Glossary · Attribution
What is multi-touch attribution?
Multi-touch attribution is any attribution approach that divides the credit for a conversion across several of the touchpoints that preceded it, instead of giving it all to the first or last one.
Also called: MTA, Multi-channel attribution
Updated
Multi-touch attribution models compared
| Model | How credit is split | Best for |
|---|---|---|
| Linear | Equally across all touches | Seeing the whole path without bias |
| Time decay | More to recent touches (e.g. halves every 7 days back) | Short decision cycles |
| Position-based | 40% first, 40% last, 20% spread over the middle | Valuing discovery and closing |
| Data-driven | Statistical model of which touches change conversion odds | High-volume advertisers |
Multi-touch attribution example
A $100 purchase follows four sessions: Google organic (day 0), newsletter (day 6), X (day 10), direct (day 14). Linear gives each $25. Position-based gives Google $40, direct $40, and $10 each to the newsletter and X. Time decay with a 7-day half-life gives the most recent touches the most: roughly $11, $19, $28 and $42 respectively. Same money, three stories.
Why multi-touch attribution matters
Customers rarely buy on the first visit. Multi-touch models stop single-touch models from over-crediting one end of the journey, and comparing several models shows which channels open, which nurture and which close.
Limits of multi-touch attribution
- It can only split credit between touches it saw. Podcasts, word of mouth and dark social never appear as touches.
- Identity gaps. Touches on another device or after cleared cookies are missing.
- Correlation, not causation. Rule-based models are conventions; even data-driven ones aren't controlled experiments. Incrementality tests answer "would this have happened anyway?"
- Shrinking options in ad tools. In 2023 Google removed first-click, linear, time-decay and position-based models from Google Ads and GA4, leaving data-driven and last-click.
How VisitTrack does multi-touch attribution
VisitTrack's Revenue tab computes five models at once — first touch, last touch, linear, time decay (7-day half-life) and position-based (40/40/20) — over each paying visitor's sessions up to the purchase, so you compare them rather than commit to one. Totals always add up to the real revenue (fractional cents are rounded so each column sums exactly), and payments with no recorded session are shown as unattributed rather than dropped. Payments come from Stripe, Polar, Lemon Squeezy, Paddle or Razorpay via revenue attribution.
Frequently asked questions
What is the best multi-touch attribution model?
There isn't one best model. Position-based is a reasonable default when both discovery and closing matter, linear when you want no bias, and time decay for short buying cycles. Comparing several is more useful than choosing one.
Is multi-touch attribution accurate?
It is a convention for dividing credit, not a measurement of cause. It's only as complete as the touches the tool can see, so offline and private sharing channels are always under-credited.
Related terms
- Linear attributionLinear attribution is a multi-touch attribution model that splits the credit for a conversion equally across every touchpoint in the customer's path.
- Time-decay attributionTime-decay attribution is a multi-touch attribution model that gives every touchpoint some credit for a conversion, but more to touches that happened closer in time to the conversion.
- Position-based attributionPosition-based attribution, also called U-shaped attribution, is a multi-touch model that gives 40% of the credit to the first touch, 40% to the last touch and splits the remaining 20% evenly across the touches in between.
- First-touch attributionFirst-touch attribution is an attribution model that gives 100% of the credit for a conversion or payment to the source of the visitor's very first visit, ignoring every visit that came after it.
- Last-touch attributionLast-touch attribution is an attribution model that gives 100% of the credit for a conversion to the source of the last visit before it happened.
- Revenue attributionRevenue attribution is the practice of connecting each payment to the visitor who made it and the marketing sources — referrer, campaign, landing page — that brought that visitor, so you can see how much money each channel actually produced.
Tools and guides
See which channels actually bring paying customers
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