The Science Behind App Uninstalls Prediction — Part 2/2

In the previous blog, my colleague and Product Manager at Tatvic — Bismayy — talked about compelling app uninstalls stats and also drew insights on an app marketer’s woes. If we do not have means to retarget and bring them back, we lose the customers forever once they uninstall the app. That’s where we touched upon the point that you and I need a magic wand to prevent these customers from uninstalling in the first place.

Machine learning predictions are the magic we are all looking for. Sounds like a challenging implementation task, don’t you think? Well, it is and it is not. At Tatvic, we call it the PredictN Model. Our data science team and implementation team have built this product which accurately predicts the cohort of users who are likely to uninstall. Let’s jump into the how’s and what’s of our PredictN Model.

The PredictN model gets trained based on historical app usage data of users and uninstall library parameters. As more data is collected into app analytics/server, the PredictN model prediction accuracy gets improved.

Once we build & run the predictN model, it will allow us to generate a list of high probable churning users using advanced segment.

Interested in reading further details of how Tatvic’s PredictN model makes this possible?

Read the full blog here by my colleague Jigar to discover how this magic unfolds.

In case of any queries or feedback, please leave a comment in the section below. We’d love to hear from you.

Related Webinar on Preventing App Uninstalls: Register here