As the mobile app ecosystem continues to grow rapidly, user base expansion is the apparent key to short-term success. For many app developers, the initial goal is to acquire as many users as possible in order to climb up the Apple’s iTune’s or Google Play’s top charts. The idea is that being more visible in the app stores will result in organic lift.
However, there are many users who often install an app only to uninstall it after the first open. Some never even open it again. For freemium apps, these types of users do not help with generating revenue since they will never make any in-app purchases. The active users who frequently open and engage with the app are the ones who are more likely to make in-app purchases. Thus, for app developers to drive stronger return on investment (ROI), acquiring high quality user is the key to a long-term success.
Who Are High Quality Users?
Before going into how to target and acquire high quality users, let’s take a step back. Who are high quality users? They continually visit the app, actively engage with the app, and make in-app purchases. To put it shortly, they are the one that brings in the revenue and drive the return on mobile app investment.
How Do You Find Them?
So, how do app marketers know users’ quality and who they should target particularly? The answer is through the use of big data analytics and user modeling. App marketers can leverage historical user behavior and information to develop a dynamic user model. This will allow app marketer to gain insights into user behavior and what are the key action drivers of high quality users. This user model will also help in targeting lookalike audiences who are most likely to also engage in the app continually and spend money in the app.
How Do You Optimize For Them?
To acquire high quality users, app marketers can leverage the dynamic user model to optimize both creative and media aspects of the ad. Using insights such as key action drivers for post-install engagement metrics such as retention, booking, in-app purchases, app marketers can determine what kind of creatives should be developed and through what media the ad should be published. To take the ad to the next level, app marketers can also use machine learning algorithms to identify the best creative variants and media placement based on prior knowledge and dynamic occurrences.
By unifying the optimization of both creative and media for active users who are most likely to spend money in the app, app marketers can see stronger ROI, especially in the long term. To learn more about how Aarki can leverage our big data architecture and machine learning technologies to help you, please contact us at email@example.com.