://stitchtech.co/about) - [Process](https://stitchtech.co/process) - [Connect](https://stitchtech.co/connect) - [Service recommender](https://stitchtech.co/recommend) ## Published insights - [Insights](https://stitchtech.co/insights) - [Segment vs Tealium](https://stitchtech.co/insights/segment-vs-tealium) - Practical CDP selection guide. - [Agentic AI for marketing](https://stitchtech.co/insights/agentic-ai-for-marketing) - Practical marketing-agent use cases and deployment considerations. - [Braze ANZ Rising Star 2026](https://stitchtech.co/insights/braze-anz-rising-star-2026) - Award announcement and Braze delivery work. ## Optional - [Full site content](https://stitchtech.co/llms-full.txt) - Plain text of every service page, case study and insight article. - [Privacy](https://stitchtech.co/privacy) - [Terms](https://stitchtech.co/terms) ## Awards TVNZ Marketing Awards Supreme 2022; 2x Gold Effie Awards Aotearoa 2022; Global Effie Finalist 2023; Braze ANZ Rising Star of the Year 2026. See the About and Braze announcement pages for context. ## Industry roles Marketing Association of New Zealand thought leader groups. Lead, AI Working Group, IAB NZ. Founding agency member, Aotearoa Independent Media Agencies (AIMA). APAC member, Customer.io Partner Advisory Board. ## Braze hub - [Braze hub](https://stitchtech.co/braze) - Braze guides, tools and benchmarks from Stitch, a Braze Alloys Solutions Partner (Orbit tier) and Braze ANZ Rising Star of the Year 2026. - [Braze or Customer.io?](https://stitchtech.co/braze/braze-or-customer-io) - Answer eight questions for a neutral steer on which platform fits better and why. - [Braze readiness scorecard](https://stitchtech.co/braze/readiness-scorecard) - Ten questions to assess your data, identity, channels, content and lifecycle measurement. - [Braze vs Customer.io: A Consultant's Comparison](https://stitchtech.co/braze/braze-vs-customer-io) - Braze or Customer.io? An independent ANZ consultant's comparison of channels, data, pricing, AI and Australian data residency to help you choose. - [Braze data residency in Australia and New Zealand: what AU-01 means](https://stitchtech.co/braze/data-residency-australia) - Braze runs an Australian data centre, AU-01. Here's what it hosts, how it's chosen, what still leaves Australia, and what NZ and AU privacy law expects. - [Connecting Braze to Snowflake, Databricks and BigQuery with Cloud Data Ingestion](https://stitchtech.co/braze/cloud-data-ingestion-snowflake-databricks) - How Braze Cloud Data Ingestion syncs Snowflake, Databricks and BigQuery data into Braze, how to send data back, and the pitfalls to avoid. - [How Braze pricing works (and how to budget for it)](https://stitchtech.co/braze/pricing) - Braze pricing is by quote, built from a Platform Edition, MAUs, Action Credits and services. Here's what drives cost and how to build the business case. - [Braze implementation checklist and timeline: a 12-week plan](https://stitchtech.co/braze/implementation-checklist) - A practical 12-week Braze implementation plan: data model, SDKs, data ingestion, email, SMS and WhatsApp setup, Canvas build, QA and launch. - [Migrating to Braze from Salesforce Marketing Cloud, Klaviyo or HubSpot](https://stitchtech.co/braze/migrating-to-braze) - What moves and what doesn't when you migrate to Braze from SFMC, Klaviyo or HubSpot: profiles, consent, templates, journeys, IP warming and risks. - [BrazeAI Decisioning in practice: what it is and when it's worth it](https://stitchtech.co/braze/brazeai-decisioning) - What BrazeAI Decisioning Studio does, when AI decisioning pays off, the data you need, how to run a fair holdout test and the pitfalls to avoid. - [ANZ customer engagement benchmark 2026: what the Braze data says, and what to do about it](https://stitchtech.co/braze/anz-customer-engagement-benchmark-2026) - ANZ brands are the most AI-confident in the world but trail on revenue. Key numbers from Braze's 2026 ANZ review, with Stitch's view on closing the gap. --- === Services === URL: https://stitchtech.co/services/cdp-implementation CDP implementation # Unify the customer. Activate everywhere. Tealium Services Partner, Advanced tier, APJ. Segment Certified Partner. Hightouch Implementation Partner. The CDP work that powers Tourism New Zealand, Real NZ, Mr Apple and Turners. ## What is CDP implementation? CDP implementation is the work of setting up a customer data platform so every system shares one trusted view of the customer, with consent, audiences and activation in one place. Stitch implements Tealium, Segment and Hightouch for businesses across New Zealand and Australia, from identity and consent through to audience activation. ## Who it's for It is for organisations with customer data spread across many systems and no single view of the customer. That includes national-scale brands like Tourism New Zealand, multi-brand portfolios like Real NZ, and exporters like Mr Apple growing across several markets. CDPs are the foundation that everything else stands on. Done well, they deliver one trusted view of the customer, consent that holds up to legal scrutiny, audience activation across every channel, and a data warehouse spine that finance, product and marketing can all agree on. Done badly, they become a very expensive integration project that nobody uses. Stitch is the New Zealand consultancy certified across Tealium, Segment and Hightouch. We have implemented eight million profiled IDs for Tourism New Zealand with 100 real-time inbound events and 160 million connector and API calls. We have unified five platforms into one customer view for Real NZ. We have stood up Tealium AudienceStream and EventStream for Mr Apple's growth across four Asian markets. ## Related case studies - Tourism New Zealand - Real NZ - Mr Apple - Turners Cars - World Vision New Zealand ## What we do - Tealium AudienceStream, EventStream, Moments and Consent - Segment Connections, Personas, Protocols and reverse ETL - Hightouch reverse ETL, audiences and identity resolution from Snowflake and BigQuery - Identity stitching, consent unification and GDPR/Privacy Act compliance - Audience activation into Meta, Google, TikTok, Salesforce, Dynamics 365 and downstream lifecycle platforms - Migrations between CDPs and warehouse-native consolidations ## FAQ ### Which platforms do you work with? Tealium, Segment and Hightouch as the primary stack. We also integrate Customer.io and Braze as activation layers downstream. ### How long does a CDP implementation take? A defensible foundation is typically live in 8 to 12 weeks. National-scale deployments with hundreds of integrations run longer. ### Are you Tealium-certified? Yes. Publicly listed Tealium Services Partner, Advanced tier, APJ in New Zealand. ### Can you migrate us from one CDP to another? Yes. Migrations between CDPs and warehouse-native consolidations are part of our CDP work. ### Do you work with Australian businesses? Yes. Stitch is based in Auckland and works with businesses across New Zealand and Australia. ### What results have clients seen? Tourism New Zealand has eight million profiled IDs in Tealium, with a 13 per cent operator revenue lift driven by digital advertising. Real NZ unified five platforms into one customer view. Tourism New Zealand case study Real NZ case study ## Keep exploring - All services - Case studies --- URL: https://stitchtech.co/services/marketing-automation Marketing automation # Lifecycle that survives the real world. Customer.io Gold Agency Partner. Braze Alloys Solutions Partner, Orbit tier. We build the journeys that fire when the flight gets cancelled, when the cart gets abandoned, and when the renewal window opens. ## What is marketing automation? Marketing automation is the lifecycle, transactional and journey messaging that reaches customers at the right moment, such as a cancelled flight, an abandoned cart or an open renewal window. Stitch designs, builds and runs these programmes on Customer.io and Braze for businesses across New Zealand and Australia, tied to revenue targets. ## Who it's for It is for teams that need lifecycle messaging to work when nobody is watching, from transactional alerts to reactivation and renewal. It suits product-led businesses like Serko AI, multi-brand operators like Skills Group, and teams moving off HubSpot, ActiveCampaign, Klaviyo or Mailchimp. Marketing automation is the part of the stack that has to work when nobody is watching. A delayed flight. A reactivation cohort. A 24-hour reminder. Each touch is a chance to lose the customer or earn a transaction. We are a Customer.io Gold Agency Partner and a Braze Alloys Solutions Partner, Orbit tier. We have built the lifecycle layer behind Serko AI's agentic corporate travel product on Braze in six weeks, including transactional, marketing and dual-sender architecture. We have orchestrated Skills Group's chat assistant family across four divisions on Zapier with a RAG layer and a Power Automate connector into Dynamics 365. We have run the lifecycle for Turners Cars since 2019. ## Related case studies - Serko AI - Skills Group - Turners Cars - World Vision New Zealand - Sanderson Group - Mr Apple ## What we do - Lifecycle, transactional and journey design on Customer.io and Braze - Migrations from HubSpot, ActiveCampaign, Klaviyo and Mailchimp - Liquid personalisation for complex objects (flights, bookings, multi-leg trips, dynamic catalogues) - Server-side ingestion via Braze Transactional API, BigQuery, Cloud Data Ingestion, GTM - Consent management via Osano and Tealium - Reactivation, churn and renewal programmes tied to commercial outcomes ## FAQ ### Which platforms do you work with? Customer.io (APAC Partner Advisory Board member) and Braze are the primary stack. We also migrate teams off HubSpot, ActiveCampaign, Klaviyo and Mailchimp. ### Do you only build journeys, or run them? Both. We design, build and operate lifecycle programmes against revenue targets. ### How long does a lifecycle build take? It depends on scope. The Serko AI lifecycle layer was built on Braze in six weeks from kick-off. Serko AI case study ### Can you migrate us from our current platform? Yes. We migrate teams from HubSpot, ActiveCampaign, Klaviyo and Mailchimp. For World Vision New Zealand we delivered and validated an audience migration from HubSpot to Segment. World Vision New Zealand case study ### Do you work with Australian businesses? Yes. Stitch is based in Auckland and works with businesses across New Zealand and Australia. ### What results have clients seen? Sanderson Group's triggered emails averaged a 61 per cent open rate across 15,000 sends. Serko AI had booking confirmation, disruption SMS and 24-hour reminder flows active from day one. Sanderson Group case study Serko AI case study ## Keep exploring - All services - Case studies --- URL: https://stitchtech.co/services/performance-media Performance media # Connect every dollar of media spend to revenue. Performance media that uses the customer data, attributes to the offline lead, and answers to the CFO. Not to the platform dashboard. ## What is performance media? Performance media is paid advertising managed against measurable business results, such as leads and revenue, rather than clicks. Stitch runs paid search, paid social, programmatic, BVOD and retail media for businesses in New Zealand and Australia, using server-side tracking, offline conversions and first-party audiences to connect spend to revenue. ## Who it's for It is for marketers who need to show the CFO how media spend turns into revenue, not platform dashboards. It suits ecommerce brands like Juliette Hogan and Trilogy International, events like the Lexus Urban Polo, and not-for-profits like Coastguard New Zealand. We run paid acquisition across Google, Meta, TikTok, programmatic display and BVOD. The thing that makes Stitch performance media different is what sits underneath it. Server-side tracking. Offline conversion ingestion. First-party audiences out of the CDP. A measurement layer that does not depend on cookies the browser is busy deprecating. We are a Google Partner and a Meta Business Partner. Our work has driven 82x ROAS on Coastguard NZ lottery campaigns, 14.1x ROAS on Trilogy International in the United States, 79x ROAS on Juliette Hogan, and 5.2x revenue growth across two markets for the Lexus Urban Polo. Every one of those numbers is owned and verified. ## Related case studies - Coastguard New Zealand - Juliette Hogan - Trilogy International - Lexus Urban Polo - Sanderson Group - World Vision New Zealand - Turners Cars - Tourism New Zealand - Mr Apple - Skills Group ## What we do - Paid search, paid social, programmatic, BVOD and retail media - Offline conversion tracking and lead-source attribution - Server-side tagging via Stape and GTM - First-party audience activation from Tealium, Segment and Hightouch into Google and Meta - Marketing mix modelling overlays via Stitch Predict - Creative testing infrastructure tied to revenue, not platform-reported clicks ## FAQ ### How do you measure media? Marketing mix modelling via Stitch Predict, plus geo-experiments and incrementality tests where useful. Closed-loop attribution back to revenue, not platform-reported clicks. ### Do you take media commissions? No. We charge fees for media management. We have no rebate or commission relationships with platforms. ### Which channels do you run? Paid search, paid social, programmatic, BVOD and retail media, across Google, Meta, TikTok and more. We are a Google Partner and a Meta Business Partner. ### Which markets do you run media in? Oceania, North America, the Middle East and Europe. Recent work spans New Zealand, Australia, the United States and Singapore. Trilogy International case study Lexus Urban Polo case study ### Do you work with Australian businesses? Yes. Stitch works with businesses across New Zealand and Australia. Trilogy International ran at 7x ROAS across Australia and New Zealand. Trilogy International case study ### What results have clients seen? 82x ROAS on Coastguard NZ lottery campaigns, 14.1x ROAS for Trilogy International in the United States and 79x ROAS for Juliette Hogan. Coastguard New Zealand case study Trilogy International case study Juliette Hogan case study ## Keep exploring - All services - Case studies --- URL: https://stitchtech.co/services/marketing-mix-modelling Marketing mix modelling # Marketing mix modelling for the mid-market. Off-the-shelf MMM either costs a fortune or hands back models nobody trusts. So we built our own. Bayesian, board-grade, NZD-priced. ## What is marketing mix modelling? Marketing mix modelling is a statistical method that shows how much each channel contributes to revenue, without relying on third-party cookies. Stitch delivers it through Stitch Predict, our Bayesian MMM platform, priced in NZD for mid-market brands in New Zealand and Australia, with geo-lift validation and scenario planning that marketing and finance can both use. ## Who it's for It is for mid-market brands that need defensible answers about what drives revenue, without enterprise pricing or long contracts. It suits marketing and finance teams who both need to trust the model, as Turners does in board-level investment decisions. Marketing mix modelling has had a renaissance as third-party cookies disappear and finance teams demand defensible answers about what is actually driving revenue. The enterprise MMM platforms in market price out the mid-market or lock clients into long contracts for models that marketing teams and CFOs cannot both believe. Stitch Predict is the proprietary platform we built because the alternatives did not fit. Bayesian regression foundation. Third-party-cookie independent. Integrated with the data infrastructure Stitch already deploys for clients. Scenario planning and budget optimisation outputs that marketing and finance can both use. Deployed across the Stitch portfolio. Validated via geo-lift on Turners Auto Retail and used in board-level investment decisions. Public launch case study with RestoreMe Clinic. ## Related case studies - Stitch Predict - Turners Cars ## What we do - Bayesian marketing mix modelling on two to three years of weekly data - Geo-lift validation - Scenario planning and budget reallocation - Channel-, campaign- and creative-level decomposition - Integration with first-party customer data, attribution and finance systems - Board-grade reporting deliverables ## FAQ ### How is Predict different from a custom MMM build? Predict is productised: same Bayesian engine, lower cost, monthly cadence, NZ-specific media library. ### How long until we get a model? First model in 6 weeks from contracted data access. ### What data do you need? Two to three years of weekly data. Predict integrates with first-party customer data, attribution and finance systems. ### How do you know the model is right? We validate with geo-lift against held-out markets. Predict was validated via geo-lift on Turners Auto Retail. Stitch Predict case study ### Do you work with Australian businesses? Yes. Stitch Predict is built for mid-market brands across New Zealand and Australia. ### What results have clients seen? For Turners, Predict identified 1.9x BVOD ROI via geo-lift, and the model is used in board-level investment decisions. Stitch Predict case study Turners Cars case study ## Keep exploring - All services - Case studies --- URL: https://stitchtech.co/services/data-engineering Data engineering # The pipes and tables underneath everything else. Most marketing problems are data problems. We build the warehouse, the pipelines, the identity layer and the dashboards that the rest of the stack runs on. ## What is data engineering for marketing? Data engineering for marketing is building the warehouse, pipelines, identity layer and dashboards that the rest of the marketing stack runs on. Stitch builds this layer on Snowflake, BigQuery and Microsoft Azure, with reverse ETL through Hightouch and Census, for businesses across New Zealand and Australia, so CDPs, lifecycle platforms and models get trusted data. ## Who it's for It is for marketing, product and finance teams who want to own their data layer. It suits businesses whose CDP, lifecycle platform or marketing mix model needs cleaner, connected inputs, such as Turners, Real NZ and Serko AI. A CDP is only as good as the data flowing into it. A lifecycle platform is only as good as the audiences feeding it. A marketing mix model is only as good as the spend, revenue and creative inputs it consumes. Stitch builds the layer underneath. Three million user records and 500,000 PII records under management for Turners. Two-way data warehouse sync into Microsoft Azure and Power BI for Real NZ. Data Warehouse to Braze via Cloud Data Ingestion for Serko AI. Stitch works with Azure Databricks for Skills Group, feeding data to ad platforms. ## Related case studies - Turners Cars - Real NZ - Serko AI - Skills Group - World Vision New Zealand ## What we do - Warehouse build-outs on Snowflake, BigQuery and Microsoft Azure - Azure Databricks feeding data to ad platforms and Microsoft Dynamics for Skills Group - Reverse ETL via Hightouch and Census from warehouse to activation tools - Server-side data ingestion via Stape, GTM, Cloud Data Ingestion and HTTP APIs - Identity resolution and PII governance - Looker Studio, Power BI and Tableau dashboards tied to operational metrics - Custom MCP server development for AI-native operating models ## FAQ ### Do you build the warehouse from scratch? Often, yes. Greenfield Snowflake or BigQuery deployments are common. ### Do you do reverse ETL? Yes. Hightouch and Census are core tools. ### Which platforms do you work with? Snowflake, BigQuery, Microsoft Azure and Azure Databricks for data platforms, Microsoft Dynamics for CRM, Hightouch and Census for reverse ETL, and Looker Studio, Power BI and Tableau for dashboards. ### Do you handle identity resolution and PII? Yes. Identity resolution and PII governance are part of the work. For Turners we manage 3 million user records and 500,000 PII records. Turners Cars case study ### Do you work with Australian businesses? Yes. Stitch is based in Auckland and works with businesses across New Zealand and Australia. ### What results have clients seen? Real NZ has two-way data warehouse sync into Microsoft Azure and Power BI. Serko AI's data warehouse feeds Braze via Cloud Data Ingestion. Real NZ case study Serko AI case study ## Keep exploring - All services - Case studies --- URL: https://stitchtech.co/services/agentic-ai Agentic AI # Agentic AI, in production. Most of the industry is talking about agentic AI. We are shipping it. Skills Institute Chatbot live since April 2026. Serko AI's agentic travel lifecycle launched May 2026. ## What is agentic AI for marketing? Agentic AI for marketing means AI agents that take actions, not just answer questions, such as qualifying leads, answering customer questions or coordinating messages. Stitch builds production chat assistants, agentic SMS and email, and custom MCP servers for businesses across New Zealand and Australia, connected to platforms like Braze, Customer.io, Zapier and n8n. ## Who it's for It is for marketing and CX teams ready to move agentic AI from slideware into production. It suits businesses that need to capture and qualify lead intent at scale, like Skills Group, or coordinate customer messaging alongside AI agents, like Serko AI. Agentic AI is the next layer of the stack, and most agencies are still in slideware. Stitch leads the IAB New Zealand AI Working Group on agentic systems and the future of measurement. We have shipped production chat assistants for Skills Group across four divisions on Zapier with a RAG layer trained on the client's content. We are a Braze Alloys Solutions Partner, Orbit tier, and the lead Braze partner on Serko AI, the agentic AI travel assistant that launched its US beta on 9 May 2026. The Stitch team runs on agentic AI internally. MCP server integrations connect AI assistants directly to Tealium, Customer.io, Braze, Jira, Slack and Google Workspace, as well as the paid media stack across Meta, Google Ads and Google Analytics. ## Related case studies - Serko AI - Skills Group ## What we do - Production AI chat assistants on Zapier, Voiceflow and n8n with RAG layers - Two-way agentic SMS and email comms via Braze and Customer.io - AI-powered lead qualification connected to Dynamics 365, Salesforce and HubSpot - Custom MCP server development for client and internal tooling - AI strategy and operating model design for marketing and CX teams ## FAQ ### What is MCP? Model Context Protocol. An open standard for connecting LLMs to tools and data sources. Stitch builds custom MCP servers and integrates third-party ones across the martech stack. ### Do you build custom agents? Yes. We design, build and operate agentic workflows for clients across Tealium, Customer.io, Braze and the rest of the martech stack. ### Which tools do you build agents on? Zapier, Voiceflow and n8n with RAG layers, plus two-way agentic SMS and email via Braze and Customer.io. ### Is agentic AI live in production for clients? Yes. The Skills Institute Chatbot has been live since April 2026, and Serko AI's agentic travel lifecycle launched in May 2026. Skills Group case study Serko AI case study ### Do you work with Australian businesses? Yes. Stitch works with businesses across New Zealand and Australia. Skills Group's chat assistants include SDG in Australia and New Zealand. Skills Group case study ### What results have clients seen? Skills Group has a chat assistant family in production across Premiere, SDG and Skills Institute, with lead capture into Dynamics 365. Serko AI's US beta launched on 9 May 2026. Skills Group case study Serko AI case study ## Keep exploring - All services - Case studies --- === Case studies === URL: https://stitchtech.co/case-studies/turners Case Study 01 / Turners Cars # Supercharging Tina with martech and data Turners Group is New Zealand's largest seller of cars, trucks and machinery. Twenty-two branches, nationwide reach, and a media problem hiding in plain sight. ## At a glance Last updated 10 October 2026 ## Background Turners Group NZ Limited is the largest seller of cars, trucks and machinery in New Zealand with 22 branches nationwide. The business runs on volume. The media spend needed to track every dollar to revenue. Stitch has worked with Turners since 2019 as the foundational client of the practice. ## The problem Media and content investment decisions were being made on website interactions. Website interactions represented 14% of all inbound business enquiries. Test drive bookings made by phone, walk-ins to branches, emails sent directly to sales teams. None of it was visible to the people deciding where to put media spend. Eighty-six per cent of business enquiries were invisible. ## The solution Stitch implemented offline attribution that captured every lead from every source. Phone and email test drive bookings, branch walk-ins, web enquiries, dealer hand-offs. We rebuilt the measurement layer on Segment, Snowflake and Customer.io and gave the team genuine insight into which channels, platforms and creative were driving cars sold, not just clicks. The data infrastructure became the foundation for the "Tina from Turners" brand work. Stitch contributed the data and martech foundations that allowed the creative to be optimised against real commercial outcomes. 