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Marketing Attribution Calculator

How conversion credit splits across touchpoints under each attribution model — and how differently the same data reads depending on which you choose.

Attribution models divide credit differently: first-touch gives everything to the first interaction, last-touch to the final one, linear splits evenly, and position-based gives 40% each to first and last with the rest shared.

Results update as you type
Results
Touchpoints
4
First-touch credit
Last-touch credit
Linear credit
Position-based credit
Time-decay credit
Largest disagreement between models
Total value being attributed
Reviewed September 2026. Funnel and advertizing arithmetic: the same formulas in every market, in your own currency. FTC guidance requires substantiation for performance claims derived from these measures.
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About marketing attribution

How the marketing attribution calculator works

Attribution models divide credit differently: first-touch gives everything to the first interaction, last-touch to the final one, linear splits evenly, and position-based gives 40% each to first and last with the rest shared.

The point of showing them together is that they disagree, often dramatically. A channel that looks worthless on last-touch can be the largest contributor on first-touch. No model is correct; they answer different questions.

Formula: linear: 1/n per touch; position-based: 40/20/40

Worked examples

InputsTouchpointsNote
Four touchpoints4first- and last-touch disagree completely
A single touchpoint1every model agrees
A long path6linear spreads thin

Frequently asked questions

Which attribution model is correct?

None of them. Each answers a different question — first-touch asks what created awareness, last-touch what closed the sale.

Why does last-touch dominate reporting?

Because it is the default in most analytics tools and needs no configuration. It systematically undervalues everything upstream.

What is position-based attribution?

40% to the first touch, 40% to the last, and the remaining 20% spread across the middle. It is a compromize between the two extremes.

How do I choose?

Look at several. If a channel is valuable under every model, it is valuable. If its worth depends entirely on the model, that is the finding.

What about incrementality?

It is the better question. Attribution divides credit for conversions that happened; incrementality testing asks which would not have happened otherwize.

Where these figures come from

Last checked: September 2026. These are standard industry definitions; where platforms disagree, the page says so.