Adam
Dandi
ADAMS PROJECT

Performance Optimization and Monetization Strategy for Serenity’s Spa Mobile Game

Completion

December 14, 2024

Overview

This project analyzed the performance of Serenity's Spa mobile game, identifying key areas for improving player engagement, retention, and revenue. Through data analysis of player progress, in-game purchases, and user behavior, this project provided actionable insights and recommendations aimed at enhancing game features and optimizing monetization strategies.
Data Details
The objective was to understand the causes of low player retention and weak monetization in Serenity’s Spa. The analysis focused on levels that slowed player progress and on new features such as the leaderboard that showed low engagement and revenue. The data came from the mobile game and included level progression, in app purchases, and leaderboard activity. The dataset contained 120 records covering levels, user interactions, and purchases, with key variables such as level and sub level, completion and churn rates, average attempts and booster usage, daily active users, and revenue metrics including IAP and ARPDAU.
The Problem
Several levels show low completion rates and high churn, mainly due to steep difficulty curves and heavy booster requirements. The leaderboard feature increased DAU and total revenue, but ARPDAU declined slightly, showing limited impact on individual spending. An AB pricing test delivered an 8.4% increase in total revenue and higher ARPU, confirming that lower prices improved conversion. Key actions include redesigning difficult levels, improving player guidance, increasing leaderboard visibility with rewards, and running longer AB tests with more detailed pricing and bundle options.
The Solution
Level Funnel Analysis: A detailed examination of completion rates and drop-off points at various levels to identify problematic levels. Leaderboard Feature Evaluation: An analysis of the impact of the newly launched leaderboard on DAU, revenue, and player engagement. AB Test Evaluation: A statistical analysis of a pricing test for in-app purchases to assess its effect on conversion rates and overall revenue.
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