530% Increase in lead volume -68% Reduction in cost per lead +38% Lift in post-lead interactions ## Additional outcomes - 14% increase in cars sold against a declining market - 43% to 48% YoY profit growth - 150% growth in the known customer universe - 3 million user records, 500,000 PII records under management ## Recognition Stitch contributed the data and martech foundations on the Turners "Tina from Turners" campaign, recognised across the industry. - 3x TVNZ Marketing Awards 2022, including the Supreme Award - 2x Gold Effie Awards 2022 - Global Effie Awards Finalist 2023, one of only two NZ campaigns selected from 125 markets - Excellence in Long-Term Marketing Strategy, NZ Marketing Awards 2024 - Gold Effie for Sustained Success 2024 ## Closing The Turners engagement set the template for everything Stitch does. Do not optimise to the metric you can measure easily. Build the measurement that captures what actually matters, then optimise to that. --- URL: https://stitchtech.co/case-studies/serko-ai Case Study 02 / Serko AI # Agentic travel lifecycle, built on Braze in six weeks. Serko, the NZX-listed corporate travel technology company, was building Serko AI: an agentic AI travel assistant for SME corporate travel, with a US beta target of 1,500 active travellers each with at least one booking. ## At a glance Last updated 27 May 2026 ## Background The product needed transactional messaging that could survive flight disruption, hotel re-bookings and 24-hour reminders, plus a marketing layer that could segment by trip context, all wired into Braze and BigQuery, in six weeks. ## The problem Lifecycle messaging in corporate travel is unforgiving. A delayed flight, a hotel re-book, a 24-hour reminder that goes to the wrong number. Each one is a customer-facing failure. Doing it for an agentic AI travel assistant, at SME scale, in six weeks, with a dual-sender domain split for transactional and marketing, was the brief. ## The solution Stitch led the Braze implementation alongside Braze's own onboarding team. Production and parallel dev workspaces. Braze Web SDK deployed via GTM. Data Warehouse to Braze via Cloud Data Ingestion. Braze Transactional API for booking confirmation, CFAR and non-CFAR disruption, and 24-hour reminders. Dual sender architecture on notify.serko.ai for transactional and insider.serko.ai for marketing. GUID-based external ID resolution. A flattened active_flights array schema co-designed with Braze to bypass nesting limits on multi-leg trips. Liquid personalisation for complex flight, hotel and cost objects. 9 May 26 Beta launched for US SME travellers Dual Sender architecture: transactional and marketing 6 wks End to end build from kick-off ## Additional outcomes - End-to-end booking confirmation, disruption SMS, and 24-hour reminder flows active from day one - Two-way agentic agentic SMS, whatsapp, on page and in-app messaging, with Braze coordinating Serko's AI travel agents - Stack: Braze (Web SDK, Transactional API, Liquid), BigQuery, Cloud Data Ingestion, GTM, Osano consent ## Closing The lifecycle layer behind Serko's bet on agentic corporate travel. Built fast, built to survive disruption, and built to evolve into two-way agentic comms as the product matures. --- URL: https://stitchtech.co/case-studies/tourism-nz Case Study 03 / Tourism New Zealand # Global-scale customer profile in production. Tourism New Zealand markets 100% Pure New Zealand to the world and supports a long tail of NZ tourism operators and global aggregators. ## At a glance Last updated 27 May 2026 ## Background Tourism New Zealand is the national tourism marketing body. It is responsible for promoting Aotearoa to international visitors and supporting a long tail of NZ tourism operators, accommodation partners and global aggregators across the booking journey. ## The problem The challenge was profile depth at global scale across multi-step consumer journeys: from newzealand.com to operator booking via Hobbiton, accommodation partners and global aggregators. Customer journeys are non-linear and multi-device, and operator-level attribution and measurement was hard to defend. ## The solution Tealium sits at the centre of the architecture. The unified data layer feeds audiences and events to Meta, Google, TikTok and Salesforce. Microsoft Dynamics 365 and ClickDimensions handle marketing automation and personalisation downstream. Operator-level conversion tracking spans thousands of NZ tourism operators, the Hobbiton Movie Set integration and global aggregators and local booking agents. 8M Profiled / stitched IDs 160M Connector and API calls 13% Operator revenue lift driven by digital advertising ## Additional outcomes - 100 real-time inbound events - Stack: Tealium, Microsoft Dynamics 365, ClickDimensions, Meta, Google, TikTok, Salesforce, Hobbiton Movie Set integrations ## Closing This is what a global-scale CDP looks like in production. Profile depth, real-time event flow, and attribution that holds up to operator-by-operator scrutiny. --- URL: https://stitchtech.co/case-studies/skills-group Case Study 04 / Skills Group # Three brands collapsed into one, with a chat assistant family in the middle. Skills Group operates four divisions across vocational, trades, leadership and B2B training. Marketing operations were duplicated across HubSpot, Google Ads, Meta and a 25,000-contact AU and NZ database that had been opening emails at six to eight per cent. ## At a glance Last updated 27 May 2026 ## Background The trades function ran three legacy brands (Etco, E-tec and ICE) that competed with each other for the same apprentice and employer audiences. A consolidation into Skills Trades Training launched in December 2025. ## The problem Three brands chasing the same buyer pool. Three sets of pixels, properties and ad accounts. A reactivation cohort sitting unmoved across the AU and NZ database. And no virtual front door for the four divisions to capture and qualify lead intent at scale. ## The solution Stitch led the digital migration for the December 2025 consolidation. New Meta Pixel, new GA4 property, new Google Ads account, fresh Looker Studio dashboards across Skills Trades and E-tec, Stape server-side tagging. Alongside the consolidation, Stitch built a virtual chat assistant family in production across Premiere, SDG (Australia and New Zealand) and Skills Institute, each hosted on Zapier with a RAG layer trained on Skills Group content and a Microsoft Power Automate connector into Dynamics 365 CRM for lead capture. Demand gen was rebuilt around mid-funnel nurture against a three to six month decision window and $1,500 to $3,000 course price points. +93% Website users (first 90 days) +56% Sessions (first 90 days) +43% Conversions (first 90 days) ## Additional outcomes - Best demand-gen unit-economic at $6.82 Meta CPL on Data Cabling AKL - Google blended CPA of $21.16 across the trades program - Skills Institute Chatbot live on 30 April 2026 at skills-institute.zapier.app - SDG webinar: 274 registrations, ~100 live attendees, 39% first eDM open rate, 31.7% second eDM open rate - LinkedIn lead generation operating at approximately $58 CPL for the leadership offer ## Closing Three brands collapse into one. A chat assistant family answers the questions a sales rep used to take a week to get to. The reactivation cohort opens emails again. That is what a consolidation is supposed to feel like. --- URL: https://stitchtech.co/case-studies/coastguard Case Study 05 / Coastguard NZ # Lifesaving performance. Coastguard New Zealand keeps people safe on the water. We made every donation dollar work harder. ## At a glance Last updated 27 May 2026 ## Background Coastguard New Zealand is the country's primary maritime search-and-rescue charity, operating across more than 60 units nationwide. The organisation depends on lottery, membership and direct donation revenue to keep volunteer rescue crews on the water. ## The problem Coastguard's fundraising had to scale in a measurement environment breaking down with the deprecation of third-party cookies. The old playbook of broad audiences, vanity reach metrics and last-click attribution was not going to deliver the donations needed to fund operations. ## The solution Stitch designed a privacy-first measurement and audience strategy on first-party data. We unified Coastguard's supporter, member and donor records, then activated media at the moments and audiences most likely to give. Measurement was rebuilt around modelled outcomes rather than the metrics ad platforms hand back for free. The same audience strategy now powers ongoing brand and member acquisition work. 82x Return on marketing spend, lottery campaigns 23% Conversion rate, six times the NZ ecommerce average $1.60 Cost per lead ## Additional outcomes - 2025 Winter Membership: 447 memberships driven through paid acquisition - $5.23 cost per acquisition on lapsed-member retargeting, 5.6x more efficient than prospecting - 238 memberships from warm web visitors - $2.75 per membership on the Females 55 to 64 lapsed-list ad set - $10 cost per lottery ticket - 66.12% email open rate - 7x ROAS on membership work - $22 cost per acquisition on new sign-ups - Lottery campaigns now contribute approximately 51% of fundraising revenue ## Closing This is what privacy-first media looks like when it is done properly. Not a workaround for cookie deprecation. A better approach that would have outperformed the old one regardless. --- URL: https://stitchtech.co/case-studies/sanderson-group Case Study 06 / Sanderson Group # Built to sell sections, not just chase clicks. A privacy-first media and lifecycle programme for Sanderson Group's Omokoroa Country Club retirement village, delivering 1,282x ROAS, $38 cost per lead and millions in lot sales across a buyer's market. ## At a glance Last updated 10 October 2026 ## Background Sanderson Group is a family-owned developer of luxury retirement villages in Aotearoa New Zealand, with a track record stretching back to Omokoroa Country Estate in 1987 and a 2019 sale of three villages to Arvida Group for approximately $180 million. Omokoroa Country Club is their newest project, a $280 million development on the Omokoroa Peninsula in Tauranga's inner harbour with around 170 standalone villas, approximately 50 apartments and an 80-bed dementia care facility on a 17-hectare site. Stitch was engaged in mid-2023 to run the digital media and marketing automation programme for the village launch, with creative delivered by Feast Creative Queenstown. ## The problem Selling a high-consideration property to a discerning buyer is not a click-bait exercise. The campaign needed to find a narrow audience of pre-retirees and recent retirees with the appetite, the equity and the timing to buy into a new village, then nurture them through a sales cycle measured in months, not minutes. All of this had to happen in the trough of the NZ property cycle, with annual sales down 41.3% from the June 2021 peak to 58,763 by May 2023 per REINZ, and in a measurement environment already fractured by Safari and Firefox cookie blocking and Chrome's announced deprecation pathway. The brief was simple to write and difficult to execute. Drive enough qualified leads to fill the development, at a cost per lead that protected margin, with attribution clean enough for the board. ## The solution We built a privacy-first audience strategy on first-party data, then activated it across Meta Ads and Google Ads. Audiences were modelled rather than scraped, and we measured everything against modelled outcomes rather than the platforms' marking of their own homework. The media programme was managed end-to-end by Stitch, with daily optimisation against cost per qualified lead. Behind the media, we built a marketing automation programme that did the heavy lifting once a lead was captured. Triggered emails carried the prospect from first enquiry through to sales-ready, with content matched to their stage and their stated preferences. We unified the enquiry, web, ad and CRM data into one trusted view of each prospect, so the sales team knew who was warm before they picked up the phone. The work began on 16 June 2023 and the campaign has continued in market, with the lifecycle programme compounding on the media spend rather than burning out alongside it. 3.73m Kiwis reached, campaign to date $38 Cost per qualified lead, blended 1,282x Return on ad spend, campaign to date ## Additional outcomes - 80% of leads from paid advertising, 20% from organic search and the marketing automation programme - 15,000 triggered emails sent, 61% average open rate - 5,100% increase in traffic to the Omokoroa Country Club website - 3,438% increase in website views - 70% increase in average engagement time and 30% increase in engaged sessions per user - Millions in lot sales banked despite a trough property market - Stack: Meta Ads, Google Ads, marketing automation, first-party audience modelling - Timeframe: June 2023 onwards, sustained campaign ## Closing "We are thrilled with the outstanding results achieved through our partnership with Stitch. Their expertise in digital media and marketing automation, combined with the creative prowess of Feast Creative, has propelled Omokoroa Country Club to new heights. We look forward to continued success as we set new standards in retirement living." A 1,282x return on ad spend is not a media result. It is what happens when you join the media, the data and the lifecycle into one programme that does not stop selling between ad impressions. We built it, we ran it, we measured it. --- URL: https://stitchtech.co/case-studies/stitch-predict Case Study 07 / Stitch Predict # Marketing mix modelling, productised for the mid-market. The off-the-shelf MMM platforms either cost a fortune or hand back models nobody trusts. So we built our own. ## At a glance Last updated 27 May 2026 ## Background Marketing mix modelling has had a renaissance as third-party cookies disappear and finance teams demand defensible answers about what is actually driving revenue. The existing platforms in market either price out the mid-market or lock clients into long contracts for models that marketing teams and CFOs cannot both believe. ## The problem Mid-market brands across NZ and Australia need MMM-grade answers without enterprise pricing or six-month consultant engagements. The existing options do not fit the way mid-market teams want to consume the output, and do not fit the way Stitch wanted to deliver it. ## The solution Stitch Predict is a proprietary marketing mix modelling platform built on a Bayesian regression foundation. It runs independently of third-party cookies, integrates with the data infrastructure Stitch already deploys for clients, and produces scenario planning and budget optimisation outputs that marketing teams and CFOs can both actually use. Positioned for the mid-market, NZD-priced, accessible without an in-house data science team. Portfolio Deployed across Stitch clients 1.9x BVOD ROI identified for Turners via geo-lift Geo-lift Validated against held-out markets ## Additional outcomes - Turners Auto Retail: flagship deployment, validated via geo-lift, used in board-level investment decisions - RestoreMe Clinic: public launch case study ## Closing Stitch Predict is what happens when a consultancy gets tired of recommending tools it does not fully trust. We built the one we wanted to recommend. Product site: stitchpredict.com --- URL: https://stitchtech.co/case-studies/world-vision Case Study 08 / World Vision New Zealand # Project Symphony. The customer data, marketing automation and paid media rebuild behind World Vision New Zealand's multi-year transformation programme. ## At a glance Last updated 10 October 2026 ## Background World Vision New Zealand is one of Aotearoa's largest child sponsorship and humanitarian organisations, with public fundraising programmes spanning child sponsorship, emergency appeals, gifts and wills, regular giving and a national supporter base measured in the hundreds of thousands. The organisation embarked on a multi-year transformation called Project Symphony to replatform its customer data and marketing technology stack, retire a legacy CRM and email setup, and move to a modern data warehouse and customer data platform that would let the fundraising and marketing teams work from one trusted view of the supporter. Stitch was engaged as the customer data, marketing automation and performance media partner for Project Symphony, working alongside the WVNZ delivery, data and fundraising teams. ## The problem The legacy stack was doing exactly what a legacy stack does. Supporter data was scattered across a Snowflake warehouse, a separate CRM, HubSpot for email, GA4 for analytics, and a paid media setup that could not see past last-click. The fundraising team could not build audiences across that mess. The lifecycle team could not trigger comms off behaviour. The performance media team could not optimise toward the metrics the board actually cares about. On top of that, a not-for-profit cannot waste a dollar. Every cost per acquisition number had to defend itself against the alternative of putting that dollar into the field. The new stack had to deliver a unified supporter view, journey-grade orchestration, clean conversion measurement, and a paid media programme that could be defended in front of a board. ## The solution We architected the data foundation around Twilio Segment as the customer data platform, with Snowflake as the warehouse, and Customer.io as the lifecycle engine. Stitch built the full Segment tracking plan, designed the data layer, ran the implementation through Google Tag Manager, and stood up the identity resolution that joined web behaviour, transactional data and supporter records into one profile. The platform was wired so that Snowflake-resident supporter data could be combined with real-time event data inside Segment, then activated downstream. On top of that foundation, we ran a programme of journey design workshops with the WVNZ fundraising and marketing teams. We mapped the supporter lifecycle across single gift, gifts and wills, child sponsorship onboarding, the Chosen sponsorship journey, emergency appeals and the supporter portal. Each journey was specified as audience definitions, triggers, exit criteria and the events needed to support it. We then migrated the HubSpot audiences into Segment and rebuilt the email programme inside Customer.io. Alongside the platform work, Stitch took over the paid media programme across Meta Ads and Google Ads, plus above-the-line planning for the major campaigns. Conversion tracking was rebuilt from the ground up around product-specific events, so a child sponsorship completion, a one-off donation and a gifts-and-wills enquiry were measured separately rather than collapsed into a single purchase event. Campaign optimisation was aligned to the actual fundraising goals, not the platforms' default conversions. 54% Lift in combined paid traffic, year on year 2x Meta sessions, year on year +30% Google active users, year on year ## Additional outcomes - Single supporter view live across Twilio Segment, Snowflake and Customer.io - Audience migration from HubSpot to Segment delivered and validated - Tracking architecture rebuilt around product-specific conversion events for child sponsorship, gifts and wills, emergency appeals and one-off donations - Journey design and build workshops delivered across single gift, gifts and wills, child sponsorship onboarding, Chosen lead nurturing, supporter portal and emergency appeals - Paid media programme across Meta Ads and Google Ads, plus above-the-line planning for major campaigns - Engagement rate on organic search lifted year on year despite reduced session volume - Stack: Twilio Segment, Snowflake, Customer.io, GA4, Google Tag Manager, Meta Ads, Google Ads, Looker Studio - Timeframe: 2023 to early 2026 ## Closing Not every transformation finishes the way it starts. What stayed true through Project Symphony was the brief Stitch was hired against. Unify the data, run the lifecycle, defend every dollar. We built it, we ran it, we measured it. --- URL: https://stitchtech.co/case-studies/mr-apple Case Study 09 / Mr Apple # Global reach, local results. Mr Apple is New Zealand's largest apple exporter. Stitch built the customer data infrastructure that powers their growth across Asia. ## At a glance Last updated 27 May 2026 ## Background Mr Apple (Scales Corporation, NZX:SCL) is New Zealand's largest apple exporter, with consumer markets across China, Vietnam, India and Thailand. Marketing operates across very different languages, channels, partners and buyer behaviours, but needs shared infrastructure that scales. ## The problem Mr Apple needed to grow its known customer universe across diverse Asian markets without duplicating effort country by country. Each market had its own retail partners, channel mix and consumer behaviours. The data was not connecting back into a unified view that marketing could act on. ## The solution Stitch implemented Tealium AudienceStream and EventStream as the customer data platform, integrated with Customer.io for lifecycle activation across all four markets, and connected Uniqode QR-code activations on packaging to bring offline interactions into the data layer. The result is one trusted view of the Mr Apple consumer across Asia, with personalisation at scale and proper measurement of what is actually working in each market. 