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Driving App User Engagement

As the market is maturing, the game is changing (fast) for the entire eco-system. Earlier this decade app developers focused primarily on acquiring vast amounts of users without analyzing in great detail their Lifetime Value (LTV) or calculating the Returns on Advertising Spend (ROAS).

Fast forward couple of years, and we see a completely different, more mature, market where app developers understand and start collaborations only with advertising partners that provide added value, whether that comes through in-house technology stacks, direct supply partnerships or transparency and optimization engines or a combination of these.

This year alone over 200 billion app downloads occurred world-wide, and while that's a staggering number, the overall retention rates and in-app engagement are dropping due to a vast amount of apps available in the Appstores. As a result, app developers are shifting their focus from simple user acquisition (UA) on a Cost-per-Install basis to more sophisticated approach. Post Install Engagements (PIE) of the users are the primary metrics used to analyze the results of the marketing efforts and to determine which channels provide the highest ROAS and thus should receive the most budgets.

To show why analyzing the PIE is so important to manage the ROAS of each marketing channel, I have illustrated below two different scenarios. For the sake of simplicity, we took Retention Rate (RR) as the example driver for measuring ROAS, while in reality other metrics such as registrations, purchases, etc. are equally, if not more important.

What we observe in Scenario 1 is that an app developer has received 940 installs from one media channel with 3 different publishers and the overall RR in Day 30 (combined) is low (7% avarage Day 30 RR) as no timely optimizations have been made.

In Scenario 2, the media partner analyses via an in-house PIE solution the 3 publishers and makes timely (automated) optimizations by blocking incoming inventory in two rounds from publishers that already at the beginning show low performance in RR. By doing so, the media partner delivers lower amounts of installs, however the overall ROAS for the app developer significantly increases with 30% to 10% (from 7% in Scenario 1). With this process in mind, chances are considerably higher that the app developer will take into consideration the media partner next time the marketing budgets are available.

Driving performance to advertising partners motivates Qverse to continuously develop innovative products that bring added value. Our most recent product involves a highly automated Post Install Event system using 2nd party data (from attribution companies such as Adjust, Appsflyer, etc.) is capable to analyze and optimize inventory based on post install engagement performace. 

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