What is an attribution model?

An attribution model in Google Ads is a rule, or set of rules, that determines how credit for conversions is assigned to different touchpoints in a user’s journey. In simple terms, it tells Google Ads how to distribute the value of a conversion across the various ads, clicks, and impressions that a customer interacted with before completing a purchase or taking a desired action (like signing up or filling out a form).

When someone clicks on multiple ads from your account before converting, the attribution model defines which click (or clicks) get the credit for that conversion. This affects your conversion data, campaign performance metrics, and ultimately the optimization decisions you make in your advertising strategy.

Understanding attribution models is important because different models can give you very different interpretations of performance, which can influence how you bid, allocate your budget, or value keywords and campaigns.

Types of Attribution Models in Google Ads

1. Last Click Attribution
   Gives 100% of the conversion credit to the last ad clicked before the conversion.
   This is simple but ignores earlier interactions that may have helped influence the decision.
   Example: If a Myntra customer clicks on an ad for “women’s dresses,” then later clicks on another ad for “Myntra summer sale” and makes a purchase, the second ad gets full credit.

2. First Click Attribution
   Gives 100% of the credit to the first ad click that started the conversion path.
   It’s useful when you’re focused on top-of-funnel awareness.
   Example: If a user first clicks on an ad for “Myntra kurtis,” browses, then later clicks on “Myntra ethnic sale” and purchases, the “Myntra kurtis” ad gets all the credit.

3. Linear Attribution
   Distributes the conversion credit equally across all the ad interactions on the path.
   It’s useful when you believe each touchpoint played an equal role.
   Example: If a user clicked on three different Myntra ads before converting, each ad would get 33.3% of the credit.

4. Time Decay Attribution
   Gives more credit to ad interactions that happened closer in time to the conversion.
   It assumes recent actions had a stronger influence than earlier ones.
   Example: If a Skechers buyer clicked on ads three days, one day, and 10 minutes before buying, most credit goes to the final touchpoints.

5. Position-Based (U-Shaped) Attribution
   Gives 40% credit to the first click, 40% to the last click, and distributes the remaining 20% equally among the middle interactions.
   This model assumes both the first and last touchpoints are the most influential.
   Example: If someone clicked on four Myntra ads in total, the first and last would each get 40%, while the two in the middle would get 10% each.

6. Data-Driven Attribution (DDA)
   This is Google Ads’ default and most advanced model. It uses machine learning to analyze all your conversion paths and assigns credit based on how each interaction actually contributed to the conversion.
   It’s only available if your account has sufficient conversion data.
   Example: If Google finds that users who click on a specific Skechers “Running Shoes” ad are 70% more likely to convert, that ad will receive more credit—even if it wasn’t the last or first touchpoint.

Why Attribution Models Matter

Attribution models directly impact how your campaigns are evaluated. Using the wrong model can lead to underestimating or overestimating the performance of certain campaigns, keywords, or devices.
For example, last click attribution may undervalue upper-funnel campaigns like display or YouTube ads that introduce your brand to users. On the other hand, data-driven attribution shows you which campaigns truly helped conversions along the path.

Example for Myntra

Myntra runs Search, Display, and YouTube campaigns. A user sees a YouTube ad for “Myntra Summer Fashion,” later searches “Myntra dresses,” clicks a Search ad, and finally clicks a retargeting Display ad before buying.

• If using Last Click, only the Display ad gets the credit.

• If using Linear, all three ads share equal credit.

• If using Data-Driven, Google looks at historical patterns and may assign 50% credit to the YouTube ad, 30% to Search, and 20% to Display—if YouTube ads are shown to have strong influence on conversions.

Best Practices

• Start with Data-Driven Attribution if your account has enough data. It provides the most accurate view of what’s working.

• If you don’t qualify for DDA, Position-Based or Linear can give a more balanced view than Last Click.

• Avoid relying only on Last Click—it often undervalues awareness campaigns.

• Regularly review attribution reports in Google Ads to see how different touchpoints contribute to conversions.

• Use attribution data to adjust bidding, keywords, ad copy, and budget allocation.

Conclusion

An attribution model helps determine how credit is assigned across your marketing efforts. Choosing the right model is essential for accurately understanding what’s driving results, which campaigns are really contributing to sales, and how to optimize your strategy. For large platforms like Myntra or Skechers, using the right attribution model ensures smarter investment in the channels, campaigns, and creatives that actually impact customer decisions. It moves you away from guesswork and toward informed, data-backed advertising decisions.