Attribution Model Comparison
Enter the touchpoints behind one conversion and see how much the credit changes from one attribution model to the next.
Who gets the credit
| Touchpoint | Last click | First click | Linear | Time decay | Position-based |
|---|---|---|---|---|---|
| Paid social | $0.00 | $1,000.00 | $250.00 | $97.26 | $400.00 |
| Organic search | $0.00 | $0.00 | $250.00 | $194.53 | $100.00 |
| $0.00 | $0.00 | $250.00 | $319.15 | $100.00 | |
| Brand search | $1,000.00 | $0.00 | $250.00 | $389.05 | $400.00 |
Time decay halves a touchpoint's weight for every 7 days before the conversion. These are simplified models for comparison.
How each model splits credit
Last click gives all the credit to the final touchpoint, and first click gives it all to the first. Linear splits it evenly, and position-based gives 40% each to the first and last, with the remaining 20% split across the middle.
Time decay favors touchpoints closer to the conversion. This tool halves a touchpoint's weight for every 7 days before the conversion.
Why the comparison matters
The same sale can make a channel look essential or irrelevant, depending only on the rule you use. None of these models shows what the marketing actually caused, so a channel's credit isn't proof of its value.
Google has retired first-click, linear, time-decay, and position-based models in Google Ads and Google Analytics, which now offer last click and data-driven attribution. They're still useful for seeing how credit rules shape your numbers.
Disclaimer
This tool is for informational purposes only, and we don't guarantee the accuracy of its results. You're responsible for verifying any results before relying on them. See our terms of use.
Common questions
Is my information saved?
No. Your numbers stay in your browser, and they aren't sent to anyone.
Why isn't data-driven attribution included?
Data-driven attribution learns from the patterns in an account's own conversion data, so it can't be worked out from a single customer's path.
Which attribution model is the most accurate?
None of them measures cause, because each one only shares credit among the interactions it can see. To find out what your ads caused, use an incrementality test.
Read about attribution vs. incrementalityWant help putting this to work?
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