150% Growth in customer database -46% Cost per landing page view $27k Monthly CPA saving ## Additional outcomes - First-ever ecommerce campaign successfully delivered in India - Cost per click reduced 60% to 489% depending on market - Click-through rate up 81% - Anonymous audience modelling on Meta enabling lookalike scaling across markets ## Closing The Mr Apple build is a working template for any NZ exporter scaling into Asia. Connect the data, activate locally, measure globally. --- URL: https://stitchtech.co/case-studies/real-nz Case Study 10 / Real NZ # Five platforms collapsed into one customer view. Real NZ is the portfolio of New Zealand tourism brands across Tourism, Skiing, accommodation, network and agent bookings. ## At a glance Last updated 27 May 2026 ## Background Real NZ is the portfolio of New Zealand tourism brands: Tourism, Skiing (Treble Cone, Cardrona), accommodation, network and agent bookings. Owned brands include realnz.com, treblecone.com and cardrona.com. ## The problem Customer profile data sat in silos across Tourism bookings, Skiing bookings, agent bookings, service centres, owned websites, Silverstripe, and the third-party platforms FareHarbor (tourism) and Aspenware (skiing). No unified customer view, no consistent audience optimisation, no defensible attribution across the portfolio. ## The solution Tealium sits at the centre with a master unified data layer holding profile and unified consent across all owned and third-party data sources. HTTP API and webhook integrations span Real NZ's three brand sites and the two third-party booking platforms. Audience and event activation reaches Meta, Google Data Studio, Salesforce Sales Cloud, SproutSocial, ActiveCampaign, Optimizely, Olark, Hotjar and Delighted. Two-way data warehouse sync runs into Microsoft Azure and Power BI. 5 Platforms unified into one customer view 3 + 2 Owned brand sites plus FareHarbor and Aspenware 1 Consent and profile spine ## Additional outcomes - Third-party integrations and data unlocks across the portfolio - Audience optimisation including suppression segments and net-new segments - Stack: Tealium, FareHarbor, Aspenware, Salesforce Sales Cloud, Microsoft Azure, Power BI, Meta, Google Data Studio, ActiveCampaign, Optimizely, SproutSocial, Olark, Hotjar, Delighted ## Closing Five platforms in, one customer out. The before-and-after of CDP work made tangible. --- URL: https://stitchtech.co/case-studies/juliette-hogan Case Study 11 / Juliette Hogan # 79x ROAS. 162% ecommerce growth, year on year. New Zealand fashion designer with a national retail footprint and direct-to-consumer ecommerce. ## At a glance Last updated 27 May 2026 ## Background Juliette Hogan is a New Zealand fashion designer with a national retail footprint and direct-to-consumer ecommerce. The brand needed to scale ecommerce without cannibalising in-store revenue, and tie creative performance directly to revenue across both channels. ## The problem Retail and DTC sit on different P&Ls but share customers, creative and inventory. The brief was to scale ecommerce and grow in-store ad revenue at the same time, without one channel stealing from the other. ## The solution Stitch ran digital strategy and media management end to end. Shopify catalogue integrations and optimisation across Google and Meta drove dynamic advertising tailored by user behaviour and product preference. Personalised customer and advertising experiences ran across the full digital customer journey, with automation tying every touch back to a single customer view. 79x Return on ad spend 162% YoY ecommerce growth 87% In-store ad revenue growth, QoQ ## Additional outcomes - 1.6x lift in online revenue - Stack: Shopify, Google, Meta ## Recognition "Taking a digitally advanced and data driven approach yielded success, helping us drive 162% ecommerce growth (YoY), 87% in-store ad revenue growth (QoQ) and a return on ad spend of 79x." ## Closing Fashion brands fight a constant tension between brand and performance. Juliette Hogan proved you can grow both, at the same time, in the same year. --- URL: https://stitchtech.co/case-studies/trilogy Case Study 12 / Trilogy International # 14.1x ROAS in the United States. 630% global ecommerce growth. New Zealand-made certified organic skincare scaled across the United States, Australia and New Zealand. ## At a glance Last updated 27 May 2026 ## Background Trilogy International is a New Zealand-made certified organic skincare brand with international ecommerce across the United States, Australia and New Zealand. The category is crowded, the unit economics are tight, and the brand needed to scale paid acquisition without the global media bill outrunning the contribution margin. ## The problem Trilogy needed market-specific ROAS optimisation across three very different economies at once. Catalogue management spanned Shopify, Amazon, Google and Meta and had to stay synchronised. Closed-loop attribution from creative to ecommerce transaction was the only honest way to make spend decisions across markets. ## The solution Stitch built Shopify catalogue integrations across Amazon, Google and Meta, with dynamic advertising tailored by user behaviour and product preference. Personalised customer experiences ran across web, ecommerce, email and the digital marketplaces. Advanced analytics and Meta multi-touch attribution tied creative and channel performance back to business outcomes, not platform-reported clicks. 14.1x ROAS, United States 7x ROAS, Australia and New Zealand 630% Global ecommerce revenue growth ## Additional outcomes - Stack: Shopify, Amazon, Google, Meta, GA4 - Markets: United States, Australia, New Zealand ## Closing Three markets, one measurement spine, one creative system. The number that matters is the one the CFO sees: revenue against spend, market by market. --- URL: https://stitchtech.co/case-studies/lexus-urban-polo Case Study 13 / Lexus Urban Polo # Sold-out polo. 5.2x revenue growth. Premium sporting and lifestyle event series across New Zealand and Singapore. ## At a glance Last updated 3 June 2026 ## Background The Lexus Urban Polo is a premium sporting and lifestyle event series across New Zealand and Singapore. Stitch ran digital strategy, media management and event sales across both markets. ## The problem The brief was to scale ticket sales across two markets while attributing event revenue to specific channels, platforms and creative. Without an attribution layer, the trade-off between brand spend and conversion spend would have been a guess. ## The solution Frictionless ecommerce ran on Eventbrite, with transactional ticket data integrated into Google and Meta. Attribution and optimisation tied ticket revenue to channel, platform and creative, so spend decisions had a direct line back to revenue per market. 5.2x Revenue growth 4.1x Return on advertising spend NZ + SG Two-market expansion ## Additional outcomes - Stack: Eventbrite, Google Ads, Meta, GA4 - Sector: events, lifestyle ## Closing Sold-out events are the easy part to brag about. The number that matters is whether the spend pencilled out to revenue. It did. In two markets, at once. --- URL: https://stitchtech.co/case-studies/calocurb Case Study 14 / Calocurb # A 40% peak lift on the product page conversion rate. Conversion research, a homepage and product page redesign, and an A/B testing programme for Calocurb, the world's first natural GLP-1 activator. ## At a glance Last updated 10 October 2026 ## Background Calocurb is a plant-based GLP-1 supplement, founded in New Zealand and growing through a United States-led strategy. The active ingredient is Amarasate, an extract from a specific bitter hops flower grown in New Zealand's South Island, developed over roughly 14 years with NZ$30 million invested by Plant and Food Research, a New Zealand government-owned Crown Research Institute. It is positioned as the world's first natural GLP-1 activator: a clinically validated, prescription-free option in a weight-management category dominated by the semaglutide injectables Ozempic and Wegovy. Calocurb is clinically shown to stimulate the body's own satiety hormones (GLP-1, CCK and PYY) at up to six times baseline levels. The brand runs three Shopify storefronts: calocurb.com for United States consumers, calocurb.co.nz for New Zealand, and wholesale.calocurb.com for practitioners. Stitch was engaged in December 2024 to lift conversion across the consumer and wholesale sites, starting with conversion research. ## The problem Calocurb sells a premium, clinically validated product at a premium price (a bottle retails at around 89 US dollars a month) in a category where the reference points are pharmaceutical. Conversion rate on the homepage and product page sat below the category benchmark, and the analytics setup behind the sites needed restructuring before any of that performance could be trusted or improved. The December 2024 conversion research identified three barriers. First, value proposition clarity: five-second tests showed that first-time visitors struggled to articulate the product category quickly, so the page was not earning the next click. Second, funnel visibility: the drop-off between viewing the product and adding to cart on United States mobile was high, and it was not visible in reporting because of gaps in the analytics. Third, premium positioning and premium proof: the area above the fold needed to surface clinical credibility, ratings and endorsements far earlier than it did. ## The solution Stitch fixed the measurement foundation first. Eight foundational analytics changes shipped before the first design variant went live, so that every later read on the redesign would be trustworthy: - Reporting identity switched from blended to device-based, because most visitors do not sign in and device-based avoids thresholding. - Attribution model switched from data-driven to last click, for more timely and actionable reporting at the available data volume. - Session timeout adjusted to 7.5 hours, to stop a 30-minute timeout fragmenting sessions, overstating direct traffic and losing conversions. - Scroll tracking removed from the GA4 enhanced measurement default and rebuilt in Google Tag Manager for greater granularity. - Form tracking moved to custom Google Tag Manager events, replacing GA4 automatic form tracking that was logging false positives. - Query parameters de-cardinalised: system-generated parameter pages were filtered out, cleaning up 1,816 sessions on the wholesale site that had been counted as genuine traffic. - The add-to-cart event was replaced with a select-quantity event on the product page, the action that actually mapped the checkout funnel. - Event naming normalised to GA4 conventions, removing spaces, uppercase letters and special characters. With clean measurement in place, Stitch redesigned two surfaces, the homepage and the product page (PDP), through structured research: five-second tests, copy iterations, and heuristic mapping against the eight conversion barriers identified in the December 2024 research. The homepage redesign reframed the category context, restructured the hero around clinical proof points (the trial result tiles showing a 30 percent reduction in hunger, a 40 percent reduction in cravings and an 18 percent reduction in calorie intake after one hour), and pushed testimonials, FAQs and trust signals into a clear visual hierarchy. The product page redesign elevated trust signals above the fold (the NutraIngredients-USA 2024 Product of the Year: Botanical award badge, a regional store selector and an aggregated rating), repositioned the dosage grid and bundle offer for mobile, and surfaced risk-reversal language and clinical credibility earlier in the page. Round 1 of the A/B test launched in April 2025 on Shoplift, the Shopify experimentation platform, with traffic split 50/50 between the original design (A) and the redesign (B), and measurement married to GA4 and Hotjar. For the first nine days the new product page ran at a +40 percent relative lift in conversion rate over control. Every checkpoint pointed the same way, the result was statistically significant at each one, and abandon rates from viewing the product through to purchase had collapsed. In late April 2025 a viral United States podcast feature about Calocurb went live. It shifted the composition of the test sample: a large new audience entered both variants with different intent and behaviour, and the measured lift moved from +40 percent to +16 percent within hours. Stitch flagged the shift the same morning, isolated the new segment, and recommended a clean reading of the test by separating the two traffic periods. Under that cleaner read, the structural lift from the redesign held up. +40% Peak lift on product page conversion rate (Round 1, before the podcast spike) 8 Foundational analytics fixes shipped before the first variant 100% Of traffic now served the new product page design ## Additional outcomes - Funnel improvements, view product to purchase (source: GA4 funnel comparison, Round 1 test period versus the prior funnel baseline from the December 2024 conversion research): view product to add-to-cart, materially reduced abandon; add-to-cart to checkout, a meaningful reduction in abandon; begin checkout to purchase, a significant reduction in abandon. - Conversion research delivered December 2024; homepage and PDP redesign through Q1 2025; Round 1 A/B test launched April 2025; iterative programme continuing through 2025. - Stack: Shopify, Shoplift, GA4, Hotjar, Google Tag Manager. - Sites: calocurb.com, calocurb.co.nz, wholesale.calocurb.com. ## Closing Round 2 recommendations went into production through 2025. The new homepage and product page designs became the live pages on calocurb.com, Variant B shipped to 100 percent of traffic, and the programme continued through the year with iterative testing and further rounds of optimisation. The number that matters is the one the redesign was built to move: more of the right visitors reaching purchase, on a premium product, in the hardest category to convert in. Data Inspired Marketing in practice. --- === Braze hub === URL: https://stitchtech.co/braze Braze hub # Everything we know about Braze, in one place. Guides, tools and ANZ benchmarks from a Braze Alloys Solutions Partner, Orbit tier, and Braze ANZ Rising Star of the Year 2026. ## What is Braze? Braze is a customer engagement platform for sending personalised, real-time messages across email, push, SMS, WhatsApp, in-app and web. Brands use it to run lifecycle, marketing and transactional messaging from one customer profile. Stitch designs, builds and runs Braze programmes for brands in New Zealand and Australia. ## Why Stitch for Braze - Braze Alloys Solutions Partner, Orbit tier. - Named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards, 2026. - Lead Braze partner on Serko AI: lifecycle layer in production in six weeks. - Appointed Braze onboarding partner by Skyline Enterprises. - Typical implementation: 8 to 12 weeks. ## Tools ### Braze or Customer.io? Answer eight questions for a neutral steer on which platform fits better and why. ### Braze readiness scorecard Ten questions to assess your data, identity, channels, content and lifecycle measurement. ## Benchmark 9 min read ### ANZ customer engagement benchmark 2026: what the Braze data says, and what to do about it ANZ brands are the most AI-confident in the world but trail on revenue. Key numbers from Braze's 2026 ANZ review, with Stitch's view on closing the gap. ## Guides 10 min read ### Braze vs Customer.io: A Consultant's Comparison Braze or Customer.io? An independent ANZ consultant's comparison of channels, data, pricing, AI and Australian data residency to help you choose. 9 min read ### Braze data residency in Australia and New Zealand: what AU-01 means Braze runs an Australian data centre, AU-01. Here's what it hosts, how it's chosen, what still leaves Australia, and what NZ and AU privacy law expects. 9 min read ### Connecting Braze to Snowflake, Databricks and BigQuery with Cloud Data Ingestion How Braze Cloud Data Ingestion syncs Snowflake, Databricks and BigQuery data into Braze, how to send data back, and the pitfalls to avoid. 8 min read ### How Braze pricing works (and how to budget for it) Braze pricing is by quote, built from a Platform Edition, MAUs, Action Credits and services. Here's what drives cost and how to build the business case. 9 min read ### Braze implementation checklist and timeline: a 12-week plan A practical 12-week Braze implementation plan: data model, SDKs, data ingestion, email, SMS and WhatsApp setup, Canvas build, QA and launch. 9 min read ### Migrating to Braze from Salesforce Marketing Cloud, Klaviyo or HubSpot What moves and what doesn't when you migrate to Braze from SFMC, Klaviyo or HubSpot: profiles, consent, templates, journeys, IP warming and risks. 8 min read ### BrazeAI Decisioning in practice: what it is and when it's worth it What BrazeAI Decisioning Studio does, when AI decisioning pays off, the data you need, how to run a fair holdout test and the pitfalls to avoid. 9 min read ### ANZ customer engagement benchmark 2026: what the Braze data says, and what to do about it ANZ brands are the most AI-confident in the world but trail on revenue. Key numbers from Braze's 2026 ANZ review, with Stitch's view on closing the gap. ## Services - Braze partner services - Marketing automation - Data engineering ## FAQ ### Is Stitch a Braze partner? Yes. Stitch is a Braze Alloys Solutions Partner, Orbit tier, based in Auckland, and was named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards in 2026. ### How long does a Braze implementation take? Most Stitch Braze implementations take 8 to 12 weeks. The Serko AI lifecycle layer shipped to production in six weeks from kick-off. ### Can Braze host data in Australia? Yes. Braze offers an Australian instance, AU-01, hosted in Sydney. The instance is chosen when your account is set up. See our data residency guide for details. ### Should I choose Braze or Customer.io? It depends on scale, channels, data residency and team. Stitch partners with both. Use our Braze vs Customer.io selector for a quick recommendation. --- URL: https://stitchtech.co/braze/braze-or-customer-io # Braze or Customer.io? Stitch partners with both Braze and Customer.io, so this is a neutral steer, not a sales pitch. Answer eight questions and we'll suggest which platform fits better and why. ## Monthly active customers you message? --- URL: https://stitchtech.co/braze/readiness-scorecard # Braze readiness scorecard Ten questions, three minutes. Find out how ready your data, team and content are for Braze, or to get more from the Braze you already have. ## How is customer data brought together? --- URL: https://stitchtech.co/braze/anz-customer-engagement-benchmark-2026 ## In short ANZ marketing leaders are more confident about AI and more optimistic about budgets than any other region, but fewer of them hit their revenue goals. Braze's ANZ Customer Engagement Review 2026 puts the gap down to fragmented data, slow activation and personalisation that stops at the insight stage. The brands that close it will be the ones that turn data into real-time, individual decisions. ## Key takeaways - 90% of surveyed ANZ marketing leaders expect their budget to grow in the next 12 months, the highest of any region, but only 61% beat their revenue goals last year (67% globally). - 98% say AI helps them understand customers better than before, yet only 34% assemble content for individual users at the moment of engagement using real-time data. - ANZ is ahead of global peers on several data foundations: 62% combine sources into a single customer profile (58% globally) and 52% use AI to predict needs (43% globally). - 68% say AI intermediation (customers reaching brands through LLMs and agents) has weakened their direct relationship, versus 63% globally. - Only a quarter of ANZ brands sit in Braze's most mature "Ace" group. The biggest share (42%) are in the middle. ## About the data The figures in this article come from the [Braze ANZ Customer Engagement Review 2026](https://www.braze.com/resources/reports-and-guides/2026-anz-customer-engagement-review). Braze commissioned Wakefield Research to survey 2,200 marketing executives (VP level or above, at B2C companies with annual revenue of at least US$10M) across 17 countries between 18 November and 1 December 2025. 200 of them were in Australia and New Zealand. Braze also analysed anonymised, aggregated data from 779 of its customers, covering 6 billion user profiles in 2025. All statistics below are Braze's. The interpretation and recommendations are ours. If you want the full picture, download the report from Braze. ## How mature are ANZ brands at customer engagement? Braze groups brands into three levels on its Customer Engagement Index. In ANZ: | Maturity level | Share of ANZ brands | |---|---| | Activate (least mature) | 33% | | Accelerate | 42% | | Ace (most mature) | 25% | Braze notes that the index was updated this year to reflect AI use, so these groups aren't directly comparable with earlier reports. **Our read:** three in four ANZ brands are not yet operating at the top level. In our experience, the jump from Accelerate to Ace is rarely about buying another tool. It's about whether the data, the platform and the team can act on a signal in minutes instead of weeks. ## Trend 1: Are ANZ brands acting on the data they collect? Braze calls this trend "Data hoarders anonymous". The numbers show a region that has invested in data foundations but isn't converting them into experiences. | Measure | ANZ | Global | |---|---|---| | AI helps us understand customers better than before | 98% | n/a | | Assemble content for individual users at the moment of engagement, using real-time data | 34% | n/a | | Combine data from different sources into a single customer profile | 62% | 58% | | Update and use data in real time through data streaming | 59% | 57% | | Use AI to predict customer needs for frictionless journeys | 52% | 43% | | Concerns about backlash or improper data use are slowing AI adoption | 46% | 54% | Braze's recommendations: treat data as a real-time relationship signal rather than a reporting asset, invest in a flexible platform that unifies and activates data, and make data literacy a basic expectation across teams. **Our read:** the 98% versus 34% gap is the headline. Most of the ANZ brands we talk to have a warehouse, a CDP or both. What they're missing is the last mile: identity that resolves in real time, a clean event model the engagement platform can trigger on, and content built in modules so it can be assembled per person. That's an architecture and operating model problem, not an AI problem. The practical fix is to pick two or three journeys where a real-time signal changes the message (abandoned browse, disruption, renewal) and wire them end to end before trying to personalise everything. ## Trend 2: Is AI intermediation a threat to ANZ brands? Braze calls this "Trust or bust". AI intermediation is when a customer deals with a brand through an LLM, AI agent or other autonomous tool instead of directly. | Measure | ANZ | Global | |---|---|---| | AI intermediation has weakened our ability to connect with customers directly | 68% | 63% | | Deploy advanced personalisation across channels to counter AI intermediation | 65% | 60% | | Use unique, human-centred customer experiences | 61% | 57% | | Run feedback loops through surveys and other tools | 51% | 55% | Braze also found ANZ brands are 1.5 times more likely than global peers to use a Trust-by-Design approach to responsible and ethical AI. Its advice: rethink segmentation with AI decisioning, move from campaign-level A/B tests to continuous individual-level optimisation, and use its TRUST framework. **Our read:** ANZ brands feel the threat more and are responding more, which is encouraging. Two things matter most. First, own the channels an agent can't easily replace: your app, your logged-in experience, and messaging people have opted into. Second, make your brand legible to the agents themselves. Clear, structured, accurate information about products, prices and policies is now part of customer engagement. The lower ANZ score on feedback loops (51% vs 55%) is an easy gap to close. ## Trend 3: Why aren't bigger budgets turning into revenue? Braze calls this "The revenue rollercoaster". | Measure | ANZ | Global | |---|---|---| | Expect marketing budget to increase in the next 12 months | 90% (highest of any region) | n/a | | Exceeded revenue goals last year | 61% | 67% | | Say ROI from AI is certain to generate growth | 98% | n/a | | Hesitation among leaders and staff is slowing AI adoption | 35% | 47% | | Using AI to predict customer desires improved satisfaction scores | 77% | 69% | Braze reports that the most popular use of AI is increasing efficiency through proven tactics, doing more without adding headcount. Its advice: use AI-driven analytics to experiment more boldly, use assistants to speed up production, and invest in training. **Our read:** confidence is not the constraint in ANZ. Measurement is. If 90% expect bigger budgets but fewer hit revenue targets, the next 12 months will be judged by the CFO, not the CMO. Every AI and engagement investment should have a holdout group and a revenue metric from day one. Pair lifecycle measurement with marketing mix modelling so you can show what engagement adds on top of media, not just what it touched. ## What should ANZ brands do next? Braze's conclusion is that ANZ is the most AI-confident and budget-optimistic region but lags on turning that into revenue. It points to three shifts: from data collection to real-time activation, from generic messages to trust-building personalisation, and from budget increases to measurable customer lifetime value. Here's how we'd turn that into a 90-day plan: 1. **Audit the last mile.** Map how long it takes for a customer action to change what they see next. If the answer is days, start there. 2. **Pick three real-time journeys.** Choose ones with a clear revenue or retention metric and build them end to end, from event to message to measurement. 