3 Paid User Acquisition Challenges (And How You Can Solve Them)

Mapendo Team
May 30, 2022
3 Paid User Acquisition Challenges (And How You Can Solve Them)

App development is a time-consuming process, and with so many developers around the world competition is fierce. In fact, it is estimated that there are over 6,000 apps added to the app store every day! This insane statistic makes it no surprise that mobile user acquisition is becoming increasingly more challenging.

Mobile user acquisition is simply the act of gaining new users for an app. Naturally, the goal is to design a UA strategy that generates installs. This is usually achieved by advertising campaigns and promotional offers, either organically or non-organically, i.e paid user acquisition.

Paid User Acquisition is simply a set of non-organic activities, performed by apps, with the goal of acquiring new users.

In this article, we will look at the key challenges marketers face in the realm of paid user acquisition, and identify the key UA strategies that will help to mitigate these risks.

Mobile Attribution Challenges for Paid User Acquisition

You probably already know that the iOS14.5 update changed the advertising landscape as we know it. The privacy-driven changes were of course welcomed, as respecting consumer privacy is what we value most here at Mapendo. However, it meant that users' IDFA, aka their unique identifier, was no longer available when they opted out of app tracking, something that was a key aspect of the deterministic model. This meant a reassessment of UA strategy.

What followed was the switch from deterministic attribution to probabilistic. This change to the mobile attribution model was life-changing. This was a switch from acquiring data that was determined, to relying on more probabilistic methods. This changed the way marketers now generate app user acquisition through mobile attribution, with the main differences being that:

  1. Post-install events are harder to measure: it is harder for marketers to understand how the users behave within the app, making it difficult to calculate a crucial metric such as LTV
  2. Not all apps and websites support SKAdNetwork (Apple’s privacy-friendly way to attribute impressions and clicks) : some apps need to make changes in the source code to support SKAdNetwork.
  3. Post-back delays: Campaign Results come with a 24–48 hours delay. This is how long it takes for Apple to ‘clean’ the data and the delay makes real-time optimization harder to carry out.

Machine Learning is the Solution

There is however a solution to these hurdles, and it comes by applying machine learning to your paid user acquisition. In the iOS 14 reality, with limited data available, machine learning can give marketers a complete view of how their efforts in their paid UA are performing.

Probabilistic modeling at Mapendo leverages machine learning to measure campaign performance without compromising privacy. We work side to side with Jenga, our proprietary technology to deliver meaningful results for our clients.

What our A.I. does in three steps:

  1. It collects hundreds of thousands of data during the programmatic media buying process.
  2. It analyses everything, and finds patterns, macro-trends and insights.
  3. On the basis of the data gathered, it manages to predict the possible outcome of a marketing campaign and finds the audience that is most likely to convert.

The tricky business of high-quality users

When advertising your app, you want to entice the users who are genuinely interested and will have a long lasting engagement with your app, i.e LTV (lifetime value users). However if you are failing to optimize your UA strategy, these true fans will be few and far between.

Let the results speak for themselves. It is the most efficient means to spend your money because the return on investment from lifetime users is so high. By bringing high quality traffic to apps, we optimize the budget and the user acquisition strategy by driving only users that are likely to perform an action and generate in-app revenues.

Acquiring High-quality users

Challenges: In the mobile app ecosystem, especially for gaming, the percentage can shrink: 10% of the players can be responsible for 65% of the revenue, according to a study by SWRVE. If you do not have a UA strategy, finding users with a high retention rate is like finding a needle in a haystack.

Solutions: The key to acquiring these high-value consumers is to monitor the post-install events or in-app events which can generate revenues — in this way you can analyze who the high quality users are and adjust your UA strategy to target them specifically.

We do it with Artificial Intelligence and machine learning. Our proprietary technology is called Jenga, an A.I. that collects data, finds trends, patterns and user behaviors.

By gathering data anonymously, we learn who are the users that are more likely to convert once they download an app and we leverage that to drive conversions and help our clients find true fans.

However, attracting your high quality user is just the first hurdle of your UA strategy. Keeping them is a whole different ballgame, one which requires a whole other set of UA strategies.

Keeping High-quality users

A recent study by AppsFlyer shows that 50% of apps are uninstalled within the first 30 days. App retention is one of the most important factors of a UA strategy and this is why you need to budget your paid user acquisition well so as to avoid being on the losing end of this statistic.

“In a time where competition is rising, it is important to ensure marketing budgets do not go to waste. App marketers should measure their uninstall rate and understand when, why and from which source uninstallers came from.- Ronen Mense, President and Managing Director, AppsFlyer APAC

Run ROAS-positive user acquisition campaigns

The challenge that exists with running a ROAS positive paid acquisition campaign is ensuring you are investing your budget in the right place. You do not want to invest carelessly, as we said before it is a very precise UA strategy to target the right users.

ROAS stands for Return on Ad Spend and it is a metric used to measure the success of an app:

ROAS = (Revenues from ad source)/(Cost of ad)

(believed to be good as long as it is positive).

3 effective metrics that can be taken to solve these challenges:

  1. Acquire High-Quality Users
  2. Create Engaging And Targeted Ads:
  3. Select Different Geos:

These help to run ROAS positive paid UA campaigns because they locate high retention users, spend money on relevant ads only and avoid wasting money on the geos that don’t generate revenues.