Predictive upsell offers drive mobile game monetization

Use Case

Upsell Prediction with pLTV, Conversion, and Churn

A social casino game publisher increased ARPU up to 30% by customizing upsell offers based on pLTV, conversion, and churn predictions.

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Industry: Mobile games

Company Size: Top-100 ranked mobile games in over 10 countries, including one with 5M+ installs

Solution: Improve game monetization

Platform Use Case: pLTV, conversion, and churn prediction

+ 11 to 30 %

increase in ARPU for social casino games

Challenge

With its social casino games highly ranked in app stores worldwide, this mobile game publisher had millions of downloads and players. But improved monetization strategies presented still more growth opportunities. 

The game’s monetization team had used business rules to guide promotions and pricing, but they recognized that a predictive approach could be more effective. 

Predictive models can recognize patterns in user and activity data that are more subtle than even a complex set of business rules. Accurate, reliable predictions for each user make it possible to refine offers much more precisely and dynamically.

Solution

This game creator partnered with Pecan to build multiple predictive models to increase two of their social casino games’ average revenue per user (ARPU) through better-targeted upsell offers. 

Pecan’s models predicted the likelihood of churn and of purchases in the coming week among the players who were active in the preceding 7 days.

The combination of these predictions helped the monetization team identify users who were both less likely to churn and more likely to purchase. These promising users were provided with an optimized store experience and enhanced package sizes worth more than their most recent purchase.

Results

Understanding the real impact of this upsell strategy requires careful testing. Pecan and the game studio’s monetization team coordinated on the test design, constructing test and control groups, selecting specific dates to monitor, and establishing the method for presenting the upsell offer to the specific users identified by the predictive models.

Comparing the test and control groups revealed exciting results. The two games used in the test showed significant increases in ARPU among the players who received the upsell offer – 11% in one game and 30% in another.

Using predictive analytics to implement a predictive upsell strategy helped this game publisher significantly increase the value of committed players. This successful approach showcases the potential of predictive analytics to enhance monetization in mobile gaming.

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