3. **Fix identity before AI.** Agree one external ID, resolve anonymous to known users, and make sure your engagement platform and warehouse agree on who a customer is. 4. **Build content in modules.** Templates, content blocks and product data that can be assembled per person, so personalisation doesn't depend on writing more emails. 5. **Prove it with a holdout.** Keep a control group on every AI-driven programme and report incremental revenue, not opens. 6. **Make your brand easy for AI to read.** Publish clear, accurate, structured information about what you sell, so assistants represent you correctly. ## How Stitch can help Stitch is an Auckland consultancy and Braze Alloys Solutions Partner, Orbit tier, named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards in 2026. We led the Braze build for [Serko AI](/case-studies/serko-ai), shipping the lifecycle layer to production in six weeks, with real-time transactional messaging, Liquid personalisation and Data Warehouse to Braze through Cloud Data Ingestion. Most implementations take us 8 to 12 weeks. Not sure where you sit? Try our [Braze readiness scorecard](/braze/readiness-scorecard) or [book a 30-minute call](/connect). ## FAQ **What is the Braze ANZ Customer Engagement Review 2026?** It's Braze's annual regional report on customer engagement, based on a Wakefield Research survey of 200 ANZ marketing leaders (part of 2,200 globally) and anonymised data from 779 Braze customers. **How mature are ANZ brands at customer engagement?** According to Braze, 25% of ANZ brands are in the most mature "Ace" group, 42% are in "Accelerate" and 33% are in "Activate". **Are ANZ marketers more confident about AI than the rest of the world?** Yes. Only 35% of surveyed ANZ leaders said internal hesitation is slowing AI adoption, compared with 47% globally, and 98% said AI ROI is certain to generate growth. **Why are ANZ brands missing revenue goals?** Braze found 61% of ANZ brands beat revenue goals last year, against 67% globally. The report links this to fragmented data and slow activation: only 34% assemble content for individuals in real time. **What is AI intermediation?** It's when customers interact with a brand through an LLM, AI agent or other autonomous tool instead of directly. 68% of surveyed ANZ leaders said it has weakened their direct customer relationships. ## Sources - Braze, ANZ Customer Engagement Review 2026 (Wakefield Research survey of 200 ANZ marketing leaders; Braze customer data from 779 customers). Download from [braze.com](https://www.braze.com/resources/reports-and-guides/2026-anz-customer-engagement-review). --- URL: https://stitchtech.co/braze/braze-vs-customer-io ## In short Choose Braze if you run a high-volume, app-led or multi-market programme, need Australian data hosting, or want deep in-product messaging and AI decisioning. Choose Customer.io if you want a warehouse-friendly, flexible platform with published pricing that a lean lifecycle team can run well. Both are strong: the right pick depends on scale, data and team. ## Key takeaways - Braze is built for scale and in-product engagement, with 12 documented channels and an Australian hosting instance (AU-01) in Sydney. - Customer.io covers the core lifecycle channels, publishes starting prices, and models non-person data (accounts, courses, trips) natively through objects and relationships. - Both platforms pull data directly from Snowflake, BigQuery, Redshift and Databricks, so a warehouse-led stack works with either. - Customer.io currently offers US and EU data regions only. If data must stay in Australia, that matters. - Your team's capacity to run the platform day to day is as important as any feature list. ## What is the difference between Braze and Customer.io? Both are customer engagement platforms that send lifecycle, marketing and transactional messages triggered by customer behaviour. The difference is mostly about scale, depth and operating model. Braze describes itself as "the leading customer engagement platform" and says it serves more than 2,000 brands across more than 70 countries, including Canva ([Braze](https://www.braze.com/company)). Its pricing scales with monthly active users, and it is sold through editions with a sales conversation rather than published prices ([Braze pricing](https://www.braze.com/pricing)). Customer.io describes itself as a platform for "personalized journeys and better business outcomes across email, push, SMS, and in-app messaging" and says it is trusted by more than 9,000 brands ([Customer.io](https://customer.io/)). It publishes plan starting prices and charges on profiles and email volume ([Customer.io pricing](https://customer.io/pricing)). In practice, we see Braze chosen by teams with large, active app or web audiences and several channels to orchestrate in real time. Customer.io tends to suit product-led and data-led teams that want flexibility and a faster path to value without an enterprise procurement cycle. ## Which channels does each platform support? Braze documents 12 channels: in-app messages, Content Cards, Banners, email, transactional email, landing pages, LINE, live notifications, push, SMS/MMS/RCS, webhooks and WhatsApp ([Braze docs](https://www.braze.com/docs/user_guide/channels)). The in-product set (Content Cards, Banners, in-app) is a real strength for app-first brands. Customer.io lists email, transactional email, push, in-app, SMS, native WhatsApp, LINE and webhooks across its plans ([Customer.io pricing](https://customer.io/pricing)). For most lifecycle programmes that is plenty. If persistent in-app feeds or rich mobile surfaces are central to your strategy, Braze has more options. ## How do the data models compare? This is where the platforms feel most different to build on. Braze is user-centric. Its own documentation says "User profiles are the primary object in Braze," with non-user data held in catalogs or queried directly from your warehouse through connected sources ([Braze docs](https://www.braze.com/docs/user_guide/get_started/b2b_use_cases/b2b_data_models)). That works well, but complex nested data needs careful schema design. On Serko AI, we co-designed a flattened array schema with Braze to handle multi-leg trips within nesting limits. Customer.io lets you model non-person things as objects (for example a company, a course or a booking) and link people to them through relationships. You can segment on those relationships and trigger journeys when an object or relationship changes ([Customer.io docs](https://docs.customer.io/messaging/objects-data/objects/start/)). For B2B, education or multi-brand businesses, that can make journeys simpler to build. ## Which is better for a warehouse-led data stack? Both work well with a modern warehouse. Braze Cloud Data Ingestion syncs from Amazon Redshift, Databricks, Google BigQuery, Microsoft Fabric and Snowflake ([Braze docs](https://www.braze.com/docs/user_guide/data/cloud_ingestion)). We used it to feed Serko AI's data warehouse into Braze. Customer.io can sync in from Amazon Redshift, Databricks, Google BigQuery, Snowflake, Microsoft SQL Server, MySQL and PostgreSQL, and can send data back out to Snowflake, BigQuery and Redshift ([Customer.io integrations directory](https://docs.customer.io/integrations/directory/)). The Segment, Snowflake and Customer.io pattern sits under our work for Turners Cars and World Vision New Zealand. If you already run a CDP such as Segment, Tealium or Hightouch, either platform will sit comfortably downstream as the activation layer. ## How do pricing models compare? Braze does not publish prices. Its pricing page says "Pricing scales with your Monthly Active Users (MAU)," and a contract combines a platform edition (Go, Select, Pro or Enterprise), profiles, Action Credits for messaging and some AI features, services and optional add-ons ([Braze pricing](https://www.braze.com/pricing)). Customer.io publishes starting prices. Its Essentials plan starts at $100 a month with 5,000 profiles and 1 million emails included, Premium starts at $1,000 a month billed yearly, and Enterprise is custom ([Customer.io pricing](https://customer.io/pricing)). The page does not state the currency, so confirm it and the inclusions when you get a quote. Our advice: model total cost over three years, including SMS and WhatsApp sends, extra environments, implementation and the people needed to run it. The licence is rarely the whole story. ## Data residency for NZ and Australian brands Braze runs an Australian instance, AU-01 ([Braze API docs](https://www.braze.com/docs/api/basics)), following the launch of its Sydney data centre in January 2025 ([Braze](https://braze.com/resources/articles/braze-expands-investments-in-australia-and-new-zealand)). For Australian organisations with residency requirements, and NZ organisations that prefer data held close to home, this is a meaningful advantage. Customer.io offers two account regions, the United States and the European Union, with its EU data centre in Belgium. You choose the region when you create the account ([Customer.io docs](https://docs.customer.io/accounts/settings/data-centers/)). Many NZ and Australian brands run happily on either region, but if your privacy, security or procurement team needs data stored in Australia, raise it before you shortlist. ## What about AI features? Both platforms are investing heavily here. Braze groups its AI under BrazeAI, including BrazeAI Agents, BrazeAI Decisioning Studio for 1:1 offer and incentive decisions, BrazeAI Operator for building content, campaigns and Canvases from plain-language requests, plus Intelligent Channel, Intelligent Timing and item recommendations ([Braze](https://www.braze.com/product/brazeai)). Customer.io offers prompt-to-build segments, suggested segments, email content analysis, translation, in-app message suggestions, audience insights, an in-platform Agent and an MCP server for connecting AI tools ([Customer.io](https://customer.io/ai)). Braze leans further into predictive and decisioning capability for large audiences. Customer.io's AI focuses on helping smaller teams build and run faster. Test the features you would actually use, on your own data, before letting AI tip the decision. ## Braze vs Customer.io at a glance | Factor | Braze | Customer.io | |---|---|---| | Positioning | Enterprise customer engagement platform, 2,000+ brands | Customer engagement platform, 9,000+ brands | | Channels | 12 documented, including Content Cards, Banners, live notifications, RCS | Email, transactional, push, in-app, SMS, WhatsApp, LINE, webhooks | | Data model | User-centric profiles, plus catalogs and connected sources | People plus objects and relationships | | Warehouse sync in | Redshift, Databricks, BigQuery, Fabric, Snowflake | Redshift, Databricks, BigQuery, Snowflake, SQL Server, MySQL, PostgreSQL | | Pricing approach | Based on MAU, editions and Action Credits, not published | Based on profiles and email volume, starting prices published | | Data regions | US, EU, Australia (AU-01) and other APAC instances | US or EU (Belgium) | | AI | BrazeAI Agents, Decisioning Studio, Operator, predictive features | Prompt-to-build segments, content analysis, Agent, MCP server | | Best fit | High-volume, app-led, multi-market programmes | Lean lifecycle teams, product-led and warehouse-led businesses | | Time to value | Weeks with the right partner and clean data | Often faster for focused programmes | ## When we recommend Braze As a Braze Alloys Solutions Partner (Orbit tier) and Braze ANZ Rising Star of the Year 2026, these are the situations where we point clients to Braze: - **Real-time, high-stakes transactional messaging.** For Serko AI we built the lifecycle layer in six weeks from kick-off, using the Braze Transactional API for booking confirmations, flight disruption and 24-hour reminders, live from day one. - **Several channels coordinated around a product.** Serko AI uses Braze to coordinate two-way SMS, WhatsApp, on-page and in-app messaging alongside its AI travel agents. - **Warehouse-fed personalisation at speed.** Serko's warehouse feeds Braze through Cloud Data Ingestion, with Liquid personalisation on complex flight, hotel and cost data. - **Teams that need value quickly on solid foundations.** Skyline Enterprises appointed Stitch as its Braze onboarding partner, and has said we helped it achieve value from Braze within weeks. - **Australian data hosting is a requirement.** The AU-01 instance makes this straightforward. ## When we recommend Customer.io As a Customer.io Gold Agency Partner and APAC Partner Advisory Board member, these are the situations where Customer.io is usually our pick: - **A CDP and warehouse already sit at the centre.** For Turners Cars, the Segment, Snowflake and Customer.io stack supported closed-loop attribution work behind a 6.3x lift in lead volume (a 530 per cent increase) and a 68 per cent reduction in cost per lead. - **Rebuilding lifecycle after leaving a legacy tool.** For World Vision New Zealand we delivered an audience migration off HubSpot into Segment, with Customer.io as the messaging platform for journeys across child sponsorship, gifts and wills, emergency appeals and the supporter portal. - **Multi-market activation from one data layer.** Mr Apple uses Tealium for its customer data and Customer.io for lifecycle activation across four Asian markets. - **Teams that want transparent, predictable pricing** and a platform a small in-house team can own. ## Frequently asked questions **Is Braze better than Customer.io?** Neither is better across the board. Braze suits high-volume, app-led and multi-market programmes, while Customer.io suits lean lifecycle teams and warehouse-led businesses that want flexibility and published pricing. **Does Braze have an Australian data centre?** Yes. Braze launched a Sydney data centre in January 2025 and lists an AU-01 instance in its documentation. **Does Customer.io store data in Australia?** Not currently. Customer.io offers US and EU (Belgium) regions, chosen when the account is created. **Can we connect our data warehouse to either platform?** Yes. Both sync directly from Snowflake, BigQuery, Redshift and Databricks, and both work well downstream of a CDP like Segment, Tealium or Hightouch. **How long does implementation take?** It depends on scope and data readiness. We built Serko AI's lifecycle layer on Braze in six weeks from kick-off. **Can we migrate from HubSpot, Klaviyo or Mailchimp?** Yes. We migrate teams from HubSpot, ActiveCampaign, Klaviyo and Mailchimp onto Customer.io or Braze, as we did for World Vision New Zealand's move off HubSpot. ## Need a second opinion? Stitch is a partner on both platforms, so we recommend the one that fits your data, team and growth plans rather than defaulting to either. If you are weighing up Braze and Customer.io, [talk to us](https://stitchtech.co/connect). ## Sources - Braze, About: https://www.braze.com/company - Braze, Pricing: https://www.braze.com/pricing - Braze Docs, Channels: https://www.braze.com/docs/user_guide/channels - Braze Docs, Create a B2B data model: https://www.braze.com/docs/user_guide/get_started/b2b_use_cases/b2b_data_models - Braze Docs, Cloud Data Ingestion: https://www.braze.com/docs/user_guide/data/cloud_ingestion - Braze Docs, API basics (instances): https://www.braze.com/docs/api/basics - Braze, Braze expands investments in Australia and New Zealand: https://braze.com/resources/articles/braze-expands-investments-in-australia-and-new-zealand - Braze, BrazeAI: https://www.braze.com/product/brazeai - Customer.io, Home: https://customer.io/ - Customer.io, Pricing: https://customer.io/pricing - Customer.io Docs, Account regions: https://docs.customer.io/accounts/settings/data-centers/ - Customer.io Docs, Objects: https://docs.customer.io/messaging/objects-data/objects/start/ - Customer.io Docs, Integrations directory: https://docs.customer.io/integrations/directory/ - Customer.io, AI: https://customer.io/ai --- URL: https://stitchtech.co/braze/brazeai-decisioning ## In short BrazeAI Decisioning Studio uses reinforcement learning agents to choose the best offer, message, channel, timing and frequency for each customer, rather than for a segment. It's worth it when you have enough volume, a clear business metric, several real levers to pull and clean outcome data. Without those, simpler BrazeAI features such as Intelligent Timing or automatic variant optimisation will usually get you most of the value for less effort. ## Key takeaways - Decisioning Studio is the product that grew out of OfferFit, which Braze finished acquiring on 2 June 2025. It comes in Go (self-serve, engagement metrics) and Pro (any business metric, with Braze services support). - Agents pick a different answer for each person, using contextual bandits, within the actions and constraints you configure. - The deciding factors are volume, a single success metric, meaningful levers and trustworthy conversion data. - Measure it against a random control and your business-as-usual journey, and keep a no-message holdout to measure overall impact. - Most failures come from weak data or too few levers, not from the model. ## What is BrazeAI Decisioning Studio? Braze describes it simply: [decisioning agents "automatically discover the optimal action for every customer"](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio), and "Decisioning Studio finds a different answer for each person." The agents choose the best message, product, incentive, channel, timing and frequency for each customer. The technology came from OfferFit. Braze [completed its acquisition of OfferFit on 2 June 2025](https://www.braze.com/press-releases/braze-completes-acquisition-of-offerfit), describing it as a "highly customizable modern reinforcement learning engine". Braze now calls the product [BrazeAI Decisioning Studio Pro, "previously known as OfferFit by Braze"](https://www.braze.com/resources/articles/what-is-offerfit). There are [two editions](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio): - **Go** is self-serve and aimed at teams getting started. Its success metric is focused on engagement (clicks). - **Pro** offers the full feature set, can optimise for any business metric including revenue and conversions, can connect any customer data source, and comes with support from Braze's AI Decisioning Services team. ## How does AI decisioning differ from A/B testing? A classic A/B test finds one winner for the whole audience. Decisioning Studio uses [contextual bandits](https://www.braze.com/resources/articles/what-is-offerfit), which "determine the optimal choice for each individual, using context from every available data point." Separate agents can optimise each dimension, such as channel, timing, subject line, creative and offer, then combine them into the best package for each customer, and they keep adapting as behaviour changes. That's the real shift. Instead of "20% off wins", you get "this customer responds to free shipping by SMS on a Thursday evening, and that one needs no incentive at all." ## How does it fit with the rest of BrazeAI? Decisioning Studio sits alongside several other documented BrazeAI features. These are often the right first step: - **[Intelligent Timing](https://www.braze.com/docs/user_guide/brazeai/intelligence_suite/intelligent_timing)** sends each message when a user is most likely to open or click, based on their past sessions and engagement. Without data, it falls back to a time you choose. - **[Intelligent Channel](https://braze.com/docs/user_guide/brazeai/intelligence_suite/)** is a filter that uses user history to identify who responds better to push versus email. - **[Optimize with BrazeAI](https://www.braze.com/docs/user_guide/brazeai/intelligence_suite/variant_selection)** automatically shifts traffic towards stronger message variants. Braze's former Intelligent Selection page now redirects here. Multi-send campaigns need a conversion event and a re-eligibility window of at least 24 hours. - **[Predictive Churn](https://www.braze.com/docs/user_guide/brazeai/predictive_suite/predictive_churn)** and **[Predictive Events](https://www.braze.com/docs/user_guide/brazeai/predictive_suite/predictive_events)** (previously Predictive Purchases) score users from 0 to 100 on their likelihood to churn or perform an event, using gradient boosted decision trees. - **[BrazeAI Operator](https://www.braze.com/docs/user_guide/brazeai/operator)** is an assistant in the dashboard that helps build campaigns, Canvases, segments and content. It's a productivity tool, not a per-customer decisioning engine. The difference is scope. These features each optimise one thing. Decisioning Studio optimises several levers at once, per person, against a business outcome you define. ## When is AI decisioning worth it? Interest in ANZ is high. The [Braze, ANZ Customer Engagement Review 2026 (Wakefield Research survey of 200 ANZ marketing leaders)](https://www.braze.com/resources/reports-and-guides/2026-anz-customer-engagement-review) found 52% of surveyed ANZ brands use AI to predict customer needs, compared with 43% globally. Yet only 34% assemble content for individual users at the moment of engagement using real-time data. Prediction is common, acting on it per person is not. Decisioning tends to earn its keep when four conditions are met: 1. **Volume.** The agent learns by trying options and observing results, so it needs enough customers and decisions to learn from. Braze's audience documentation doesn't publish a minimum. 2. **A clear success metric.** Braze advises choosing a metric that aligns with [business objectives, "not proxy metrics like clicks or opens"](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/design_agents/), such as revenue, conversions, ARPU or customer lifetime value. 3. **Enough levers.** If you only have one offer and one channel, there's little to decide. Braze recommends focusing on the dimensions "most likely to have a significant impact on the success metric." 4. **Data quality.** Braze is blunt that ["high-quality data is the foundation of an effective Decisioning Studio agent"](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/prepare_data/). Key events such as [purchases, logins, cancellations and renewals](https://www.braze.com/resources/articles/what-is-offerfit) must be accurate and available. Good candidates are high-volume, repeatable decisions with a measurable outcome: renewal and winback offers, cross-sell, and onboarding nudges. ## What do you need in place first? - **Clean identity.** Decisioning Studio aligns on [Braze external IDs](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/prepare_data/), so your `external_id` strategy needs to be settled. - **Outcome data flowing back.** The agent needs data that "tell[s] the Agent how a customer reacts to its decisions", per the [setup steps](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio). Usually this comes from your warehouse or CDP. - **Orchestration.** With Braze, [Decisioning Studio sends through API-triggered campaigns](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/orchestration_setup/), one per base template, with trigger properties for each optimised dimension. Salesforce Marketing Cloud is also supported via API events and Journey Builder. - **An action bank and constraints.** The agent [can only take actions you configure](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/design_agents/). Constraints enforce business rules, such as blocking an offer in an ineligible region or capping spend. - **Templates built for variation.