Last click attribution

Last-click attribution is one of marketing measurement analytics models that advertisers can use to measure performance of their advertising campaigns. Since the customer journey often involves multiple platforms and devices, attribution models are how advertisers determine which keyword, ad platform, or device led to the eventual sale. When marketers are using a last-click attribution model, the credit for a conversion is attributed to the final ad clicked before a sale or goal completion.

For example, let’s say that a customer starts their journey on Facebook by clicking on an ad and then Googles the company name, then sees another ad, clicks on it on Google, visits a website, and completes a purchase. In the case of last-click attribution, only the final click from Google Ads would get the credit for the conversion. Similarly in mobile app install campaigns, while a person might see five or six ads before eventually deciding to tap one and install the app, only the last tap gets credit.

As you can see from this example, one of the major flaws with last-click attribution is that clearly the initial Facebook ad had some impact on the eventual sale, and thus should receive some credit.

HubSpot summarizes the pros and cons of last click attribution as follows:

Last click attribution is helpful if you want to know which of your marketing channels and touchpoints have the most influence in the final stage of the buyer’s journey. While this is helpful information, it doesn’t account for the numerous other channels and touchpoints that impacted a customer from the very start of the buyer’s journey.

In order to address the concern that last click does not provide enough insights into the entire customer journey, there are several other attribution models that advertisers can use. As Google highlights in their article on attribution models, the most common examples of each measurement technique includes:

• Last click: As we just discussed, this model gives conversion credit to the last-clicked ad and keyword.
• First click: This is basically the opposite of las click. This model gives credit to the ad and keyword that was clicked first.
• Linear: This model distributes credit equally across each interaction with an ad on the journey to a conversion. (One challenge: some and likely many of the customer journey steps are entirely invisible to marketers.)
• Time-decay: This model gives more credit to ads or touches that are interacted with closer to the time of conversion.
• Position based: This model gives 40% of the credit to both the first and last click interaction, and the remaining 20% is distributed to other ad interactions in the customer journey. (Marketers can play with the percentage amounts as well.)
• Data driven: This model allocates credit based on previous data in the account for each particular type of conversion.

As you can see, each of these models have their own use cases, although it’s important to note that last-click attribution is typically the most common model for advertisers to measure their ad performance.

Mobile attribution is typically a last-click attribution scenario. Especially today on iOS 14 and beyond, where SKAdNetwork literally only shares the last click before an install.

However, there are ways to go beyond that.

Monitoring clicks and assists gives you a sense of which ad partners are contributing to conversions and installs. SKAdNetwork is adding details on view-through attribution, which helps provide a more full picture than last-click attribution, and version 3.0 has “loser postbacks,” which provides postbacks for up to five ad networks whose ads where shown but who did not incite the winning click.

And, of course, Singular offers class-leading cost aggregation which enables modeling and incrementality methods for attributing the results of marketing campaigns to the causes.

In the context of last-click attribution, Singular prioritizes the ad interaction that is closest to the time of install. As described in our Help Center article on prioritizing touchpoints and last-touch attribution:

This way, Singular picks the touchpoint that is most relevant to the install and is able to attribute the install to the relevant partner network.

In summary, Singular helps advertisers accurately attribute and report on their advertising efforts in an accurate and holistic way in order to help improve profitability and increase ROAS.