Replace multi-touch attribution in four steps
Switching attribution methods mid-year usually creates a reporting gap nobody planned for. Four steps that avoid it, in the order that keeps everyone able to compare.
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By Joris van Huët, Founder & CEOUpdated 3 min read
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The failure mode when switching attribution methods is not the new tool, it is the reporting gap the switch creates. Numbers change on the day of the migration, nobody can tell whether the business changed or the instrument did, and the new method spends its first quarter defending itself.
Four steps avoid that, and the order is not negotiable.
The four steps
| Step | What happens | How long |
|---|---|---|
| 2 | Reconcile and document the difference per channel | A day |
| 3 | Agree the new decision thresholds explicitly | One meeting |
| 4 | Retire the old method, keeping its history exported | An hour |
Step 1. Parallel run on history, not on the future
Run the new method on a window the old method already reported. This is the whole trick. You get a direct comparison with no waiting, and no period exists where you have one number and not the other.
Pick a window with real spend variation in it, because a flat window will not distinguish the methods.
Step 2. Reconcile per channel and write it down
Expect the differences to concentrate in predictable places: branded search, retargeting, and anything that fires close to the conversion. Multi-touch attribution distributes credit along an observed path, so it rewards proximity. A causal read asks what would have happened otherwise, so it does not.
Write one line per channel explaining the gap. This document is what stops the same argument recurring monthly for a year. The mechanics of the disagreement are in causal versus rule-based attribution.
Step 3. Reset the thresholds
Old thresholds do not transfer. If a channel was scaled at a reported 3.0 return, that threshold was calibrated against a number that included credit for conversions the channel did not cause. Applying it to a causal estimate will look like every channel got worse overnight.
Agree new numbers explicitly, in the meeting, before anyone sees a monthly report in the new units.
Step 4. Retire, but export first
Export the old method's full history before cancelling, including per-channel numbers by period. You will want it for year-on-year comparison, and it stops being available when the contract does. The general point is in you do not own your attribution data.
What this looks like with us
Step one is a €99 one-time read on a Google Analytics export of a window you have already reported, refundable within 30 days, no questions asked. Steps three and four are yours.
The mistake to avoid
Do not switch in the middle of peak trading. The one period where you most need comparability is the worst possible time to change the instrument, and the confusion lasts well into the following year.
Related answers
Frequently asked questions
How do I switch attribution methods without a reporting gap?
Run the new method on a past window the old one already reported, rather than starting fresh going forward. That gives an immediate side-by-side comparison and means no period exists where only one number is available.Why do my channel numbers drop when I move to causal attribution?
Because multi-touch attribution distributes credit along an observed path and therefore rewards proximity to the conversion. A causal estimate asks what would have happened otherwise. Thresholds calibrated against the first will look punitive against the second.When is the worst time to change attribution method?
During peak trading. It is the period where comparability matters most and where a change in the instrument is impossible to separate from a change in the business, and the resulting confusion tends to last into the following year.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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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.
- ConversionConversion is a specific, desired action a user takes in response to a marketing message, such as a purchase or a sign-up.
- Google AnalyticsGoogle Analytics is a web analytics service that tracks and reports website traffic.
- Multi-Touch AttributionMulti-Touch Attribution assigns credit to multiple marketing touchpoints across the customer journey. It provides a complete view of channel impact on conversions.
- RetargetingRetargeting is online advertising that targets users who have previously interacted with your website or content. Attribution analysis shows the causal role of retargeting in driving conversions and improving ad spend.