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Solution: DTC brands

Causal Attribution for DTC Brands

Three dashboards, three numbers, and a budget meeting where nobody can say which to trust. Causal attribution is the tie-breaker.

€99 once, excl. VAT. Full refund within 30 days, no questions asked. You keep the read.

By , Founder & CEOUpdated

The problem you are living with

Triple Whale shows one number, Meta shows another, GA4 shows a third, and the actual sales in Shopify rarely agree with any of them. Your team argues about which dashboard is right while spend drifts to whatever reports the biggest ROAS. The channel that creates demand quietly under-spends. The channel that captures it quietly scales. Neither of those decisions came from data; they came from whichever vendor wrote the most flattering attribution rules.

What causal attribution changes

Instead of dividing credit by rules, causal attribution measures whether each conversion would have happened anyway. One read of what each channel caused, next to last-click, with a data-health score on every channel. No more reconciling three dashboards. The meeting becomes a single decision: which channel actually causes incremental sales, and where the budget should move.

How it fits your workflow

Export 12 months or more of GA4 data. Longer reads better. Drag the file into Causality Engine. The causal model runs in 1–2 minutes and returns what each channel caused next to last-click, with a data-health score and a next step for every channel. €99 per run. No subscription, no integration project, no engineering ticket.

Frequently asked questions

  • Why does the causal read credit my channels with less than my platforms claim?
    Because each platform takes credit for sales that would have happened anyway, and several platforms claim the same sales at once. The causal read shares your actual revenue out once, by what each channel caused, so the totals reconcile to what you really sold.
  • Do I need a data team?
    No. Causality Engine runs on one standard GA4 export, as a CSV. The output is a plain-English read with a next step for every channel, and how to test it. No statistics degree required.
  • What if I am scaling fast and last quarter is not a guide?
    Causal attribution still tells you what was incremental at your previous scale. As spend grows, you can re-run weekly. Each read gives every channel a data-health score and a next step, and where data health is under 90 it says to move budget in steps.

Use cases

  • Cut an underperforming channel
  • Scale a channel above its current spend
  • Identify a measurement blind spot

Your platforms guess.
We run the math.

Upload a GA4 export and see what each channel caused, next to last-click, in 1–2 minutes. The read is yours to keep.

The free finding runs in your browser. Your file never leaves it. The full read is €99, refundable within 30 days, no questions asked. Prices exclude VAT.