How to Build a Single Source of Truth for DTC Marketing Data
Short answer
A single source of truth starts with your order and customer data (Shopify or equivalent) as the foundation, then layers clean marketing cost and performance data on top, with consistent definitions for revenue, new customers, and channels.
Core building blocks
- Order truth layer — Shopify / orders + refunds + customer ID.
- Cost layer — Ad spend from every platform pulled via API or reliable export, normalized to the same currency and date.
- Identity & channel mapping — Consistent UTM taxonomy + first-party customer matching.
- Metric definitions — Written and enforced (what counts as a new customer, how revenue is recognized, etc.).
- Visualization layer — Looker Studio, Tableau, or similar that everyone trusts.
Practical steps
- Standardize UTM parameters across all campaigns.
- Build a central data warehouse or at least a well-structured BigQuery / spreadsheet layer that joins orders to spend.
- Create a short “definitions” document that the whole team uses.
- Validate regularly against raw platform and Shopify exports.
Once you have one trusted number for revenue and one trusted number for spend, every other analysis — CAC, ROAS, incrementality, MMM — becomes dramatically more reliable.
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