Unified Shopify, ad platforms, email and GA4 in your warehouse — with clean dbt models for blended CAC, LTV, contribution margin, and channel attribution. Delivered in 3–4 weeks. Not a proof of concept. A production-grade data layer your team owns.
Meta reports one ROAS. GA4 reports another. Shopify reports something else entirely. Your CMO picks whichever number looks best for the board deck — which means nobody actually knows what’s working.
The problem is not the platforms. It is the absence of a single data layer that ingests all of them, applies consistent definitions, and surfaces one set of numbers everyone agrees on. Until that layer exists, every marketing decision is made on contested data.
Marketing Data Foundations builds that layer. In 3–4 weeks, your Shopify, Meta, Google Ads, TikTok, Klaviyo and GA4 data lives in one warehouse, modelled correctly, ready for every downstream dashboard and decision.
Meta, GA4, and Shopify all report different revenue. Marketing Data Foundations reconciles every source into a single blended CAC and ROAS figure — the one that goes in the board deck, not the three that contradict each other.
Last-click attribution punishes the channels that assist. We model first-touch, last-touch, and linear attribution in parallel — so your CMO can choose a model and defend it, rather than defaulting to whichever platform claims the most credit.
90-day and 180-day LTV by acquisition channel, cohort, and product line — so you know which channel is acquiring customers worth keeping, not just customers worth acquiring.
ROAS ignores fulfilment, returns, and cost of goods. Contribution margin views built on your actual P&L data show which channels and products are profitable, not just which drive revenue.
Instead of weekly requests to the data team, your marketers get pre-built dashboards updated on your warehouse schedule. CAC by channel, spend vs. revenue by week, cohort retention — in the BI tool they already use.
Every model is built in dbt with full documentation, tests, and CI. When you hire your next analyst, they inherit a codebase they can understand and extend — not a maze of legacy SQL no one remembers writing.
Meta, GA4 and Shopify report different revenue figures
Your CMO cannot defend a single blended CAC number
You don't know which channels are driving profitable customers
Your marketing team waits on the data team for weekly reports
LTV is either missing or calculated differently by everyone
You're scaling ad spend but can't confidently attribute what's working
A 30-minute conversation to understand your current stack, which platforms you’re running, and what a single source of truth would unlock for your marketing team.