** Subject lines, creative and offers need to be modular enough to swap. ## How do you run a fair holdout test? Decisioning Studio divides customers into [treatment groups to run randomised controlled trials](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/audience/): - **Decisioning Studio:** customers get AI-optimised recommendations. - **Random Control:** customers get randomly selected options from the same action bank. - **Business-as-Usual (optional):** customers get your current journey. - **Holdout (optional):** customers get no communications. Each comparison answers a different question. Agent versus Random Control shows whether personalisation beats chance. Agent versus Business-as-Usual shows whether it beats what your team does today, which is the number your CFO cares about. Agent versus Holdout shows whether the programme drives incremental results at all. Braze reports [uplift as (Primary Group minus Comparison Group) divided by Comparison Group](https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/reporting/performance/), calculated from the KPI results. Practical rules: - Agree the success metric and comparison groups before launch, and don't change them midway. - Keep the Business-as-Usual journey genuinely unchanged during the test. - Give the agent time to learn before judging it. It learns by trying options, so early results include that exploration. - Confirm group sizing and significance testing with Braze, as the public docs don't specify either. ## What are the common pitfalls? - **Optimising a proxy.** An agent told to maximise clicks will find clicks, not revenue. - **Too few levers.** Two subject lines and one offer won't give the agent room to personalise. - **Broken outcome data.** If conversions arrive late or unmatched to `external_id`, the agent learns the wrong lessons. - **Missing constraints.** Without guardrails, an agent may give generous discounts to customers who'd have bought anyway. - **Treating it as set and forget.** Review insights, refresh the action bank, and retire options that never win. ## How Stitch can help Stitch is a Braze Alloys Solutions Partner (Orbit tier) and was named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards in 2026. We lead the IAB New Zealand AI Working Group. For Serko AI, Stitch was lead Braze partner on a lifecycle layer where Braze coordinates Serko's AI travel agents across two-way agentic SMS, WhatsApp, on-page and in-app messaging, with Cloud Data Ingestion from the data warehouse and GUID-based external ID resolution. That's the data and identity groundwork decisioning depends on. Our typical Braze implementation runs 8 to 12 weeks. ## FAQ **What is BrazeAI Decisioning Studio?** A Braze product that uses reinforcement learning agents to choose the best offer, message, channel, timing and frequency for each customer. It evolved from OfferFit, acquired by Braze in 2025. **What's the difference between Decisioning Studio Go and Pro?** Go is self-serve and optimises for engagement (clicks). Pro supports any business metric, any data source and includes Braze services support. **Do I need a data warehouse for AI decisioning?** Not strictly, but you need reliable customer and outcome data tied to Braze external IDs. A warehouse or CDP is the usual source. **How do I prove decisioning is working?** Compare the agent against a Random Control and your Business-as-Usual journey, and use a no-message Holdout to measure overall incrementality. **Is Intelligent Timing the same as AI decisioning?** No. Intelligent Timing optimises send time only. Decisioning Studio optimises several levers per customer against a business metric. ## Sources - https://www.braze.com/docs/user_guide/brazeai/decisioning_studio - https://www.braze.com/press-releases/braze-completes-acquisition-of-offerfit - https://www.braze.com/resources/articles/what-is-offerfit - https://www.braze.com/docs/user_guide/brazeai/intelligence_suite/intelligent_timing - https://braze.com/docs/user_guide/brazeai/intelligence_suite/ - https://www.braze.com/docs/user_guide/brazeai/intelligence_suite/variant_selection - https://www.braze.com/docs/user_guide/brazeai/predictive_suite/predictive_churn - https://www.braze.com/docs/user_guide/brazeai/predictive_suite/predictive_events - https://www.braze.com/docs/user_guide/brazeai/operator - https://www.braze.com/resources/reports-and-guides/2026-anz-customer-engagement-review - https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/design_agents/ - https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/prepare_data/ - https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/orchestration_setup/ - https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/audience/ - https://www.braze.com/docs/user_guide/brazeai/decisioning_studio/reporting/performance/ --- URL: https://stitchtech.co/braze/cloud-data-ingestion-snowflake-databricks ## In short Braze Cloud Data Ingestion (CDI) connects Braze directly to Snowflake, Databricks, BigQuery, Redshift and Microsoft Fabric, and syncs new or changed rows into Braze on a schedule or on demand. It handles user attributes, custom events, purchases, subscription states, catalogs and user deletes, using an `UPDATED_AT` column to work out what's new. For the return path, Braze offers Snowflake Data Sharing and Currents. ## Key takeaways - CDI supports five warehouses (Snowflake, Databricks, BigQuery, Redshift, Microsoft Fabric) plus S3, Azure Blob Storage and Google Cloud Storage. - Syncs are driven by an `UPDATED_AT` timestamp: get that column right and most problems go away. - Recurring syncs run every 15 minutes by default, down to every 5 minutes on request, and you can trigger syncs on demand. - CDI is a strong default when your warehouse is the source of truth. A reverse ETL tool earns its place when you need heavier transformation, orchestration or many destinations. - Design nested objects carefully. Every key in a nested object can count as a data point on legacy contracts, and payloads are capped. ## Which warehouses does Braze Cloud Data Ingestion support? According to [Braze's CDI documentation](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion), CDI connects to: - **Cloud data warehouses:** Amazon Redshift, Databricks, Google BigQuery, Microsoft Fabric and Snowflake - **Cloud file storage:** Amazon S3, Azure Blob Storage and Google Cloud Storage Braze says CDI is available in all Braze regions and any Braze region can connect to any source data region, which matters if you're on [AU-01](https://www.braze.com/docs/user_guide/data/infrastructure/data_centers/) and your warehouse sits elsewhere. Each warehouse has its own [connection set-up](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/integrations/): - **Snowflake:** key-pair authentication using a public key Braze provides, with a unique Snowflake user per Braze workspace. Auto-resume should be on for the warehouse. - **Databricks:** an OAuth service principal or a personal access token. Classic and Pro SQL warehouses can add two to five minutes of warm-up; serverless reduces this but "may result in slightly higher integration costs". - **BigQuery:** a service account, via Workload Identity Federation or a service account key, with access granted to the relevant datasets. If your warehouse uses network policies, allowlist the [Braze IPs for your instance](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/faqs/). ## How does a CDI sync work? You create a table or view in your warehouse that Braze reads from. For the [standard table set-up](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/table_setup/), each row needs: - **`UPDATED_AT`:** when the row was added or last changed - **An identifier:** `EXTERNAL_ID`, `ALIAS_NAME` with `ALIAS_LABEL`, `BRAZE_ID`, `EMAIL` or `PHONE`, with one identifier type per row - **`PAYLOAD`:** a JSON string of the fields to sync On each run, Braze [syncs rows where `UPDATED_AT` is later than the last value it synced](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/integrations/). That makes syncs incremental, but only if your timestamps are honest. Payload limits are worth knowing upfront. Braze says each row can carry [a JSON object with up to 250 attributes, and payloads over 1 MB are rejected](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion). By default, each run can sync up to 500 million rows. ## What types of data can you sync? CDI covers [user and non-user data](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion): - **User attributes**, including nested custom attributes, arrays of objects and subscription statuses - **Custom events**, with `name` required and `time`, `app_id` and `properties` optional - **Purchase events**, with `product_id`, `currency` and `price` required - **Subscription states**, as `subscription_group_id` and `subscription_state` pairs - **Catalog items**, for product, content or offer catalogs - **User deletion requests** Field-level requirements for events, purchases and subscriptions are on the [table set-up page](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/table_setup/). If an event row has no `time`, Braze uses `UPDATED_AT` as the event time. Braze's [best practices](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/best_practices/) say you can delete users by external ID, user alias or Braze ID. Braze also offers zero-copy options. According to its [comparison of ingestion options](https://www.braze.com/docs/user_guide/example_library/data/compare_data_ingestion_options), CDI Segments and CDI Canvas triggers keep warehouse data in place rather than writing it to profiles. Those queries run in your warehouse, so you pay the compute, but Braze doesn't log data points for them. ## How often can CDI sync? Braze says [recurring syncs can run as often as every 5 minutes or as rarely as once per month](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion). The dashboard default minimum is 15 minutes, and 5-minute syncs need Braze Support or your customer success manager. You can also trigger a sync through the API once a warehouse job finishes, which is often the cleanest pattern: your dbt or orchestration run completes, then Braze pulls the new rows. Only one sync can run per integration at a time. Two other things to plan for: - **Rate limits:** CDI [shares the rate limit with the Braze API](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion), so heavy syncs can compete with real-time `/users/track` traffic. - **Real-time needs:** if something must hit Braze within seconds, such as a booking or a password reset, send it via the SDK or REST API. Braze describes `/users/track` as [near real time](https://www.braze.com/docs/user_guide/example_library/data/compare_data_ingestion_options). ## How do you get Braze data back into the warehouse? The return path matters as much as ingestion. You need engagement data in the warehouse to measure lift, build attribution and feed models. - **Snowflake Data Sharing:** Braze shares a read-only database straight into your Snowflake account. What you get depends on your [Data Distribution entitlement](https://www.braze.com/docs/partners/data_and_analytics/data_warehouses/snowflake/data_sharing): engagement events, user behaviour events, or Profile 360 with profile and attribute changes. Shared data uses no storage in your account, so you pay only for compute when you query it. - **Currents:** Braze's [real-time stream of engagement events](https://www.braze.com/docs/user_guide/data/braze_currents/), delivered in Avro format. The [available Currents partners](https://www.braze.com/docs/user_guide/data/distribution/braze_currents/setting_up_currents/available_partners) for storage are Amazon S3, Google Cloud Storage and Azure Blob Storage, so for Databricks or BigQuery you'd typically land files in storage and load from there. Braze says a Currents connector is included in many pro and enterprise-level packages. - **Newer options:** In June 2026 Braze announced [User Profile Streaming and a Delta Sharing integration (beta) for Databricks](https://www.braze.com/resources/articles/2026-braze-data-platform-product-launch) that sends engagement signals back to the warehouse. ## When should you use CDI instead of a reverse ETL tool like Hightouch or Census? Braze itself says [many reverse ETL use cases can also be handled with native CDI](https://www.braze.com/resources/articles/exploring-the-technical-side-of-ingesting-data-into-braze), and that the choice depends on transformation, orchestration and data ownership. Here's how we'd frame it: **Use CDI when:** - Your warehouse is the source of truth and your data team can shape tables for Braze - Braze is the main or only destination - You want fewer tools and contracts to manage **Consider a reverse ETL tool like Hightouch or Census when:** - You need to send the same audiences to Braze and to ad platforms, CRM or support tools - Marketers want a visual audience builder over warehouse models - You want change detection handled for you. Hightouch, for example, says it [only syncs data that needs updating and sends only changed columns](https://hightouch.com/docs/destinations/braze), though it notes this can be slower than overwriting Plenty of stacks use both: CDI for core profile and event data, and a reverse ETL tool for cross-channel audiences. ## What are the common CDI pitfalls? - **Bad `UPDATED_AT` values.** A view using `CURRENT_TIMESTAMP` re-syncs everything every run. Future timestamps make later syncs skip rows. Late rows with older timestamps never sync. Braze recommends [UTC timestamps and writing rows that share a timestamp in a single transaction](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/best_practices/). - **Re-syncing full profiles.** Braze updates or adds fields, so you don't need to sync the whole profile each time. Send changes only. - **Data point consumption.** If you're on a legacy data point contract, CDI is [billed like `/users/track`](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion). Braze says that [as of Spring 2025 it no longer bills new customers on data points](https://www.braze.com/docs/user_guide/data/infrastructure/data_points), but older multi-year contracts may still be. Check yours. - **Nested objects.** On data point billing, [every key in a nested object counts as a data point](https://www.braze.com/docs/user_guide/data/infrastructure/data_points), and arrays of objects consume a data point for each key updated. Deep nesting also makes Liquid templates harder to maintain. - **Type drift.** Keep column types consistent between syncs, cast numbers explicitly and store dates as timestamps, not strings. ## What does CDI look like in a real implementation? Stitch was lead Braze partner for Serko AI, working alongside Braze's onboarding team. Serko's data flows from its data warehouse into Braze via Cloud Data Ingestion, alongside the Braze Web SDK and a server-side integration via GTM. Multi-leg trips were the tricky part. We co-designed a flattened `active_flights` array schema with Braze to work around nesting limits, then used Liquid to personalise messages with complex flight, hotel and cost objects. The lifecycle layer shipped to production in six weeks from kick-off, with booking confirmation, disruption SMS and 24-hour reminder flows active from day one. ## How Stitch can help Stitch is an independent Auckland consultancy and a Braze Alloys Solutions Partner (Orbit tier), named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards in 2026. We're also a Hightouch Implementation Partner and Segment Certified Partner, so we can help you pick the right ingestion pattern rather than defaulting to one tool. We design warehouse schemas for Braze, set up CDI and the return path, and build the lifecycle programmes that use the data. Typical implementations take 8 to 12 weeks. ## FAQ **Does Braze Cloud Data Ingestion support Databricks and BigQuery?** Yes. Braze lists Snowflake, Databricks, Google BigQuery, Amazon Redshift and Microsoft Fabric as supported warehouses, plus S3, Azure Blob Storage and Google Cloud Storage. **How often can Braze CDI sync?** Every 15 minutes by default, down to every 5 minutes if you ask Braze Support, or as rarely as monthly. You can also trigger a sync via the API after a warehouse job finishes. **What is the UPDATED_AT column for?** Braze uses it to find rows added or changed since the last sync. If it's wrong, rows get skipped or re-synced, so keep it accurate and in UTC. **Can CDI delete users in Braze?** Yes. Braze supports user deletion requests through CDI, using external ID, user alias or Braze ID. **Do I need Hightouch or Census if I have CDI?** Not always. CDI covers many warehouse-to-Braze use cases. A reverse ETL tool helps when you need many destinations, visual audience building or managed change detection. ## Sources - https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion - https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/integrations/ - https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/table_setup/ - https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/best_practices/ - https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/faqs/ - https://www.braze.com/docs/user_guide/example_library/data/compare_data_ingestion_options - https://www.braze.com/docs/user_guide/data/infrastructure/data_points - https://www.braze.com/docs/user_guide/data/infrastructure/data_centers/ - https://www.braze.com/docs/partners/data_and_analytics/data_warehouses/snowflake/data_sharing - https://www.braze.com/docs/user_guide/data/braze_currents/ - https://www.braze.com/docs/user_guide/data/distribution/braze_currents/setting_up_currents/available_partners - https://www.braze.com/resources/articles/2026-braze-data-platform-product-launch - https://www.braze.com/resources/articles/exploring-the-technical-side-of-ingesting-data-into-braze - https://hightouch.com/docs/destinations/braze --- URL: https://stitchtech.co/braze/data-residency-australia ## In short AU-01 is Braze's Australian data centre, launched in Sydney in January 2025, and it lets ANZ brands host their Braze workspace data locally. You choose it when your Braze account is set up, so it's a contract-time decision. Local hosting helps with privacy and governance, but it doesn't mean no data ever leaves Australia: some sub-processors, AI features and support teams sit offshore, so you still need to read the sub-processor list and do your privacy homework. ## Key takeaways - Braze lists AU-01 alongside its US, EU, Indonesian, Japanese and South Korean data centres, with its own dashboard, REST and SDK endpoints. - You pick a region-specific data centre when you set up your Braze account. Braze's public docs don't describe a simple way to move an existing workspace between data centres. - Braze's current sub-processor list shows Australian locations for AWS hosting, Snowflake and ClickHouse, but other sub-processors (including AI model providers and monitoring) are listed in the US or EU. - Under the NZ Privacy Act 2020 and Australia's Privacy Act 1988, you generally stay responsible for personal information held by a provider on your behalf, wherever it's hosted. - Ask Braze specific questions about AU-01 before you sign, and get the answers in writing. ## What is Braze AU-01? Braze runs its platform across what it calls [data centres in different regions around the world](https://www.braze.com/docs/user_guide/data/infrastructure/data_centers/), also referred to as [clusters or instances](https://www.braze.com/docs/user_guide/administrative/access_braze/sdk_endpoints). AU-01 is the Australian one. Its endpoints are: - Dashboard: `dashboard.au-01.braze.com` - REST API: `rest.au-01.braze.com` - SDK: `sdk.au-01.braze.com` Braze announced in December 2024 that it would open [a new local data centre in Sydney](https://braze.com/resources/articles/braze-expands-investments-in-australia-and-new-zealand), confirming the launch in January 2025, and positioned it for brands in both Australia and New Zealand. Other Braze docs also reference the Sydney region. For example, Braze's [Snowflake Data Sharing page](https://www.braze.com/docs/partners/data_and_analytics/data_warehouses/snowflake/data_sharing) lists AP-Southeast-2 (Sydney) as one of the regions where Braze hosts user-level data, and the [Cloud Data Ingestion FAQ](https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/faqs/) publishes a separate IP allowlist for AU-01. ## Which Braze data centres are available? Braze's [data centres page](https://www.braze.com/docs/user_guide/data/infrastructure/data_centers/) lists six regions: | Region | Instances | |---|---| | United States | US-01 to US-08, US-10 | | European Union | EU-01, EU-02 | | Australia | AU-01 | | Indonesia | ID-01 | | Japan | JP-01 | | South Korea | KR-01 | For ANZ brands, the realistic choice is usually AU-01 or a US instance. ## How is the data centre chosen, and can you change it later? Braze says that [when you set up your Braze account, you can sign up for region-specific data centres](https://www.braze.com/docs/user_guide/data/infrastructure/data_centers/), and suggests talking to your account manager about which one fits where your users are. Braze also notes that [your onboarding manager will tell you which cluster you're on](https://www.braze.com/docs/user_guide/administrative/access_braze/sdk_endpoints). The docs don't describe a switch to move an existing workspace to another data centre. Braze's guide to [migrating data between workspaces and instances](https://www.braze.com/docs/user_guide/administer/global/create_and_manage_workspaces/migrate_workspace_data) makes clear that a move is a rebuild, not a toggle: user profiles "don't transfer as a packaged unit", segment definitions stay in the source workspace, message history stays behind, and channel settings such as sending domains and WhatsApp numbers are workspace-scoped. For large or special account moves, it says to contact Braze Support. The practical lesson: treat the data centre as a contract-time decision. Changing it later is a migration project, with SDK endpoint changes, re-imports and channel set-up to redo. ## What data is stored in AU-01, and what isn't? This is where marketing claims and legal reality can drift apart, so it pays to read the detail. Braze's [current sub-processor list](https://cdn.sanity.io/files/b7pblshe/marketing-prod/56073d92ae50195865f0258019982d5c3263bb0a.pdf) (last modified 1 June 2026, linked from [braze.com/subprocessors](https://www.braze.com/subprocessors)) shows Australia as a location for: - Amazon Web Services (third-party hosting, and email delivery via SES) - Snowflake (hosting data for advanced reporting and business intelligence) - ClickHouse (hosting analytical data for reporting) The same list shows a number of sub-processors located only in the United States, or the US and EU, including: - AI model and infrastructure providers (Anthropic, OpenAI and Google), described as supporting "data processing and advanced platform features" - DataDog for monitoring, where Braze "may provide End User metadata, such as user identifiers" for troubleshooting - Rackspace, which hosts and stores End User profiles (listed as US and EU) - Email and mobile message delivery providers such as SendGrid, Sparkpost and Infobip - Global content delivery networks (Cloudflare, Fastly) The list also names Braze group entities in Australia, the US, the UK, Ireland, Singapore and other countries that provide "customer success, business operations and technical and engineering support services". Braze notes that "not all Sub-processors will be needed" depending on how a customer uses the services, including geographic location. So the list alone doesn't tell you exactly what applies to an AU-01 workspace. That's a question to put to Braze directly. Braze's [Data Processing Addendum](https://braze.com/company/legal/dpa) sets out how Braze processes personal data, and the sub-processor list says customers can subscribe for notice of new sub-processors. ## What does the NZ Privacy Act 2020 say about overseas data? This is general information, not legal advice. Talk to your privacy officer or lawyer about your own situation. Information Privacy Principle 12 controls [disclosing personal information outside New Zealand](https://www.privacy.org.nz/privacy-principles/12/). Before disclosing overseas, an agency must be satisfied that the recipient is subject to the Act, has comparable safeguards, is bound by an agreement such as the model contract clauses, or falls under a prescribed scheme or country. Otherwise, the individual must authorise it after being expressly told the information may not be protected to a comparable standard. Using a cloud provider is often treated differently. Under section 11, a provider that holds information [solely on your behalf, and not for its own purposes](https://www.privacy.org.nz/resources-and-learning/a-z-topics/working-with-third-party-providers/), isn't treated as holding it, so the transfer isn't a disclosure. The catch is that "your organisation remains fully responsible under