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Quickstart stack

A composable CDP stack: warehouse first, activation on top

The warehouse holds the customer record, and reverse ETL sends audiences out to the channels. There is no packaged CDP in the middle: the jobs a CDP does are split across tools your data team already runs.

Open this stack in Stack Builder → No sign-up. It opens on the canvas, ready to change.

10 tools · 11 connections

OneTrust to Twilio Segment: Consent signalGTM Server-side to Twilio Segment: Server eventsTwilio Segment to Snowflake: Event streamTwilio Segment to Google Analytics 4: Analytics forwardSnowflake to dbt: Raw tablesdbt to Snowflake: Modelled tablesSnowflake to Hightouch: Audience modelsHightouch to Braze: Profile syncHightouch to Google Ads: Customer MatchHightouch to Meta Ads: CAPI audiencesBraze to Twilio Segment: Engagement events OneTrust Consent Management dbt Data Modeling GTM Server-side Server-side Tagging Twilio Segment Event Router Snowflake Data Warehouse Hightouch Reverse ETL Google Ads Advertising Meta Ads Advertising Google Analytics 4 Analytics & BI Braze Customer Engagement
Scroll sideways to see the whole stack. Arrows show the direction data moves. Every connection is listed by name below.

What it is for

Teams whose customer data already lives in a cloud warehouse, with a data team that models it in SQL, usually reach for this shape. Marketing gets audiences built from the same tables finance and product report from, instead of a second copy of the customer inside a separate platform.

It is drawn as a stack in transition. Twilio Segment still collects and routes events while Snowflake becomes the source of truth, so Segment and Hightouch both sit in the picture. That is how most composable stacks look in their first year, and the Stack Audit flags the pair as overlapping, which is the conversation to have before renewal.

Why each tool is here

  • OneTrust Consent Management

    Consent management. It records what each visitor agreed to and passes that state on, so the tools downstream only collect and use what they are allowed to.

  • GTM Server-side Server-side Tagging

    Server-side tagging. Events are collected on a server you control, not in the browser, which is less exposed to ad blockers and keeps vendor scripts off the page.

  • Twilio Segment Event Router

    Event collection and routing. It takes the server events and forwards them to the warehouse and to GA4.

  • Google Analytics 4 Analytics & BI

    Web analytics. Fed from the router, so reporting reads the same events the warehouse does.

  • dbt Data Modeling

    Data modeling. It turns raw event tables into customer and audience models, in SQL, with tests and version control.

  • Snowflake Data Warehouse

    The warehouse, and the customer record. Raw events land here and the modeled tables are what everything downstream reads.

  • Hightouch Reverse ETL

    Reverse ETL. It reads audience models from Snowflake and syncs them to the channels on a schedule.

  • Braze Customer Engagement

    Customer engagement: email, push and in-app messages, driven by profiles Hightouch keeps in sync.

  • Google Ads Advertising

    Paid search. Receives Customer Match audiences from the warehouse.

  • Meta Ads Advertising

    Paid social. Receives audiences for targeting and suppression.

How data flows

Events start at the server-side container and go to Segment, which streams them into Snowflake and forwards a copy to GA4. OneTrust sends the consent signal to Segment, so routing can respect it.

Every hour dbt reads the raw tables and writes modeled ones back. Hightouch reads the audience models from those tables and syncs them to Braze hourly and to the ad platforms daily. Braze sends engagement events back through Segment, which closes the loop: what a customer opened or clicked is in the warehouse by the next model run.

Every connection

  1. OneTrust to Twilio Segment Consent signal · Real time, on each event
  2. GTM Server-side to Twilio Segment Server events · Streaming, continuously
  3. Twilio Segment to Snowflake Event stream · Streaming, continuously
  4. Twilio Segment to Google Analytics 4 Analytics forward · Streaming, on each event
  5. Snowflake to dbt Raw tables · Batch, hourly
  6. dbt to Snowflake Modelled tables · Batch, hourly
  7. Snowflake to Hightouch Audience models · Batch, hourly
  8. Hightouch to Braze Profile sync · Batch, hourly
  9. Hightouch to Google Ads Customer Match · Batch, daily
  10. Hightouch to Meta Ads CAPI audiences · Batch, daily
  11. Braze to Twilio Segment Engagement events · Streaming, on each event

When this is the wrong choice

  • You have no one to own the warehouse models. In this shape dbt is where segments are defined; without an analytics engineer it stalls.
  • You need a decision in the moment, during a session. Hourly syncs are fine for lifecycle and paid media, not for on-site personalization.
  • Your customer data does not live in a warehouse yet. Start with the Packaged CDP or the Analytics & BI quickstart instead.

Try this: Open it and run the Stack Audit: it should flag Segment and Hightouch as overlapping.

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