Attribution Modeling

Attribution modeling is the rule, or set of rules, that determines how credit for sales and conversions is assigned to touchpoints in conversion paths. For example, the Last Interaction model in Analytics assigns 100% credit to the final touchpoints (i.e., clicks) that immediately precedes sales or conversions. In contrast, the First Interaction model assigns 100% credit to touchpoints that initiate conversion paths. Following is an example of a customer’s conversion path and how the different attribution models would attribute value:

A customer finds your site by clicking one of your Google Ads ads. She returns one week later by clicking over from a social network. That same day, she comes back a third time via one of your email campaigns, and a few hours later, she returns again directly and makes a purchase. Which avenue gets credit for the conversion? It depends on the attribution model.

Google Ads offers several attribution models:

 Last click: Gives all credit for the conversion to the last-clicked ad and corresponding keyword.

 First click: Gives all credit for the conversion to the first-clicked ad and corresponding keyword.

 Linear: Distributes the credit for the conversion equally across all ad interactions on the path.

 Time decay: Gives more credit to ad interactions that happened closer in time to the conversion. Credit is distributed using a 7-day half-life. In other words, an ad interaction 8 days before a conversion gets half as much credit as an ad interaction 1 day before a conversion.

 Position-based: Gives 40% of credit to both the first and last ad interactions and corresponding keywords, with the remaining 20% spread out across the other ad interactions on the path.

 Data-driven: Distributes credit for the conversion based on your past data for this conversion action. It’s different from the other models, in that it uses your account’s data to calculate the actual contribution of each interaction across the conversion path. Note: This is only available to accounts with enough data. Learn more about data-driven attribution

 

Why is it important to move away from Last Click?

The average person clicks on about four different Search ads before converting. Last Click attribution, the default choice in Google Ads, ignores three out of those four clicks and does therefore not give a fair representation of their value. As marketers, it is crucial to understand the value of each click that contribute to a conversion to be able to allocate investments where they have the most impact.

To get an optimal basis for decision making it is therefore important to select the attribution model that best distributes conversion value across the contributing clicks. Moving from Last Click to more accurate models will help you increase your number of conversions and invest your money where they will have the most impact. NB that AdWords attribution models only distributes value across Search campaigns.

Switch attribution model by editing each conversion action under Tools > Conversions.

Choose Data-driven attribution when available

For accounts with enough conversions (~600 conversions and 15 000 clicks/month) the option to use a Data-driven attribution model will appear under Conversion actions. When available the Data-driven model is the best option as it uses machine learning to distribute conversions in accordance to the actual value of each click. In comparison to Last Click, Data-driven attribution delivers on average  5% more conversions at similar CPA.

Choose a static distribution if Data-driven isn’t available

Even when the Data-driven model isn’t available one should still always move away from the Last Click model and instead choose the most appropriate static model that distributes conversion value across contributing clicks. Which model is most appropriate depends on your business and it’s customers.

For companies with an aggressive growth strategy we recommend the Position-based attribution model that distributes 40% of the conversion to the first click, 40% to the last click and spreads the remaining 20% evenly across the clicks in between. The Position-based model focuses on driving new customers into the sales funnel.

For companies with a conservative growth strategy where focus lies on driving sales/conversions rather than finding new customers, the Time Decay model is recommended. This model will attribute increasing value with each click so that the closer the click was to the actual conversion, the more value it will get. This means that the last click will continuously be attributed most value and the first click the least.