the Privacy Act for what happens to that information", and the Office of the Privacy Commissioner asks you to consider your practical ability to control information held by an overseas provider. If the provider uses the information for its own purposes, both parties may hold it and IPP 12 may come into play. The OPC's [guidance on sending information overseas](https://www.privacy.org.nz/responsibilities/disclosing-personal-information-outside-new-zealand/) says that in most circumstances you'll remain responsible for personal information you put in cloud servers. For NZ brands, AU-01 is still offshore. It's closer and in a jurisdiction with comparable privacy law, but it doesn't remove your obligations. ## What does Australia's APP 8 require? Again, this is general information, not legal advice. Australian Privacy Principle 8 requires an APP entity to take [reasonable steps to ensure an overseas recipient doesn't breach the APPs](https://www.oaic.gov.au/privacy/australian-privacy-principles/australian-privacy-principles-guidelines/chapter-8-app-8-cross-border-disclosure-of-personal-information) before disclosing personal information overseas, usually through an enforceable contract. Under section 16C, the Australian entity can be accountable for the overseas recipient's acts. The OAIC guidelines say that providing information to an overseas contractor is usually a disclosure, but storing it with an overseas cloud provider may be a "use" if you keep effective control, for example through a binding contract limiting the provider's handling, and the ability to access, change, retrieve and delete the data. Even then, you still hold the information and remain responsible for it. AU-01 can reduce how much personal information crosses the border for Australian brands, which may simplify your APP 8 analysis. The offshore sub-processors and support access noted above are what you'll still need to assess. ## How does this compare with platforms that only offer US and EU regions? Not every customer engagement platform offers ANZ hosting. Customer.io, for example, offers [two data centre regions: the US and the EU](https://docs.customer.io/accounts/settings/data-centers/), and doesn't support data centre migrations except in extenuating circumstances. That doesn't make it a worse choice, as US or EU hosting can work well with the right contracts in place. But if local hosting is a firm requirement from your board or privacy team, AU-01 is one way to meet it. ## What questions should you ask Braze about AU-01? - Which data, exactly, is stored in AU-01: profiles, event data, message content, media assets, exports, backups? - Which sub-processors on the list apply to an AU-01 workspace, and from which locations? - Which BrazeAI features send data to US-based AI providers, and can they be switched off? - Where are support and engineering staff who can access our workspace located, and how is that access controlled? - How are Currents exports and Snowflake Data Sharing hosted for AU-01? - What's the process and cost if we ever need to move data centres? - How will we be notified of sub-processor changes? ## How Stitch can help Stitch is an independent Auckland consultancy and a Braze Alloys Solutions Partner (Orbit tier), named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards in 2026. We work across media, martech, data and AI for New Zealand and Australian brands. We help teams make the data centre decision before contracts are signed, map what data goes where, and set up the integration so your privacy team has clear answers. Typical Braze implementations take 8 to 12 weeks. If you're weighing up Braze or reviewing an existing set-up, get in touch. ## FAQ **Does Braze have an Australian data centre?** Yes. Braze lists AU-01 as its Australian data centre, launched in Sydney in January 2025, with its own dashboard, REST and SDK endpoints. **Can New Zealand brands use AU-01?** Yes. Braze positioned the Sydney data centre for brands in Australia and New Zealand. For NZ brands, it's still an overseas location, so Privacy Act 2020 obligations still apply. **Can I move my Braze workspace from a US instance to AU-01?** Braze's public docs don't describe a simple switch. Moving between instances is a migration project: profiles, segments, channel settings and history don't transfer as a package. Ask Braze about options before signing. **Does AU-01 mean no data leaves Australia?** No. Braze's sub-processor list includes US and EU locations for some services, such as AI models, monitoring and message delivery, and support teams are spread across several countries. Confirm the details for your workspace with Braze. **Is this legal advice?** No. This is general information about IPP 12 and APP 8. Get advice from your privacy officer or lawyer for your specific situation. ## Sources - https://www.braze.com/docs/user_guide/data/infrastructure/data_centers/ - https://www.braze.com/docs/user_guide/administrative/access_braze/sdk_endpoints - https://braze.com/resources/articles/braze-expands-investments-in-australia-and-new-zealand - https://www.braze.com/docs/partners/data_and_analytics/data_warehouses/snowflake/data_sharing - https://www.braze.com/docs/user_guide/data/unification/cloud_ingestion/faqs/ - https://www.braze.com/docs/user_guide/administer/global/create_and_manage_workspaces/migrate_workspace_data - https://www.braze.com/subprocessors - https://cdn.sanity.io/files/b7pblshe/marketing-prod/56073d92ae50195865f0258019982d5c3263bb0a.pdf - https://braze.com/company/legal/dpa - https://www.privacy.org.nz/privacy-principles/12/ - https://www.privacy.org.nz/resources-and-learning/a-z-topics/working-with-third-party-providers/ - https://www.privacy.org.nz/responsibilities/disclosing-personal-information-outside-new-zealand/ - https://www.oaic.gov.au/privacy/australian-privacy-principles/australian-privacy-principles-guidelines/chapter-8-app-8-cross-border-disclosure-of-personal-information - https://docs.customer.io/accounts/settings/data-centers/ --- URL: https://stitchtech.co/braze/implementation-checklist ## In short Most Braze implementations take 8 to 12 weeks from kick-off to first live journeys. The order matters more than the speed: lock your identity and data model first, then integrate SDKs and data feeds, set up channels (with email IP warming and SMS sender registration running in the background), build in Canvas, test properly and launch with a short optimisation window. ## Key takeaways - Decide your `external_id` strategy before anyone writes SDK code. Braze won't let you turn an identified user back into an anonymous one. - Start channel admin early. DNS delegation, IP warming, WhatsApp template approval and Australian sender ID registration all have lead times you don't control. - Use Cloud Data Ingestion for warehouse data and the SDKs for behavioural data, rather than forcing one route to do both jobs. - Build reusable pieces (Content Blocks, Liquid patterns) before you build Canvases, not after. - A tight first release can go live faster than 12 weeks. Stitch's Serko AI lifecycle layer reached production six weeks from kick-off. ## How long does a Braze implementation take? At Stitch, a typical implementation runs 8 to 12 weeks, and that holds for composable builds too, where Braze sits alongside a warehouse or CDP. The 12-week plan below leaves room for real-world delays such as legal sign-off, app store releases and DNS changes. Shorter is possible when the first release is scoped tightly. For Serko AI, where Stitch was lead Braze partner working alongside Braze's onboarding team, the lifecycle layer shipped to production in six weeks from kick-off. Booking confirmation, disruption SMS and 24-hour reminder flows were live from day one of the US beta on 9 May 2026. | Weeks | Phase | |---|---| | 1 to 2 | Discovery and planning | | 2 to 3 | Data model and `external_id` strategy | | 3 to 6 | SDK integration (web, iOS, Android) | | 4 to 7 | Data ingestion | | 2 to 9 | Channel setup, including IP warming and sender registration | | 6 to 9 | Liquid, Content Blocks and Canvas build | | 9 to 10 | QA | | 11 | Launch | | 12 | Optimisation and handover | ## What happens in discovery? Discovery sets the scope of your first release. Agree the three to five journeys that matter most, the channels each one needs, and the events and attributes that trigger and personalise them. This is also where you design your workspace structure. Braze describes a [workspace](https://www.braze.com/docs/user_guide/administer/global/create_and_manage_workspaces) as "a shared environment for you to track and manage engagement for related mobile apps or websites", and notes that a new workspace doesn't inherit historical data or user profiles from another one. Leave discovery with a written tracking plan, a journey list with owners, and a list of external dependencies (app release dates, DNS access, legal review). ## How should you design your data model and external_id strategy? The `external_id` is the identifier you assign once you can recognise a user, and it lets Braze [identify the same user profile across multiple devices](https://www.braze.com/docs/user_guide/data/user_data_collection/user_profile_lifecycle/). Two rules from Braze's own guidance shape everything else: - Don't assign an `external_id` before you can uniquely identify the person, and once a user is identified you can't make them anonymous again. - Braze [recommends UUIDs](https://www.braze.com/docs/developer_guide/analytics/setting_user_ids/) and lists email addresses, visible usernames and auto-incrementing IDs as not recommended. For anything that isn't your primary key, such as a CRM or BI tool ID, use [user aliases](https://www.braze.com/docs/user_guide/data/user_data_collection/user_profile_lifecycle/). An alias is a label and name pair, and you can set as many as you need on a profile. When an anonymous user is later identified with an existing `external_id`, Braze merges selected fields into the known profile, and the identified user's values win where data conflicts. In the same phase, define custom attributes, custom events and purchase events, plus any nested structures. For Serko, Stitch used GUID-based external ID resolution and co-designed a flattened `active_flights` array schema with Braze to work around nesting limits on multi-leg trips. ## What does SDK integration involve for web, iOS and Android? Braze publishes SDKs for [Web, Android, Swift and several cross-platform frameworks](https://www.braze.com/docs/developer_guide/sdk_integration), including React Native and Flutter. The core steps are similar on each platform: install the SDK, initialise it with your API key and SDK endpoint from the dashboard, and call `changeUser` with the `external_id` when the user logs in. Watch these details: - On web, Braze advises calling `openSession` after `changeUser`, otherwise you can lose session data for anonymous users. - Don't call `changeUser` on logout, and never use a shared or default ID. Braze [warns against both](https://www.braze.com/docs/developer_guide/analytics/setting_user_ids/). - If you hash an identifier instead of using a UUID, implement SDK authentication to prevent user impersonation. - Book mobile release dates early. ## How do you get data into Braze? Use the SDKs for real-time behaviour, and [Cloud Data Ingestion (CDI)](https://www.braze.com/docs/user_guide/data/cloud_ingestion/) for data that already lives in your warehouse. CDI connects directly to Snowflake, BigQuery, Redshift, Databricks and Microsoft Fabric, as well as S3, Azure Blob Storage and Google Cloud Storage. It syncs user attributes (including nested attributes and subscription statuses), custom events, purchases and catalog items, on a schedule as often as every five minutes. Serko's data warehouse feeds Braze this way. For one-off loads, Braze also supports [CSV import and the `/users/track` REST endpoint](https://www.braze.com/docs/user_guide/data/user_data_collection/user_import/). Plan the outbound direction too: [Braze Currents](https://www.braze.com/docs/user_guide/data/braze_currents/) streams engagement events in real time to your warehouse or analytics tools. ## What channel setup has the longest lead time? ### Email: domains, authentication and IP warming Braze's [email setup](https://braze.com/docs/user_guide/channels/email/email_setup) starts with delegating a sending subdomain, after which Braze manages SPF and DKIM for your sending and tracking domains. Set a [DMARC policy on your root domain](https://www.braze.com/docs/user_guide/channels/email/email_setup/authentication) as well. Use separate IP pools if you want to keep transactional and marketing reputation apart. Then warm your IPs. Braze calls this [required](https://www.braze.com/docs/user_guide/channels/email/email_setup/ip_warming) and publishes conservative, moderate and aggressive schedules, all starting at 50 emails on day one. Start with your most engaged contacts, warm to your average daily volume rather than your peak, and use the built-in user limit on campaigns to control volume. Reputation data is typically kept for about 30 days, so a month of silence means warming again. ### SMS and WhatsApp In Braze, SMS sending numbers sit inside [subscription groups](https://www.braze.com/docs/user_guide/channels/sms_mms_and_rcs/message_setup/subscription_groups), and users are subscribed or unsubscribed per group, so you can separate transactional and promotional traffic. If you send to Australian numbers with an alphanumeric sender ID, register it in the ACMA SMS Sender ID Register. [From 1 July 2026, unregistered sender IDs are replaced with "Unverified"](https://www.acma.gov.au/sites/default/files/2026-01/SMS%20Sender%20ID%20Register%20user%20guide%20for%20businesses%20and%20organisations_Dec%202025.pdf). For New Zealand numbers, confirm sender requirements with your SMS provider early. [WhatsApp in Braze](https://braze.com/docs/user_guide/channels/whatsapp/whatsapp_setup) needs a Meta Business account and a WhatsApp Business account, connected through embedded signup. Only Meta-approved templates can start conversations, so submit templates as soon as copy is agreed. ## How should you build templates and Canvases? Build the reusable layer first. [Content Blocks](https://www.braze.com/docs/user_guide/engagement_tools/templates_and_media/content_blocks/) hold cross-channel content such as headers, footers and offer codes in one library (up to 50kB each, nestable only one level deep). [Liquid](https://www.braze.com/docs/user_guide/personalization_and_dynamic_content/liquid/) handles personalisation and conditional logic, and [Connected Content](https://www.braze.com/docs/user_guide/personalization_and_dynamic_content/connected_content/) pulls information from an API into a message at send time. Then build journeys in [Canvas](https://www.braze.com/docs/user_guide/engagement_tools/canvas/), Braze's interface for multi-message campaigns, using steps such as Message, Delay, Decision Split, Action Paths, Experiment Paths and Audience Paths. ## What should QA cover before launch? Test the data before the messages. Confirm that profiles merge as expected, events arrive with the right properties, and subscription states are correct. Then test each Canvas path with real test profiles, every Liquid fallback for missing data, every channel's opt-out, and rendering across devices. Braze notes that it [doesn't support all of Shopify's Liquid](https://www.braze.com/docs/user_guide/personalization_and_dynamic_content/liquid/), so test templates rather than assuming. ## What happens at launch and after? Launch transactional and high-value triggered journeys first, while email volume is still warming. Use week 12 to review delivery, conversion and data quality, then agree a backlog for the next release. ## Printable Braze implementation checklist **Discovery** - First-release journeys, channels and owners agreed - Workspace structure decided - Tracking plan written (events, attributes, purchases) - External dependencies listed with dates **Data model** - `external_id` format agreed (UUID or equivalent, not email) - Login and logout identification rules documented - User alias labels defined for secondary IDs - Nested attributes and arrays designed **SDKs** - Web SDK installed, `changeUser` and `openSession` order checked - iOS and Android SDKs installed and app releases booked - SDK authentication considered **Data ingestion** - Cloud Data Ingestion syncs configured and scheduled - Historical import plan agreed (CSV or API) - Currents destination agreed **Channels** - Sending subdomain delegated, DMARC set - IP pools agreed, warming schedule chosen and started - SMS subscription groups created, Australian sender IDs registered - WhatsApp accounts connected and templates submitted **Build** - Content Blocks and Liquid patterns built - Connected Content endpoints tested - Canvases built with fallbacks **QA and launch** - Profile merge and event tests passed - Every path tested with test users - Opt-outs tested on every channel - Launch sequence and rollback plan agreed ## How Stitch can help Stitch is an independent Auckland consultancy and a Braze Alloys Solutions Partner (Orbit tier), named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards in 2026. Skyline Enterprises appointed Stitch as its Braze onboarding partner in 2026. For Serko AI, Stitch delivered the Braze Web SDK, Transactional API flows, a dual sender architecture, Cloud Data Ingestion from the warehouse and server-side integration via GTM, shipping to production six weeks from kick-off. Our typical timeline is 8 to 12 weeks. ## FAQ **How long does a Braze implementation take?** Typically 8 to 12 weeks from kick-off to live journeys. A tightly scoped first release can be faster: Serko AI's went live in six weeks. **What should be decided first in a Braze implementation?** Your `external_id` strategy. Braze recommends UUIDs, and identified users can't be made anonymous again, so changing course later is expensive. **Do I need to warm my IP addresses in Braze?** Yes. Braze describes IP warming as required and recommends starting with your most engaged users and building to your average daily volume. **Can Braze read data directly from my warehouse?** Yes. Cloud Data Ingestion syncs attributes, events, purchases and catalogs from Snowflake, BigQuery, Redshift, Databricks and Microsoft Fabric. **Do Australian SMS senders need to register?** Yes, if you use an alphanumeric sender ID. From 1 July 2026, unregistered IDs show as "Unverified" in Australia. ## Sources - https://www.braze.com/docs/user_guide/administer/global/create_and_manage_workspaces - https://www.braze.com/docs/user_guide/data/user_data_collection/user_profile_lifecycle/ - https://www.braze.com/docs/developer_guide/analytics/setting_user_ids/ - https://www.braze.com/docs/developer_guide/sdk_integration - https://www.braze.com/docs/user_guide/data/cloud_ingestion/ - https://www.braze.com/docs/user_guide/data/user_data_collection/user_import/ - https://www.braze.com/docs/user_guide/data/braze_currents/ - https://braze.com/docs/user_guide/channels/email/email_setup - https://www.braze.com/docs/user_guide/channels/email/email_setup/authentication - https://www.braze.com/docs/user_guide/channels/email/email_setup/ip_warming - https://www.braze.com/docs/user_guide/channels/sms_mms_and_rcs/message_setup/subscription_groups - https://www.acma.gov.au/sites/default/files/2026-01/SMS%20Sender%20ID%20Register%20user%20guide%20for%20businesses%20and%20organisations_Dec%202025.pdf - https://braze.com/docs/user_guide/channels/whatsapp/whatsapp_setup - https://www.braze.com/docs/user_guide/engagement_tools/templates_and_media/content_blocks/ - https://www.braze.com/docs/user_guide/personalization_and_dynamic_content/liquid/ - https://www.braze.com/docs/user_guide/personalization_and_dynamic_content/connected_content/ - https://www.braze.com/docs/user_guide/engagement_tools/canvas/ --- URL: https://stitchtech.co/braze/migrating-to-braze ## In short Migrating to Braze is a rebuild, not a lift and shift. Profiles, consent states and push tokens can be moved with planning, but journeys, templates and most engagement history need to be rebuilt or re-modelled for Braze. The safest path is to settle identity and consent mapping first, warm your new email IPs while the old platform keeps running, then move journeys across in priority order. ## Key takeaways - Consent is the highest-risk item. Map every opt-in and opt-out from the old platform to Braze global subscription states and subscription groups before importing anyone. - Choose your import route by job: CSV for one-off loads, `/users/track` for API loads and push tokens, Cloud Data Ingestion for ongoing warehouse syncs. - Journeys don't transfer. SFMC Journey Builder journeys, Klaviyo flows and HubSpot workflows all need to be rebuilt as Braze Canvases. - Plan a parallel-run period. New IPs need warming, and Braze calls warming required. - Decide early what history you actually need. Most teams need far less than they think. ## What moves to Braze, and what doesn't? | Item | Moves? | How | |---|---|---| | User profiles and attributes | Yes | CSV import, API or Cloud Data Ingestion | | Email and SMS consent | Yes, with mapping | Subscription states and subscription groups | | Mobile push tokens | Mostly | API import or automatic SDK capture | | Web push tokens | No | Re-permission users | | Historical events and purchases | Selectively | CSV (custom events) or API | | Templates | Rebuild | HTML can be reused, logic rewritten in Liquid | | Journeys and automations | Rebuild | Canvas | | IP and domain reputation | No | Warm new IPs | A few of these deserve detail. Braze CSV import [doesn't support arrays, push tokens or custom event data types in user import](https://www.braze.com/docs/user_guide/audience/manage_audience/import_users/csv_import), so tokens go through the API. For mobile push, Braze notes that [tokens for opted-in users are migrated automatically the next time they open your app](https://braze.com/docs/help/help_articles/push/push_token_migration) once the SDK is live, and you can import them earlier through `/users/track`. Web push tokens [can't be migrated through the API](https://braze.com/docs/help/help_articles/push/push_token_migration), so budget for a re-permission prompt. Templates are the other surprise. Your HTML and design system can come across, but personalisation logic from the old platform has to be rewritten in [Liquid](https://www.braze.com/docs/user_guide/personalization_and_dynamic_content/liquid/), which Braze supports up to Liquid 5 but not in full. Move shared headers, footers and offer codes into [Content Blocks](https://www.braze.com/docs/user_guide/engagement_tools/templates_and_media/content_blocks/) as you go. ## How do you import users into Braze? Braze supports [four main routes](https://www.braze.com/docs/user_guide/data/user_data_collection/user_import/): Braze CSV import, a Lambda-based CSV import from S3, the `/users/track` REST endpoint, and Cloud Data Ingestion. - **CSV import** suits one-off backfills. Attribute files can be up to 500 MB and custom event files up to 50 MB. Each file must use [one identifier type](https://www.braze.com/docs/user_guide/audience/manage_audience/import_users/csv_import): `external_id`, `braze_id`, a user alias, email or phone. You can't mix `external_id` and aliases in one file. - **The REST API** suits engineering-led loads and anything CSV doesn't support, such as push tokens. - **[Cloud Data Ingestion](https://www.braze.com/docs/user_guide/data/cloud_ingestion/)** suits teams with a warehouse. It syncs attributes (including subscription statuses), events, purchases and catalogs from Snowflake, BigQuery, Redshift, Databricks or Microsoft Fabric. If your warehouse is the source of truth, this is usually the cleanest migration path because the same pipeline keeps running after cutover. Whatever the route, settle your `external_id` first. Braze [recommends UUIDs](https://www.braze.com/docs/developer_guide/analytics/setting_user_ids/) and advises against using email addresses as user IDs. Old platform IDs can be kept as [user aliases](https://www.braze.com/docs/user_guide/data/user_data_collection/user_profile_lifecycle/) for reconciliation. ## How do you map consent and