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Mastering App Retargeting: Introduction to Incrementality

As app marketers begin to shift their focus away from just user acquisition to retargeting to get the highest possible value out of their users, new ad formats and approaches to segmentation and optimization bring with them new challenges for how to identify the strategies that bring the most value. Further, a lack of industry standards in attribution and measurement hinder their ability to make well-informed decisions — from understanding ROI to knowing which creatives perform best. How can app marketers make data-driven decisions to assess the true impact of retargeting on their user base?


After witnessing the growing frustration of marketers in the industry, back in 2016, we began to focus all our efforts on providing clients with the tools they need to measure uplift and determine the strategies that provide the most value. In this series of posts, we’ll be sharing insights and tips based on our experience conducting over 300 incrementality tests for our clients across all verticals from gaming and mCommerce, to banking. This first post will explore the basics of incrementality measurement and take a look at some of the use cases and results our clients have seen with uplift testing, to help you decide if measuring incrementality makes sense for you and your app.

What is Incrementality Measurement?

Running an incrementality test, or ‘uplift test’ provides insights into the incremental value added by a marketing strategy or vendor. With an uplift test, the impact of an ad being shown to a target group is compared against a control group, which is not shown any ad. This allows advertisers to compare how users that are not exposed to retargeting ads are performing compared to users that are exposed to ads. By measuring the lift in the value of purchases or increase in engagement that ads provide, advertisers can use the insights gleaned to better optimize and forecast retargeting ad spend, and determine the most effective strategy to achieve their goals.

‍Check out these talks from our incrementality testing expert for more info:


How Can Incrementality Measurement Help Marketers?

Some of the top mobile apps like Netflix, eBay, and advocate for A/B testing almost every aspect of their business before making decisions, including the incremental value of their advertising efforts. By isolating a variable like creative or audience under testing conditions, it becomes easier for marketers to connect it to business results and shift budgets to the tactics that drive long-term success with advertising.

There are a number of questions that marketers can attempt to answer in measuring incrementality. We’ve listed some of the most common use cases we see for testing uplift below.

Does it Make Sense to Target Active Users?

The primary use case for measuring incrementality we see here at Adikteev, is marketers who use incrementality testing to understand the uplift in engagement or revenue retargeting will have on a specific segment of users. Although what you will test will largely depend on your goals, app vertical, or business model; most marketers want to understand if it makes sense to retarget active users and users who have already converted in their app. In other words, does retargeting my active users drive additional revenue?

With gaming apps, ‘Whales’ or top spenders can account for up to 70% of total in-app purchase revenue. For gaming app marketers, measuring incrementality can help to determine whether or not it is valuable to retarget these active, high-value users who may convert organically, without being shown retargeting ads. It can also help you to discern other, more valuable user groups to focus your retargeting efforts on.


One of our gaming clients was interested in testing this hypothesis. The client was initially reluctant to target active users for fear of cannibalizing their organic audience, but given the app’s game mechanics, our account management team suggested an incrementality test to determine if targeting active users would generate significant lift in revenue. By analyzing the campaign, the results were clear: retargeting active users drove a significant increase not just in the number of purchases, but purchase value as well.


% lift in revenue & number of purchases following exposure to retargeting campaign
% lift in revenue & number of purchases following exposure to retargeting campaign

The client saw a 40% increase in the number of purchases as well as a 35% increase in purchase value of users exposed to retargeting ads vs the control group. Initially wary of retargeting active users, the client discovered that not only does retargeting actives not have a negative impact, but it actually drove a significant increase in bottom-line revenue. Armed with this information, the client opted to shift more budget to target active users — confident that the campaign would produce incremental lift.

It’s important to note that these results are specific to gaming and this particular free-to-play gaming client who monetizes with in-app purchases. When developing your test hypothesis, make sure that you’re testing a strategy that makes sense for your application, that works well with the way you monetize, and that at the end, you look at more than one metric. It could be the case that a particular marketing strategy is not adding incremental revenue but it does add incremental engagement — if that works for you that’s good, if not try another approach.

Does it Make Sense to Target Inactive Users?

In our previous post, we looked at some of the ways marketers are using app retargeting to drive engagement and revenue in their apps. One common use case we mentioned was marketers who run re-engagement campaigns to remind inactive users to come back and engage with their app. It makes sense then, that a question marketers often want to answer is whether or not it is valuable to target inactive or dormant users. In other words, can retargeting drive inactive users to be more engaged or complete a purchase?

Average Retention Curve for Android Apps
Average Retention Curve for Android Apps

Retention data from Quettra Mobile Intelligence tells us that across all industries, it’s normal for an app to lose 80% of its daily active users in 30 days. The question here is — is it possible to drive engagement and prevent some of this user churn with app retargeting?


To test this hypothesis, we used the intention to treat method (ITT) and looked at the retargeting campaigns of a number of apps across gaming, eCommerce, travel and more. We split the app’s audiences into two groups:

  • The control group: will not be retargeted
  • The target group: comprised of users who are eligible to see ads

Not everyone in the target group will see an ad due to budgetary constraints and users’ RTB visibility. The users in the target group who see ads are the exposed group.

We found that retargeting drove a significant lift in retention after 7 days and even after 30 days, against the control group who were not exposed to ads. Though there were some slight differences in results depending on the app vertical, overall the retention rate after 7 days for gaming apps was on average 36% higher for retargeted users. In non-gaming, the retention rate of retargeted users was 28% higher.

Impact of Retargeting D+7
Impact of Retargeting D+7

After 30 days, the retention rate of gaming app users who were exposed to retargeting ads was 54% higher and 33% higher in non-gaming.

Impact of Retargeting D+30
Impact of Retargeting D+30

These results demonstrate an interesting opportunity for app marketers. By retargeting inactive users, it is possible to increase engagement and reduce churn and the longer your users stick around, the more loyal they will become, increasing the probability they will become payers. If your app monetizes with ads, retaining users is equally beneficial since the more time the user spends with your app, the more opportunities you have to show them in-app ads.


These are just a few examples of the ways marketers can use incrementality measurement to ensure they are employing the right retargeting strategy to reach their goals. Measuring incrementality can be a game-changer in how organizations measure the effectiveness of their marketing spending, and improving the processes for this will continue to be a priority for Adikteev.

In our next post, we’ll be exploring the most popular methodologies for incrementality testing and outlining the key steps to set up your incrementality test and ensure statistically significant results.

If you’re interested in conducting your first incrementality test or want to know more on the topic, contact your dedicated account manager or shoot an email over to

Originally posted on Medium.