Mobile User Acquisition In A Post-IDFA World: Everything You Need To Know

Mapendo Team
May 30, 2022
Mobile User Acquisition In A Post-IDFA World: Everything You Need To Know

is by developing the best mobile UA strategies. Better than your competitors, and powerful enough to thrive in this dynamic market.

In this post-IDFA world, with user privacy at the heart of priorities, this is more true than ever. Take a look as we explore why you need to focus on optimizing your mobile user acquisition with machine learning in this privacy-centric era.

Why Machine Based Learning Is Crucial Post-IDFA

It’s old news now that millions of users have opted out of IDFA sharing, meaning advertisers’ abilities to identify high quality users is severely impacted. So what now? Without Apple’s identifier, mobile marketers need a new way to target, optimize, and attribute campaign performance to the individual. And this calls for machine learning.

What is machine learning?

In a post-IDFA world where tracking users and gathering personal data is getting harder, companies need to rely on machine learning and AI to improve their mobile user acquisition. When advertisers rely on machine learning, they know that the algorithm they are using is considering all the information it has to suggest the best possible decisions. As time goes on, an algorithm is capable of gathering and processing more information to drive the advertisers actions and target the right audience.

Here at Mapendo, Jenga, our proprietary AI powered CPA optimizer, helps to understand trends, user behaviors and journeys in a way that is respectful to the user. Jenga collects tens of thousands of data, finds patterns, macro-trends and insights, and on the basis of the data gathered, it manages to predict the possible outcome of a mobile user acquisition campaign and finds the audience that is most likely to convert.

SKAdNetwork Helps You Thrive In A Privacy Centric World

How to give users personalized experiences in a privacy centric world?

In this post-IDFA era, there is a catch 22; on the one hand, users have concerns about the way data is collected and stored, on the other hand, they want personalized experiences. They want the best of both worlds: benefiting from targeted ads and no identity exposure. So how can we give this to them?

Well this is where SKAdNetwork comes into play. SKAN (StoreKit Ad Network) is a privacy-centric API operated by Apple which helps ad networks and advertisers measure their ad activity, like clicks, impressions and app installs, on an aggregated level. It provides deterministic mobile attribution results when users opt out of ATT and hide their IDFA, in the case of paid app-to-app campaigns. Simply put, according to Apple there is no other way to attribute conversions with app install campaigns other than by using SKAdNetwork.


Digital advertising was and still is heavily based on tracking, data collection and optimisation. While this post-IDFA era certainly brought with it some challenges, applying machine learning and SKAdnetwork will help you overcome these constraints and focus on optimizing your mobile user acquisition strategy in a way that protects user privacy.

Mapendo is a performance DSP for app install campaigns you can rely on to grow your mobile app.