subscription groups? Braze has two layers. For email, global subscription states are `opted_in`, `subscribed` (neither opted in nor out) and `unsubscribed`, [set through the `email_subscribe` field](https://www.braze.com/docs/user_guide/audience/manage_audience/import_users/csv_import). Underneath sit [subscription groups](https://www.braze.com/docs/user_guide/message_building_by_channel/email/managing_user_subscriptions/) for categories such as newsletters or promotions. Changing a group doesn't change the global state. For SMS, users must be in an SMS subscription group to receive messages, and each user is [subscribed or unsubscribed per group](https://www.braze.com/docs/user_guide/channels/sms_mms_and_rcs/message_setup/subscription_groups). In a CSV import you set `subscription_group_id` and `subscription_state`, and only one group per row, so multi-group users need [one import per group](https://www.braze.com/docs/user_guide/audience/manage_audience/import_users/csv_import). Practical rules: - Map conservatively. If the old platform can't prove an opt-in, don't import it as `opted_in`. - Carry suppressions across as unsubscribes, not as missing records. A missing record can be re-imported later as subscribed. - Keep the consent source and date as custom attributes for audit. - Get privacy or legal sign-off on the mapping table before the first import. ## What should you know about each source platform? ### Salesforce Marketing Cloud In Marketing Cloud Engagement, a data extension is ["simply a table with fields of data about your contacts"](https://trailhead.salesforce.com/content/learn/modules/marketing-cloud-contact-management/learn-about-data-extensions). Sendable data extensions map to a subscriber, while non-sendable ones hold reference data such as orders or product tables. In Braze, sendable data usually becomes profile attributes, and reference data often fits better as [catalogs via Cloud Data Ingestion](https://www.braze.com/docs/user_guide/data/cloud_ingestion/) or as a Connected Content lookup. [Journey Builder](https://trailhead.salesforce.com/content/learn/modules/journey-builder-basics/get-started-with-journey-builder) journeys start from entry sources such as data extensions or API events, so inventory those entry sources: each becomes a Canvas entry trigger or segment. ### Klaviyo A Klaviyo flow is ["a sequence of automated actions (e.g., sending messages) triggered by a behavior or event"](https://help.klaviyo.com/hc/en-us/articles/115002774932), with triggers including lists, segments, metrics, date properties, price drops and low inventory. Metric-triggered flows map naturally to action-based Canvases. Price drop and low inventory triggers depend on product-level data, so plan how that data reaches Braze. Klaviyo also records [why a profile can't receive email marketing](https://help.klaviyo.com/hc/en-us/articles/20016490907163), such as unsubscribed, manual suppression, invalid email or hard bounce. Keep those reasons when you map to Braze. ### HubSpot HubSpot uses [subscription types](https://knowledge.hubspot.com/contacts/how-do-subscription-preferences-and-types-work) for categories of marketing email, and can require both an opted-in status and a legal basis to send. Subscription types map well to Braze email subscription groups. HubSpot [workflows](https://knowledge.hubspot.com/workflows/create-workflows) enrol records through filter, event, schedule or webhook triggers, which you'll rebuild as Canvas entry rules. ## How should you handle email domains and IP warming? Treat the email channel as new. Braze's setup starts with [delegating a sending subdomain](https://braze.com/docs/user_guide/channels/email/email_setup), after which Braze manages SPF and DKIM, and you should set [DMARC on the root domain](https://www.braze.com/docs/user_guide/channels/email/email_setup/authentication). Then warm the IPs. Braze calls warming [required](https://www.braze.com/docs/user_guide/channels/email/email_setup/ip_warming), and its conservative schedule is recommended for senders migrating from a shared IP. Start with your most engaged users and build to average daily volume. ## Should you run both platforms in parallel? Usually, yes, for a defined window. The old platform keeps carrying volume while Braze IPs warm, and you move journeys across one at a time. Rules that keep parallel running safe: - One platform owns each journey at any moment. Never let both send the same message. - Sync unsubscribes both ways during the overlap, ideally daily or faster. - Set an end date. Braze notes that [reputation data is typically kept for about 30 days](https://www.braze.com/docs/user_guide/channels/email/email_setup/ip_warming), so don't let new IPs sit idle while you wait. ## What's a sensible migration sequence? 1. Inventory: journeys, templates, data sources, consent fields, sending domains. 2. Identity and consent mapping, signed off. 3. SDK and data pipelines live, profiles and consent imported. 4. Email domain delegated and IP warming started. 5. Transactional and triggered journeys rebuilt and moved first. 6. Marketing campaigns moved as warming volume allows. 7. Old platform switched off, final suppression export kept. A typical Stitch implementation runs 8 to 12 weeks. For a migration, plan for the longer end so the inventory and parallel run have room. ## Migration risk checklist - Consent mapping documented and approved - Suppressions imported as unsubscribes - `external_id` agreed and old IDs stored as aliases - Push tokens imported with the correct app ID and environment - Web push re-permission planned - Liquid rewrites tested with missing-data fallbacks - IP warming schedule chosen and tracked - Unsubscribe sync running during parallel run - No journey live on both platforms - Contract end date for the old platform aligned with the plan ## How Stitch can help Stitch is an independent Auckland consultancy and Braze Alloys Solutions Partner (Orbit tier), named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards in 2026. We were appointed Braze onboarding partner by Skyline Enterprises in 2026, and as lead Braze partner for Serko AI we shipped a lifecycle layer to production in six weeks, including Cloud Data Ingestion from the warehouse and a dual sender architecture separating transactional and marketing email. We're also a Customer.io Gold Agency Partner, Segment Certified Partner and Hightouch Implementation Partner, so we're comfortable with the data plumbing either side of a migration. ## FAQ **Can I migrate journeys from SFMC, Klaviyo or HubSpot into Braze automatically?** No. Journeys, flows and workflows need to be rebuilt as Braze Canvases, though the logic and content can be reused. **How do I import email consent into Braze?** Set `email_subscribe` to `opted_in`, `subscribed` or `unsubscribed`, and use `subscription_group_id` and `subscription_state` for subscription groups. **Can push tokens be migrated to Braze?** Mobile tokens can be imported via the API or captured automatically when users open the updated app. Web push tokens can't be migrated through the API. **Do I need to warm new IPs when moving to Braze?** Yes. Braze calls IP warming required, and recommends a conservative schedule when migrating from a shared IP. **How long does a migration to Braze take?** Stitch's typical Braze implementation is 8 to 12 weeks. For a migration, plan for the longer end to allow for inventory and a parallel run. ## Sources - https://www.braze.com/docs/user_guide/audience/manage_audience/import_users/csv_import - https://braze.com/docs/help/help_articles/push/push_token_migration - https://www.braze.com/docs/user_guide/personalization_and_dynamic_content/liquid/ - https://www.braze.com/docs/user_guide/engagement_tools/templates_and_media/content_blocks/ - https://www.braze.com/docs/user_guide/data/user_data_collection/user_import/ - https://www.braze.com/docs/user_guide/data/cloud_ingestion/ - https://www.braze.com/docs/developer_guide/analytics/setting_user_ids/ - https://www.braze.com/docs/user_guide/data/user_data_collection/user_profile_lifecycle/ - https://www.braze.com/docs/user_guide/message_building_by_channel/email/managing_user_subscriptions/ - https://www.braze.com/docs/user_guide/channels/sms_mms_and_rcs/message_setup/subscription_groups - https://braze.com/docs/user_guide/channels/email/email_setup - https://www.braze.com/docs/user_guide/channels/email/email_setup/authentication - https://www.braze.com/docs/user_guide/channels/email/email_setup/ip_warming - https://trailhead.salesforce.com/content/learn/modules/marketing-cloud-contact-management/learn-about-data-extensions - https://trailhead.salesforce.com/content/learn/modules/journey-builder-basics/get-started-with-journey-builder - https://help.klaviyo.com/hc/en-us/articles/115002774932 - https://help.klaviyo.com/hc/en-us/articles/20016490907163 - https://knowledge.hubspot.com/contacts/how-do-subscription-preferences-and-types-work - https://knowledge.hubspot.com/workflows/create-workflows --- URL: https://stitchtech.co/braze/pricing ## In short Braze doesn't publish prices. A Braze contract is made up of a Platform Edition (Go, Select, Pro or Enterprise), a volume of Monthly Active Users and profiles, a pool of Action Credits used across channels, and CX services, priced by quote. To budget properly, size your MAUs and message volumes by channel, then add implementation, add-ons, channel pass-through costs and the team to run it. ## Key takeaways - Braze lists four Platform Editions: Braze Go, Braze Select, Braze Pro and Braze Enterprise. Prices aren't published. - Pricing scales with Monthly Active Users, and channel sends draw on a shared pool of Action Credits. - Braze says it stopped billing new customers on data points in Spring 2025, but older contracts may still use them. - The licence is only part of the cost: implementation, data work, channel fees and people time all belong in the budget. - Build the business case from your own baseline numbers, not vendor benchmarks. ## Does Braze publish its prices? No. Braze's [pricing page](https://www.braze.com/pricing) asks you to "Get pricing" or "Talk to an expert", and says to speak to your account manager or contact Braze for details. It also states that Braze doesn't offer a free plan, though a free trial is available from the same page. If you want an outside reference point, Vendr, a software purchasing platform, publishes [Braze contract data](https://www.vendr.com/marketplace/braze): a median of $88,507 a year, with a range of $20,017 to $477,107, based on 255 purchases (page last updated February 2026). Vendr doesn't state the currency or say which markets its buyers are in, so treat this as a loose signal, not a quote. Your number depends on your MAUs, channels, edition and negotiation. ## What are the Braze Platform Editions? Braze's [pricing page](https://www.braze.com/pricing) lists four editions, each building on the one before: - **Braze Go:** for early-stage growth teams activating customer data and launching cross-channel messaging, with core Braze features. - **Braze Select:** adds increased orchestration, enhanced security features and user provisioning, for companies scaling across more channels and team members. - **Braze Pro:** adds predictive AI, AI personalised recommendations, expanded dashboard user group administration and message prioritisation. - **Braze Enterprise:** adds enterprise-grade orchestration, infrastructure and governance, plus advanced experimentation with BrazeAI Agent Console. Braze says every tier includes BrazeAI (including Operator, Agent Console, generative AI and Content Optimizer), the Braze Data Platform, cross-channel messaging (email, push, SMS/MMS/RCS, WhatsApp, in-app and more), journey orchestration through Campaigns and Canvases, and security features such as SAML SSO and granular permissions. ## How does the Braze pricing model work? According to Braze, [your contract is made up of](https://www.braze.com/pricing): - **A Platform Edition** suited to your business - **Monthly Active Users and Profiles:** pricing scales with MAUs, meaning users who actively interact with your brand, and each MAU comes with "a large allotment of User Profiles" - **Action Credits:** a single, flexible pool of credits used across channels and some BrazeAI products - **CX Services:** support and service plans Braze's own example of Action Credits is that an SMS may cost 1 credit and a WhatsApp message may cost 5. The exact credit rates for your channels and markets are something to confirm in your quote. ### What about data points? Older Braze contracts were often built around data points, a billable unit logged whenever a profile is updated. Braze's [data points documentation](https://www.braze.com/docs/user_guide/data/infrastructure/data_points) says that "as of Spring 2025, Braze no longer bills new customers based on data points", and that the count is informational only if your contract isn't on data point billing. If you signed a multi-year deal before then, check which model you're on: it changes how you design your data integration. ## What drives Braze costs up or down? **1. Monthly Active Users.** This is the main lever. Work out how many people you'll actually engage each month, not your total database. A large dormant list you rarely message is a different conversation from a highly active app audience. **2. Channel mix and volume.** Email, push, SMS and WhatsApp draw on Action Credits at different rates. Model sends per channel per month, including transactional messages such as confirmations and reminders, which add up quickly. **3. Channel pass-through costs.** Some channels carry costs set by third parties. Meta, for example, has charged [per message for the WhatsApp Business Platform since 1 July 2025](https://developers.facebook.com/docs/whatsapp/pricing/), with rates that vary by template category (marketing, utility, authentication) and the recipient's country, and Meta may update pricing on the first day of each quarter. Ask Braze how carrier and Meta fees are handled in your contract and whether they sit inside Action Credits or are billed separately. **4. Edition.** Features like predictive AI, recommendations and message prioritisation sit in higher editions. Be honest about what you'll use in year one. **5. Add-ons.** Braze mentions [a variety of add-on SKUs](https://www.braze.com/pricing) across the Braze Data Platform and BrazeAI. Data export is one to check: Braze says a Currents connector is [included in many pro and enterprise-level packages](https://www.braze.com/docs/user_guide/data/braze_currents/), and Snowflake Data Sharing depends on your [Data Distribution entitlement](https://www.braze.com/docs/partners/data_and_analytics/data_warehouses/snowflake/data_sharing). **6. Contract length and growth.** Multi-year terms and MAU growth assumptions affect pricing. Agree in advance what happens if you exceed your MAU or credit allowance. ## What costs sit outside the Braze licence? The licence is the line item everyone looks at, but it's rarely the whole picture: - **Implementation:** SDK integration, data modelling, channel set-up (sending domains, SMS numbers, WhatsApp Business accounts), migration of existing journeys and QA. Stitch's typical Braze implementation takes 8 to 12 weeks. - **Data and engineering:** building and maintaining the feeds into Braze, whether via SDK, API or Cloud Data Ingestion. Zero-copy features such as CDI Segments [run queries in your warehouse](https://www.braze.com/docs/user_guide/example_library/data/compare_data_ingestion_options), so they add warehouse compute cost. - **People:** someone has to plan, build, test and report on campaigns. A platform nobody has time to use is the most expensive option of all. - **Creative and content:** templates, imagery and copy for every lifecycle stage and channel. - **Ongoing optimisation:** testing, deliverability management and reporting. ## How do you build a business case for Braze? Start from your own numbers. A credible case usually covers: **1. Baseline.** Current spend on your existing engagement tools, SMS and email providers, and agency or contractor time. Current performance: conversion, retention, repeat purchase, app engagement, whatever matters most. **2. Use cases.** List the specific journeys you'll launch in year one, such as onboarding, abandoned browse or cart, transactional messaging, win-back and loyalty. Tie each one to a metric. **3. Conservative uplift.** Estimate the improvement for each use case using your own test results or modest assumptions. Show a low, mid and high case. **4. Total cost of ownership.** Licence, Action Credits, channel pass-through costs, add-ons, implementation, internal headcount and partner support over the contract term. **5. Consolidation savings.** Tools you can retire, manual processes you can automate and duplicated data pipelines you can remove. **6. Risk and governance.** Data residency (Braze offers an [Australian data centre, AU-01](https://www.braze.com/docs/user_guide/data/infrastructure/data_centers/)), security features, and the cost of not acting. **7. Payback period.** When cumulative benefit passes cumulative cost. Finance teams care more about this than headline ROI. ## What should you ask Braze before signing? - How are MAUs defined and counted for our use case, including anonymous web users? - How many Action Credits are included, what does each channel consume in our markets, and what happens if we run over? - Are SMS carrier and WhatsApp (Meta) fees included in credits or billed separately? - Which add-ons do we need for data export to our warehouse? - Are we on data point billing, and if so, how much headroom do we have? - What support and service plan is included? - What are the price protections at renewal? ## How Stitch can help Stitch is an independent Auckland consultancy and a Braze Alloys Solutions Partner (Orbit tier), named ANZ Rising Star of the Year at Braze's inaugural ANZ Partner Awards in 2026. Skyline Enterprises appointed us as its Braze onboarding partner in 2026. We help ANZ brands size MAUs and message volumes, map use cases to editions, and build the implementation plan and business case before contracts are signed. Then we do the build: for Serko AI, the lifecycle layer shipped to production in six weeks from kick-off. If you're budgeting for Braze, get in touch. ## FAQ **How much does Braze cost?** Braze doesn't publish prices; pricing is by quote. Your cost depends on Platform Edition, Monthly Active Users, Action Credits for channel sends, add-ons and services. **Does Braze charge per MAU?** Braze says pricing scales with Monthly Active Users, with each MAU including an allotment of user profiles. Channel sends draw on a separate pool of Action Credits. **Does Braze still charge for data points?** Braze says it stopped billing new customers on data points in Spring 2025. Some older, multi-year contracts may still be based on data points. **Does Braze have a free plan?** No. Braze says it doesn't offer a free plan, but a free trial is available from its pricing page. **What are Braze Action Credits?** A single pool of credits used across channels and some BrazeAI products. Braze's example is that an SMS may cost 1 credit and a WhatsApp message may cost 5. ## Sources - https://www.braze.com/pricing - https://www.braze.com/docs/user_guide/data/infrastructure/data_points - https://www.braze.com/docs/user_guide/data/braze_currents/ - https://www.braze.com/docs/partners/data_and_analytics/data_warehouses/snowflake/data_sharing - https://www.braze.com/docs/user_guide/example_library/data/compare_data_ingestion_options - https://www.braze.com/docs/user_guide/data/infrastructure/data_centers/ - https://developers.facebook.com/docs/whatsapp/pricing/ - https://www.vendr.com/marketplace/braze --- === Insights === URL: https://stitchtech.co/insights/braze-anz-rising-star-2026 News # Stitch named Braze ANZ Rising Star of the Year 2026 Published 25 August 2026 · Last updated 4 October 2026 ## Key takeaways - Stitch was named ANZ Rising Star of the Year at the inaugural Braze ANZ Partner Awards. - The award was presented at Braze Partner Day Sydney on 17 August 2026. - It recognises the partner that has most rapidly grown its impact within the Braze Alloys Partner Network across Australia and New Zealand. - In the past year Stitch delivered Braze programmes for companies including Serko, and was appointed Braze onboarding partner by Skyline Enterprises. Stitch has been named ANZ Rising Star of the Year at the inaugural Braze ANZ Partner Awards, accepted by Co-Founder and Managing Partner Adnan Khan and Head of Marketing and AI Automation Vikas Varma at Braze Partner Day Sydney on 17 August 2026, in front of more than 100 leaders from across the Braze ANZ partner ecosystem. The award recognises the partner that has most rapidly grown its impact within the Braze Alloys Partner Network across Australia and New Zealand. Braze's judging panel highlighted Stitch's evolution from a new partner into one of the most impactful and trusted delivery partners in the ANZ ecosystem. "Two years ago we were a new Braze partner that most of the ANZ ecosystem hadn't heard of, so Rising Star is an award we're proud to accept on behalf of our whole team in Auckland," said Adnan Khan, Co-Founder and Managing Partner at Stitch. "This recognition belongs to our team and to our clients, who trusted us to take on their complex enterprise data and customer engagement needs. Stitch is an independent consultancy with big ambitions, and we think the best of what we can build with Braze is still ahead of us." "This award is thoroughly well deserved," said Chris Johnston, Senior Director, Commercial Partnerships, APJ at Braze. "The way the Stitch team works with our teams on opportunities - the responsiveness, transparency and depth of information - is first-class. It is honestly the best I have seen in my time in this role, and we look forward to continuing to grow our partnership across New Zealand and Australia." In the past year Stitch has delivered Braze programmes for New Zealand companies including agentic travel technology platform Serko (NZX/ASX: SKO), and was recently appointed by Skyline Enterprises as their Braze onboarding partner. "Stitch worked alongside the Serko team to build the backbone of our Braze programme, from beta through to commercial launch for our new agentic product, Serko.ai. They move fast, and when we hit constraints, they came back with options to keep us moving forward. As we push into an agentic, real-time model of customer engagement, Stitch is a key partner we trust to build alongside us, not just for us," said Kathryn Hoolihan, Director of Growth Marketing at Serko. "Stitch stand out as an agile and responsive partner with a track record of supporting clients to maximise their Braze investment at speed," says Ella Spittle, Group Customer Experience Manager at Skyline Enterprises. "They've quickly become an invaluable extension of our team, helping us to achieve value from Braze within just weeks while designing the right foundations for our longer-term customer engagement ambitions." ## Coverage - Stitch named Braze ANZ Rising Star of the Year 2026 StopPress - Stitch makes its mark at Braze M+AD Daily As reported by StopPress . ## Related services - Marketing automation - Agentic AI --- URL: https://stitchtech.co/insights/agentic-ai-for-marketing Insights · Guide # Agentic AI for marketing: what it actually is, and what to do about it. A field guide for CMOs, growth leaders and the next generation of marketers. Adapted from Adnan Khan's May 2026 guest lecture to the University of Auckland MCom Marketing cohort. Published 15 May 2026 · Last updated 10 October 2026 ## Key takeaways - An AI agent perceives, plans, acts, observes and loops on its own. Autonomy is the unlock. - MCP is a universal standard that lets any agent connect to any tool. - Adoption is not value: 79% of enterprises claim AI agent adoption, but only 11% run agents in live environments. - AI is taking marketing tasks, not whole jobs. - This quarter, build one real agent and own GEO for your vertical. ## What is agentic AI for marketing? Agentic AI for marketing is AI that runs marketing workflows itself, across tools and time. Generative AI produces output when prompted, and a copilot suggests next moves alongside a human. An AI agent perceives, plans, acts, observes and loops on its own. Autonomy is the defining trait, and it changes the cost of marketing operations. If your mental model of AI in marketing is still ChatGPT writes a blog post , you are roughly three years behind the live frontier. Agentic AI is the next layer of the stack, and it has already moved out of slideware and into production at brands you compete with. This guide gives you a clearer mental model, an honest take on jobs, and one concrete action. Stitch leads the IAB New Zealand AI Working Group on agentic systems, convenes the Marketing Association's AI, Digital, Social, Data & Privacy Thought Leader Groups, and ships agentic AI for clients including Serko, Skills Group and Bayleys. The frames below are the ones we use with our own clients. ## Three categories that matter There are three useful buckets. Generative AI produces output when prompted - ChatGPT's web interface is the canonical example. An AI assistant or copilot sits next to a human and suggests next moves - Claude CoWork, GitHub Copilot. An AI agent perceives, plans, acts, observes and loops on its own. Autonomy is the unlock. Once an agent can take real actions in real systems without a human in every loop, the cost curve of marketing operations bends. ## Case in point - Coca-Cola + Soma Coca-Cola handed an entire Saudi Arabia campaign to an AI agent called Soma, built by Toronto's Cluep. The agent identified audiences by scanning public posts on TikTok, Meta, Pinterest and Reddit and matching them to mobile IDs via ad exchanges. Generative AI built the creative on the fly - burger fans saw Coke + burger creative, spicy-food fans saw "refreshing relief" creative. The agent then ran 24/7 for two months through Coke's existing Burger King and AMC partnerships. The result: ~8 million autonomous actions, 828,000 personalised coupon ads, 20,000+ click-throughs - and zero marketing team members in the loop. The agent ran the campaign while Coke's marketers slept. ## The infrastructure - MCP is the USB-C moment In November 2024 Anthropic released Model Context Protocol - a universal standard that lets any agent connect to any tool. By March 2026 the ecosystem hit ~97M monthly SDK downloads, 5,800+ community MCP servers and 16,000+ public servers. Salesforce, HubSpot, Adobe, Snowflake, Webflow, Meta and Google all ship MCP servers. An agent inside ChatGPT can now spin up an Amazon ad campaign in a single prompt. The plumbing is standard - your stack does not need to be bespoke. In May 2026 Robinhood shipped Agentic Trading. Paste one MCP URL into your agent config, fund a ringfenced "agentic account", and your AI agent can place real stock trades on a real brokerage account, 24/7, for $0. The MCP era is not a B2B abstraction anymore. It is in retail finance, today. ## Reality check - adoption is not value 79% of enterprises claim AI agent adoption. Only 11% are actually running agents in live environments. 