Attribution debt sits with you, not the vendor
Whoever produced the numbers, the misallocated budget is yours. Three consequences, and why that changes the questions worth asking a vendor.
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By Joris van Huët, Founder & CEOUpdated 3 min read
Whoever produced the numbers, the misallocated budget is yours. No vendor refunds a year of over-funding the wrong channel, and no contract makes the position recoverable.
That asymmetry should shape which questions you ask before buying, not after.
Three consequences
| Consequence | What follows |
|---|---|
| The error is uninsurable | You cannot outsource the risk, only the work |
| Verification is your job | A vendor cannot mark its own homework |
| Portability matters more than features | You need to be able to check with a second method |
Verification is the one people skip
Every measurement claim can be checked against something. Platform claims can be checked against your order table. A causal read can be checked against a period you already understand, and against a deliberate test on one channel.
None of that verification is the vendor's to do. A vendor can make it possible by publishing method, but the checking belongs to whoever carries the consequence. The vendor-side commitments are in why vendors should explain methodology openly.
Why portability is the ownership question
If your measurement history lives in a vendor's systems, you cannot check this year against last year after leaving, and you cannot re-run a past window through a different method. That means the debt becomes unauditable at exactly the moment you most want to audit it.
An export-based approach avoids it structurally: the source is your own Google Analytics account, so a window you can export is a window any method can read, now or later. The argument in full is you do not own your attribution data.
The questions this reframing produces
Not "how accurate is your model", which no vendor can answer credibly about your business. Instead: what would I check this against, what do you publish that lets me, and what can I take with me.
Those three are answerable, and the quality of the answers is a better signal than any accuracy claim.
What we do about it on our side
Publish the method in plain language on how it works. Take the input as an export you produce, so nothing depends on a connection you cannot revoke.
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The sentence worth internalising
You can delegate the analysis. You cannot delegate the consequence, which means you cannot delegate the checking either.
Related answers
Frequently asked questions
Can I hold an attribution vendor responsible for bad decisions?
Practically, no. No vendor refunds a year of over-funding the wrong channel, and no contract makes the position recoverable. You can outsource the analysis but not the consequence, which means the verification stays yours.How do I verify an attribution vendor's numbers?
Against your own order table for totals, against a past period you already understand, and against a deliberate test on one channel. A vendor makes this possible by publishing method and showing intervals; the checking itself is yours.What questions matter more than accuracy claims?
What would I check this against, what do you publish that lets me check it, and what can I take with me when I leave. All three are answerable, unlike a vendor's accuracy claim about your specific business.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Keep reading
Terms in this article
- AnalyticsAnalytics is the systematic computational analysis of data. It reveals customer behavior and measures campaign performance.
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- Attribution DebtAttribution debt is the gap between what your ad platforms claim drove revenue and what actually caused it, carried quarter after quarter into the budget. It is how marketing debt accrues: allocate on claimed conversions long enough and the plan itself becomes the liability.
- Google AnalyticsGoogle Analytics is a web analytics service that tracks and reports website traffic.
- Marketing AttributionMarketing attribution assigns credit to marketing touchpoints that contribute to a conversion or sale. Causal inference enhances attribution models by identifying true cause-effect relationships.