Picture an F.C. Barcelona play. After a corner by the opposing team, the goalkeeper starts the counterattack with a strong goal kick to midfield; Iniesta picks up speed and reaches the final third, then passes to Neymar, who crosses to Messi, who scores. Who gets credit for the goal: Trilogi? Nooo, Messi! But in reality not all the credit is his; it belongs to every player involved in the play. The problem arises when deciding which contribution mattered most, if any mattered more than another. That’s the same problem we need to solve when deciding which channel gets credit for a sale.
Something very similar happens in web analytics when analyzing the channels a user interacted with before completing a purchase.
What are sales attribution models?
According to Google, an attribution model is a rule or set of rules that determines how credit for sales and conversions is assigned to touchpoints in conversion paths.
This lets us weight the different traffic acquisition channels based on how we define each one’s contribution to conversions.
Google Analytics (GA) offers several sales attribution models.
To explain them, we’ll use an example of interactions before a sale and how GA assigns credit under each attribution model.
A user visits our website for the first time from an AdWords ad. The following week they return, this time by clicking on a social network. That same day they come back a third time through an email marketing campaign, and finally, an hour later, they visit our website directly and make a purchase.
Next, let’s see how this conversion is reflected depending on the attribution model used.
- Last interaction (4th interaction in the chart)
Assigns the sale’s value to the last touchpoint with the website before the sale. In the example, 100% would go to the direct channel. - Last non-direct click (3rd interaction in the chart)
All direct traffic during the interaction is excluded, and full credit for the sale goes to the last channel the customer clicked before converting. In the example, 100% would go to email marketing (email). - Last AdWords click (1st interaction in the chart)
The full value of the sale is assigned to the user’s last click on an AdWords campaign. In the example there is a first and last AdWords click, which would receive 100% of the credit. - First interaction (1st interaction in the chart)
The first touchpoint gets 100% of the conversion credit. In the example this would also be paid search (AdWords). - Linear
This model assigns the same share of the sale to each touchpoint from the start until the sale occurs.
In the example, 25% would go to each of the 4 channels: paid search, social network, email and direct. - Time decay
This model assigns a higher percentage to the touchpoints closest in time to the sale or conversion.
In the example, the channels receiving the most credit would be email (3rd interaction) and direct (4th interaction), since these are the channels the user interacted with in the hours before the sale. - Position-based
In this case, 40% is assigned to the first and last interactions, and the remaining 20% is spread evenly across the middle interactions, i.e., 10% to the social network channel and another 10% to the channel that, in the example, is email.
Continuing with the example, if the sale amounted to €2,000, attribution would work as follows:
By default, Google Analytics (GA) considers 30 days when analyzing interactions. However, this setting can be changed quickly and easily, within a range of 0 to 90 days. It’s important to know that by default GA always shows reports using the last non-direct click attribution model, i.e., last click excluding direct traffic. We should also keep in mind that sales can be attributed to the offline channel using the Analytics Measurement Protocol.
Custom models
If none of GA’s predefined attribution models suits us, we can create an entirely new model or start from an existing one and modify it.
A custom model can be created in the Attribution Model Tool by changing the lookback window (days before conversion), adjusting the credit assigned based on engagement (time on site, pages viewed or a custom rule), and other related elements such as path position, campaign, keyword and so on.
This tool not only compares results from different attribution models —up to three at a time— but also evaluates the effectiveness of each channel. This helps us make better investment decisions based on the results.
And you, which attribution models do you use?
If you have any questions, feel free to contact us: at Trilogi we’ll be happy to advise and help you.
