- Preventing user churn is crucial and should not be overlooked by mobile marketers, as it helps maintain a stable and loyal user base
- Churn prediction models help app marketers overcome one of the most common pain points – finding where customers are likely to stop engaging and preventing them from lapsing
- Retaining users is more cost-effective than acquiring new users, and prevents them from leaving in favor of competitors’ apps.
What is user churn?
The definition of user churn in the mobile context is the loss of app users or customers over time. Churn is one of the most common pain points for app marketers looking to monetize their existing users or grow an active user base. Right now one of the most interesting developments in user retention is in the advancement of churn prediction models.
Usually, marketers use inactivity as a proxy for when users will churn: ie how many days have they been inactive in the app. It’s a pretty good estimate, but we’re finding that with churn prediction models, marketers can predict with higher precision which point in the funnel certain users are likely to leave the app and target them ahead of time to prevent that outcome from happening.
It is often more cost-effective to retain customers rather than acquire new customers, for example, in a Mobile Attribution Partner study in 2022 we found that for iOS User Acquisition is on average 84% more expensive than retargeting returning users. Therefore, at Adikteev we’re aiming for churn prediction to pinpoint exactly when a user will leave in order to take preventative measures to keep them engaged.
What pain points can preventing churn help overcome?
Preventing user churn is crucial as it helps maintain a stable and loyal user base. Retention over reacquisition is a key principle to keep in mind, as winning back lapsed users is often more costly and time-consuming than retaining existing ones. By preventing churn, app marketers can ensure that their users continue to derive value from their apps, leading to increased user loyalty.
Churn prevention also helps overcome the pain points associated with competing user attention. Users have a plethora of options when it comes to different products and services. The average smartphone user can have an average of 80 apps installed on their device.
A decrease in interest in an app can result in users leaving in favor of a competitor. However, by implementing strategies to prevent churn, app marketers can keep their users engaged and satisfied, reducing the likelihood of them seeking alternatives or just getting bored. This can also help businesses differentiate themselves from their competitors by providing superior experiences and value propositions.
How quickly can you see improvements in LTV if you can prevent users churning?
You can see improvements to Lifetime Value pretty much immediately. If we’re talking about a gaming app, we typically see that users who spend money in-app will either leave the app, or continue to spend money in-app while they are using it. So if you prevent that user from abandoning your app, they will continue to behave as a payer does.
What do app marketers need to have in place to prevent user churn?
First and foremost, I’m of course going to suggest that app marketers have a robust retargeting program in place, tailored to the specific vertical they are working in. Reaching out to users who have downloaded the app and encouraging them to continue the user journey through personalized ads is one of the best ways to maintain an engaged app audience.
But as privacy constraints are becoming more and more of a concern, marketers should also consider implementing these churn prediction models. Applying lists of about-to-churn users to run retention strategies through retargeting, in-app and CRM messaging, or push notifications is only going to become more important as user-level data becomes less and less available. In this context, the data you have to retain existing high-value users will give you a competitive edge in a crowded field.
Finally, retargeting programs, churn prediction, and push strategies are important, but above all and regardless of channel, the app experience should be consistent. Aligning messaging and branding with the product team and the rest of the marketing team ensures a cohesive user experience and reinforces the app’s value proposition. A good retention strategy starts with consistency across the app.
What are the key KPIs marketers should measure to understand user churn?
Measuring Return On Ad Spend (ROAS) like any other campaign will help gauge the overall effectiveness of retargeting.
At Adikteev, we also recommend tracking:
- Predicted vs Actual Churn: the comparison between predicted churn and actual churn. This allows you to refine your targeting strategies and messaging to reach at-risk users.
- Associated Revenue: the revenue generated by users who are at risk of churn. By measuring the associated revenue, marketers can prioritize targeting users who have a higher potential value.
- Scores per User: scores assigned by the churn algorithm to individual users based on their likelihood of churn. Marketers should monitor these scores to identify users with the highest risk and allocate budget accordingly.
Apart from these specific KPIs, we use the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) method to measure the performance of churn prediction models. AUC represents the model’s ability to distinguish between churned and non-churned users by plotting the true positive rate against the false positive rate. In other words, comparing the number of correctly identified churners to incorrectly identified churners. A higher AUC value indicates a more accurate and effective churn prediction model.
How should the strategies of churn prevention and app retargeting work together?
Segmenting your app audience is essential before embarking on any kind of remarketing campaign. When focusing on retargeting, a good place to start is dividing users into payers, non-payers, and new installers. From there, you can divide these segments further into active payers and lapsed payers, active non-payers and lapsed non-payers, and so on. This will give you a sense of who your users are, what their behavior is like, and which users are the most valuable to your app’s growth. Marketers can deliver personalized and targeted campaigns to each segment, increasing the chances of retaining users and reducing churn.
Applying churn prediction algorithms to these segments can remove some of the test-and-learn work of running campaigns. By analyzing user behavior and historical data, predictive models can identify patterns and indicators of potential churn. This information can then be used in conjunction with rule-based segmentation to target at-risk users with specific campaigns and offers aimed at reducing churn.
About Kate Lovejoy
Kate Lovejoy is the Chief Operating Officer for Retargeting at Adikteev. Kate has spent her career launching both User Acquisition and Retargeting campaigns for mobile game developers such as King, Zynga, and EA. Kate is driven to always seek new ways for app marketers to identify ways to make the most of their customer user experiences.