Attribution model
An attribution model decides how credit for a conversion is split between the ad clicks that came before it. Google Ads defaults to data-driven.
In the platformMeasurement
Attribution model
An attribution model decides how credit for a conversion is split between the ad clicks that came before it. Google Ads defaults to data-driven.
Someone might click a generic Search ad, then a brand ad a week later, then buy. Last click gives the brand ad all the credit. Data-driven attribution, the default, uses your account's conversion paths to give each step a share. In 2026 Google Ads offers only these two; first click, linear, time decay and position-based were removed in 2023. The model changes which campaigns look profitable, not how many sales you made.
Where you'll see it
In Google Ads, the model is set per conversion action: Goals > Conversions > Summary, open the action, and edit "Attribution model". To see how credit shifts, use Goals > Attribution, including Model comparison and Conversion paths. Meta and TikTok don't offer a choice of model the same way; they credit conversions within the attribution window you set, so their numbers overlap with Google's and shouldn't be added together.
Worked exampleA generic Search campaign, $2,000 a month
| Model | Conversions credited | CPA |
|---|---|---|
| Last click | 10 | $200 |
| Data-driven | 16 | $125 |
Under last click, you might cut this campaign. Under data-driven, it looks viable, because it often starts paths that end on a brand click. Fractional credit, such as 15.6 conversions, is normal with data-driven.
Do
- Use the same model on actions you compare
- Run an incrementality test to prove a campaign caused the sale
Don't
- Add up Google, Meta and TikTok conversions as real sales
- Switch models and compare the new numbers with old reports