What are Attribution Models, and when should I use each one?

Attribution refers to giving credit to an ad for helping lead to a customer's purchase. There are different methods for assigning credit to ads for the role they played in causing a customer to make a purchase.

Because Triple Pixel tracks every touchpoint across your customers' entire customer journey, we can report on each of these while giving you the tools to decide which ad click deserves credit.

First, it's important to note that Triple Whale utilizes a lifetime attribution window -- meaning, all ads or clicked throughout the customer's journey will be tracked and included in that customer's story, even if those ads were clicked on 30, 60, or 100 days ago (but not before our Pixel was installed on your site, though). That way, you can select the correct attribution model (more detail on these below) to weigh the appropriate credit between each click in your customer journeys.

Each attribution model works differently, so it's important to understand how they work and the ideal use-case for each.

Last Click

Last Click Attribution gives full credit to the last ad click tracked in the customer's journey.

Example: If a customer clicked on Facebook ad #1, then Facebook ad #2, then a Google ad, and finally made their purchase, then the ad receiving credit would be the Google ad.

First Click

First Click Attribution gives full credit to the first ad click tracked in the customer's journey.

Example: If a customer clicked on Facebook ad #1, then Facebook ad #2, then a Google ad, and finally made their purchase, then the ad receiving credit would be Facebook ad #1.

Triple Attribution

Triple Attribution gives full credit to the last ad click per ad channel in the customer's journey. In this model, each marketing channel's final click for the particular customer receives full credit for the purchase.

Example: If a customer clicked on Facebook ad #1, then Facebook ad #2, then a TikTok ad, and finally made their purchase, then Facebook ad #2 would receive full credit AND the TikTok ad would receive full credit. In this example, using this model results in duplicate credit. In this model, the final click a user made within each ad platform is deemed the most significant for that channel, and credit is assigned thereby. Therefore, the credit is duplicated.

Why would you want to use a model that may generate duplicated credit? Triple Attribution is an incredibly powerful model for when you're running an omnichannel marketing strategy. Many brands will see Google Branded Search, for example, swallowing up all their BOF credit. Using Triple Attribution allows you to focus in on a particular channel at any given time, and give credit to the last ad click on a particular channel -- even if customers are subsequently clicking through ads on other channels as well.

As such, when viewing the Ads > All Channel page, using either of the "Triple Attribution" attribution models may result in the bottom-line revenue reporting higher than your Shopify sales data due to the duplicated attribution. As such, you would not want to use this model on the All Channels view, because the total orders would be duplicated. This model is ideal for optimizing a single channel's ads on the last click the customer made on that particular platform.

Triple Attribution + Views

Triple Attribution + Views is a unique attribution model for use with Facebook ad data. As you may know, Facebook models both click-through as well as view-through data -- meaning, conversions that are derived from an ad click as well as conversions that are derived from an ad view (known on Facebook as 1-day views).

We cannot independently verify Facebook's claimed view-through data since no one but Facebook has visibility as to the content users are viewing (but not clicking) on Facebook. However, what we can do is layer Facebook’s view-through attribution data on top of our own Triple Pixel ad=click attribution. This way, you can see the impact of Facebook's reported view-through modeled data when added to Triple Pixel's own ad-click attribution.

Example: If the Triple Pixel ROAS was 2.35, and Facebook's view-through attribution claimed an additional 0.5 ROAS, then toggling to the Triple Attribution + Views model will layer that additional 0.5 ROAS and the corresponding increase in Conversion Value on top of our our own click-through ROAS and tracked CV.

Linear (Paid Only)

Linear Paid equally splits credit evenly amongst all the ads in the customer's journey.

Example: If a customer clicked on Facebook ad #1, then Facebook ad #2, then a TikTok ad, and finally made a purchase, then all three ads would receive partial credit, which means that the credit is distributed evenly between them.

Linear (All)

Linear All is when the credit (conversion value and orders) are divided equally amongst any channels or sources that had a touchpoint (click) in the customer's journey to conversion -- regardless of whether the touchpoint was a paid channel or an organic source.

Use Linear All when you are viewing your channels on the "All" page within the Triple Pixel. In this view, you will now be able to see the exact number of orders and revenue we tracked through the pixel. This is a useful model to use when analyzing your entire marketing mix on an even playing field.

Linear All when on the All page will provide the true number of orders and conversion value we tracked. It will de-duplicate the Triple Attribution model that is standard.


Example: If a customer clicks on Facebook ad #1, then Facebook ad #2, Triple Whale is only taking into account that they clicked from Facebook, so it is one order attributed to Facebook, regardless of how many campaigns they clicked on. However, if you're only looking at the Facebook channel AND using "Triple Attribution", the orders are not de-duplicated. So, if someone clicked on multiple campaigns, their order is counted one time for every campaign they clicked on.


You can learn more about attribution models and the functionality of the Pixel by watching a scene from Episode 14 of our podcast, where our pixel-pro Corey dives deeper into these different models. The scene begins at 35 minutes.


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