34% of marketing teams report running at least one autonomous agent - more than double Q4 2024. We are roughly where e-commerce was in 1999: the winners are obvious in retrospect, but most companies are still arguing about whether to ship. Nearly 8 in 10 organisations report no significant bottom-line gains from AI generally (McKinsey, 2026). Adoption is not the same as value. Operating model, data foundation and measurement decide who actually captures the upside. ## Content - velocity is no longer the moat One Forrester-cited content programme lost 70% of its organic traffic in 9 months (from 24M to 6-7M visits) while growing revenue 22% YoY. Traffic and outcomes have decoupled. Content velocity is a commodity. What scales now is original data, taste and citation share inside the LLMs. End-to-end content agents - Writer.com (Vanguard, L'Oreal, Mars; Forrester-validated 333% three-year ROI), Jasper (100+ marketing agents, used by Spark NZ's marketing team), Adobe's Content Production Agent in beta - are the new baseline, not the cutting edge. ## SEO becomes GEO Google AI Overviews now appear on 48% of all queries (February 2026), reaching 2 billion monthly users. An ISB + Carnegie Mellon randomised field experiment found AI Overviews cut organic clicks by 38%. 72% of searches now end with no click. Only ~6.82% of ChatGPT-cited results overlap with Google's top 10. What ranks on Google is largely not what gets cited by ChatGPT, Perplexity or Gemini. Generative Engine Optimisation (GEO / AEO) is a new discipline, not a tag on the old one. If 72% of searches end with no click, your brand-building playbook for 2030 has to be built for AI answer surfaces - not the blue links. ## Social - AI eats every layer TikTok Symphony (URL-to-video, digital avatars, image-to-video) is delivering documented results: Meoky reported 1.8x purchases and +13% ROAS; YOOX reported -15% cost-per-add-to-cart. 76% of TikTok advertisers plan to increase use of AI creative tools. AI influencers earn real money. Aitana Lopez, a fully synthetic Barcelona-based persona, has ~370K Instagram followers and earns $6,000-$20,000/month. Brands signed her before realising she was not real - and proceeded anyway. ## The CMO is being unbundled 49% of Fortune 500 marketing leaders still hold the "CMO" title - down from 55% in 2024. One in three F500 companies now has no enterprise marketing leader at all. Just 15% of CEOs believe their CMO is AI-savvy. Gartner projects "lack of AI literacy" will rank in the top three reasons CMOs are replaced by 2027. The CMO of 2030 is more likely called a Chief Growth Officer - owning P&L, supervising agentic squads, with CFO-grade financial fluency and an explicit AI ethics remit. ## The job market is already pricing this in The PwC 2026 AI Jobs Barometer puts the global AI wage premium at +56%, up from 25% a year earlier. The Anthropic Economic Index (February 2026) found API workflows for business sales and outreach roughly doubled between November 2025 and February 2026. The simplest split: at risk - junior copywriting, manual reporting, template-driven creative; enhanced - brand strategy, customer research, narrative, taste; emerging - AI Marketing Manager (US median ~$136K), Agent Orchestration Lead, GEO Lead, Marketing Data Engineer. ## Agentic AI is already live across Aotearoa Stitch ships agentic AI in production for New Zealand brands today. Bayleys Real Estate use agentic AI for lead qualification and listing enrichment. Skills Group runs a production chat assistant across four divisions on Zapier with a RAG layer trained on client content (live since April 2026). Stitch is the lead Braze partner on Serko AI, the agentic travel assistant whose US beta launched on 9 May 2026. Spark New Zealand runs modular, purpose-built agents that audit international roaming fees, fetch usage logs, cross-reference travel data and assemble resolutions for service reps in seconds. ## The thing that surprised even me A December 2025 INSEAD study found AI-generated ads won against human-made ads 59.1% of the time - and AI ads tested at a 21-point premium on certain creative quality measures while landing 29.4% cheaper to produce. The point is not that AI is taking marketing jobs. The point is that AI is taking marketing tasks . Your job is to make sure the value you create is on the task list AI is bad at. ## Where this goes by 2030 By end-2026, Gartner projects 40% of enterprise applications will include task-specific AI agents (up from under 5% in 2025). By 2028-2030, McKinsey expects agentic AI to power up to two-thirds of marketing activities, accelerate campaign creation 10-15x and drive 10-30% revenue growth for organisations that operationalise it. A 24-year-old marketer today can do work that took a team of 20 in 2015. The real question is whether you compress 10 years of career growth into 2 - and whether your CV in 2030 reads "I used AI" or "I orchestrated agents" . ## What to do this quarter - Build one real agent. Pick one platform - Make, n8n, Viktor, Gumloop, Lindy, Zapier Agents - and ship a working end-to-end agent against a real workflow. This alone puts you in the top decile. - Pick a vertical and own GEO for it. Track citation share inside ChatGPT, Perplexity and Google AI Overviews, not just blue-link rankings. - Practise the human-only skills harder. Active listening, reading comprehension, customer empathy, narrative, judgement and taste are more valuable, not less. - Audit your marketing operating model. Map every workflow against the agentic stack and decide what humans should orchestrate vs. perform. - Pick the right partner. Most agencies are still doing slideware. Pick one shipping production agents you can reference. ## FAQ ### What is agentic AI, in plain English? An AI agent perceives, plans, acts, observes and loops - autonomously. That is the unlock. Generative AI produces output when prompted. A copilot suggests next moves alongside a human. An agent runs the workflow itself across tools and time, with autonomy as the defining trait. ### What is MCP and why does it matter for marketers? Model Context Protocol, released by Anthropic in November 2024, is effectively USB-C for AI agents. It is a universal standard for connecting any agent to any tool. By March 2026 the ecosystem hit ~97M monthly SDK downloads, 5,800+ community servers and 16,000+ public servers. Salesforce, HubSpot, Adobe, Snowflake, Webflow, Meta and Google all ship MCP servers, so an agent in ChatGPT can spin up an Amazon ad campaign in a single prompt. The plumbing is now standard. ### Are real brands actually running agentic campaigns? Yes. Coca-Cola handed an entire Saudi Arabia campaign to an AI agent called Soma. Over two months it took ~8 million autonomous actions, delivered 828,000 personalised coupon ads and 20,000+ click-throughs, with zero marketing team members in the loop. Robinhood shipped Agentic Trading in May 2026, letting an AI agent place real stock trades on a real brokerage account via MCP. This is no longer slideware. ### Which marketing roles are most at risk? Tasks, not titles, are being automated first. Junior copywriting, routine campaign ops, manual reporting and template-driven creative are the most exposed. Roles centred on judgement, taste, narrative, customer empathy and orchestration of agentic squads are becoming more valuable. The CMO title is also being unbundled - 49% of Fortune 500 marketing leaders still hold the CMO title (down from 55% in 2024) and one in three F500 companies has no enterprise marketing leader at all. ### What should I do this quarter? Pick one agent platform - Make, n8n, Viktor, Gumloop, Lindy, Zapier Agents - and build one real working agent end to end. Document it. Then pick a vertical and own GEO (generative engine optimisation) for it: AI Overviews already appear on 48% of Google queries and cut organic clicks by ~38%, and only ~6.82% of ChatGPT-cited results overlap with Google's top 10. Citation share inside the LLMs is the new ranking. ## Related services - Agentic AI - Marketing automation ## Keep exploring - Segment vs Tealium comparison - Agentic AI service - Serko AI case study - Skills Group case study - About Stitch --- URL: https://stitchtech.co/insights/segment-vs-tealium Insights · Comparison # Segment vs Tealium: a consultant's comparison. Both are excellent customer data platforms. They are not the same product, and the choice between them is rarely about features. This is the comparison we walk clients through - from a consultancy that has shipped both in production. Published 3 June 2026 · Last updated 10 October 2026 ## Key takeaways - Choose on architecture and operating model, not on features. - Tealium fits multi-brand or regulated enterprises that need strong consent enforcement and tag governance. - Segment fits warehouse-native teams that want Reverse ETL and a fast collection layer. - Both are quote-based. Include the implementation partner cost when you compare them. - Stitch has shipped both: Tealium for Tourism New Zealand, and Segment for World Vision and Turners Cars. We get asked "Segment or Tealium?" at least twice a month. The honest answer is: it depends on your operating model, your data architecture, your consent posture and who is going to run it after we leave. Most published comparisons are written by one of the vendors or by an aggregator pricing for affiliate clicks. This one is written by a consultancy that has implemented both at scale and has no incentive to push one over the other. Stitch is the lead Tealium partner in New Zealand and a certified Segment partner. We delivered Tealium for Tourism New Zealand (8M+ profiled IDs across markets), and Segment for World Vision and Turners Cars (6.3x lead growth on a Segment + Snowflake + Customer.io stack). The frames below are what we use in real selection workshops. ## TL;DR - choose on architecture, not features Pick Tealium if you are a multi-brand or regulated enterprise that needs strong consent enforcement, server-side tag governance, and a profile store managed inside the CDP. AudienceStream is a strength here, and the Consent Manager is mature. Pick Segment if you are warehouse-native, your data team lives in Snowflake / BigQuery / Databricks and dbt, and you want Reverse ETL, Linked Audiences and a fast collection layer that ships to a deep destination catalog with minimal engineering. Twilio Engage is the activation upside. Both can do almost everything the other can do. The question is which one your team will actually operate well three years in. ## Segment vs Tealium at a glance ## Implementation model - utag vs analytics.js Tealium implementations are anchored on utag , a tag management layer that runs client-side and server-side (EventStream). You centralise tag governance, consent logic and vendor pixels behind a single UI. The upside is control: marketing teams can ship and govern tags without engineering for every change. The downside is heavier up-front setup - data layer design, utag.js publishing, EventStream pipelines and AudienceStream visitor stitching all have to be modelled deliberately. Segment implementations centre on analytics.js (web), the mobile SDKs and server libraries, all speaking a simple Track / Identify / Group / Page spec. Engineering ships events in hours rather than days, and the destination catalog (400+ integrations) does the heavy lifting. The trade-off is governance: without a tracking plan and Protocols, Segment implementations sprawl quickly. Rule of thumb: if marketing operations owns the stack, Tealium is closer to your operating model. If product engineering owns the stack, Segment is. ## Identity resolution Tealium AudienceStream uses configurable visitor stitching rules - you define which attributes count as identifiers (email, hashed email, CRM ID, MAID, anonymous ID), how they merge, and what wins on conflict. The resulting visitor profile lives inside Tealium and is queryable via DataAccess. This is the right model when consent and PII handling sit with the marketing operations team and need to be auditable inside one tool. Segment Unify / Profiles does deterministic identity resolution with merge-protection (so two distinct users do not accidentally get stitched into one) and exposes the unified profile to the warehouse natively. Linked Audiences then lets your data team build audiences directly from warehouse tables and ship them to destinations. This is the right model when your data team owns identity inside the warehouse and treats the CDP as a collection-and-activation layer. Both support consent-aware identity. Tealium's Consent Manager is the more mature surface here; Segment relies on integrations with OneTrust, Sourcepoint or your own consent service. ## Warehouse activation (Reverse ETL) This is where the two platforms have moved fastest, and where the choice is most consequential. Segment treats the warehouse as a first-class source. Reverse ETL ships pre-built - point Segment at a Snowflake / BigQuery / Redshift / Databricks model, define a sync, and your warehouse audiences flow to any destination in the catalog. Linked Audiences and Twilio Engage build on top of that, letting marketers compose audiences from warehouse entities (orders, subscriptions, lifetime value) without writing SQL each time. For warehouse-native teams this collapses the stack - you no longer need a separate Hightouch or Census license for the basics. Tealium reaches the warehouse through DataAccess (export profiles and events to Snowflake or S3) and through integrations. Activation back from the warehouse is supported, but the canonical Tealium workflow still runs through AudienceStream and EventStream, not the warehouse. If your audience logic lives in dbt models, Tealium will feel like a longer path. If it lives in AudienceStream, the warehouse round-trip is rarely needed. ## Governance, consent and privacy Tealium has a structural advantage on tag-level consent. The Consent Manager + iQ Tag Management combination enforces consent at the vendor-fire level - if a user opts out of analytics, the analytics tag does not fire, full stop. For brands operating under GDPR, the Australian Privacy Act 2024 amendments or sector-specific regimes (health, finance), this is materially easier to defend in audit. Segment Privacy Portal and Protocols handle this differently - consent is enforced at the destination layer and through filtering on the event stream. With a disciplined tracking plan it is robust, but the enforcement point is further down the pipe. For pure product analytics use cases this is fine; for heavy marketing-tag estates, Tealium is the safer default. ## Pricing posture Both vendors are quote-based and price on MTUs (monthly tracked users), event volume, modules (AudienceStream / Engage / Linked Audiences) and seats. Indicative ranges we see in the New Zealand and Australia market: Segment : mid-market deployments commonly land $40K - $120K USD/year for Connections + Unify. Twilio Engage and Linked Audiences add meaningfully - full-suite enterprise deployments routinely cross $250K - $750K USD/year. Self-serve free / team tiers exist but stop being viable once you need Protocols or Reverse ETL at scale. Tealium : mid-market deployments land $50K - $150K USD/year for iQ + EventStream + AudienceStream. Enterprise multi-brand deployments with full DataAccess and Predict run $300K - $900K USD/year. Tealium tends to be slightly higher at the entry point and flatter at the top - heavy enterprises often pay less for Tealium than for full-stack Segment. Always include the implementation partner cost in the comparison. A poorly-implemented Tealium is more expensive than a well-implemented Segment, and vice versa. ## Real-world context - Tourism New Zealand (Tealium) Stitch built the Tealium implementation underpinning Tourism New Zealand's international demand programme - 8M+ profiled visitor IDs across markets, multi-language consent, AudienceStream visitor stitching tied to first-party CRM signals, and activation into Meta, Google and DV360. The Consent Manager was non-negotiable: TNZ operates in jurisdictions with very different privacy regimes (EU, US, India, China) and Tealium let us enforce that at the tag layer in one place. This is a case where Segment would have required a heavier custom consent layer and additional engineering. Tealium was the right call. ## Real-world context - World Vision and Turners (Segment) For World Vision we deployed Segment as the collection layer feeding a Snowflake warehouse, with Customer.io as the messaging tool. The use case - donor journeys built from warehouse-modelled audience definitions - was a textbook fit for Segment's warehouse-native posture. For Turners Cars the Segment + Snowflake + Customer.io stack is what carried the closed-loop attribution work that drove 6.3x lead volume and a 68% reduction in cost per lead. The Reverse-ETL motion from Snowflake back into Customer.io and the paid-media platforms was the unlock. Tealium could have done the collection layer; Segment made the warehouse round-trip materially shorter for an in-house team that did not want to run AudienceStream. ## How we run the selection A typical Stitch CDP selection runs four to six weeks: requirements workshop, data architecture review, vendor demos against your real data, scored evaluation across implementation effort, identity model, activation, governance, and total cost of ownership, then a written recommendation with a roll-out plan. We are paid the same regardless of which platform wins - and roughly half the time it is Tealium, half the time Segment, with a handful of Hightouch + warehouse-only outcomes for teams that do not need a CDP at all. ## Decision shortcuts - Multi-brand or regulated, heavy marketing tag estate, marketing ops owns governance Tealium. - Product-led, warehouse-native, data team owns activation in Snowflake or BigQuery Segment. - You already run a strong Reverse ETL tool (Hightouch, Census) and want a lean collection layer Segment, lean SKU. - You operate across jurisdictions with very different consent regimes Tealium. - You want a CDP that doubles as your messaging tool out of the box Segment + Twilio Engage. - Your team can credibly run only one platform end-to-end pick the one that matches who you already hire. ## FAQ ### Segment vs Tealium - which CDP is better? Neither is universally better. Tealium wins for enterprises that need granular consent, tag governance and a server-side EventStream with a long track record in regulated markets. Segment wins for product-led, warehouse-native teams that want a fast collection layer, a deep catalog of destinations and tight Reverse ETL via Twilio Engage and Linked Audiences. Pick on operating model and data architecture, not on feature checklists. ### How do Segment and Tealium differ on identity resolution? Tealium AudienceStream uses a deterministic visitor stitching model with configurable identity rules and a strong consent-aware profile. Segment Unify (built on top of the Profiles API) does deterministic identity resolution with a merge-protection model, exposed natively to the warehouse. In practice: Tealium gives you more control inside the CDP UI; Segment gives you more control inside your warehouse. ### Does Segment or Tealium do Reverse ETL better? Segment via Twilio Engage and Linked Audiences treats the warehouse as a first-class source - you can model audiences in Snowflake or BigQuery and activate them to downstream channels without a separate Reverse ETL tool. Tealium added warehouse activation through DataAccess and partnerships, but the workflow is less warehouse-native. If your team lives in dbt and Snowflake, Segment is the shorter path. If your team lives in a tag manager and consent UI, Tealium is. ### How much does each cost? Both are quote-based and scale on monthly tracked users (MTUs) plus events and seats. Indicative ranges we see in market: mid-market Segment deployments land $40K - $120K USD/year; mid-market Tealium deployments land $50K - $150K USD/year. Enterprise deployments of either run six to seven figures once Engage, AudienceStream, or Linked Audiences are layered in. The right question is total cost of ownership, including the implementation partner. ### Which is easier to implement? Segment's JavaScript and mobile SDKs are easier to ship for product engineering teams - the spec is simple, the catalog of destinations is large, and warehouse loading is one-click. Tealium's implementation is heavier up front (utag, EventStream, AudienceStream, Consent) but pays back when you need centralised tag governance and consent enforcement across a large brand portfolio. ### Has Stitch implemented both? Yes. Stitch is the lead Tealium partner in New Zealand and has deployed Tealium for Tourism New Zealand (8M+ profiled IDs, multi-market activation). We have also delivered Segment for World Vision and Turners Cars, where the Segment + Snowflake + Customer.io pattern underpinned 6.3x lead growth at Turners. We are certified on both platforms and pick the right tool per client rather than per panel. ## Related services - CDP implementation - Data engineering ## Keep exploring - Agentic AI for Marketing guide - CDP implementation service - Stitch × Tealium - Stitch × Segment - Tourism New Zealand case study - World Vision case study - Turners Cars case study ---