AB Testing for Mobile Games: Using Machine Learning

The purpose of this research is to identify the impact of the change of the game level design in a mobile game on players’ retention by applying the AB test. The goal is to compare the effectiveness of a game “gate” located at level 30 and level 40 to determine the consequences of the relocation in regards to player’s engagement.

Our methodology involves:

  1. Data Collection: Collecting information concerning the players’ retention at different levels of the game.
  2. Data Analysis: Evaluating game statistics, specifically players, concerning their decisions to remain with the game or not.
  3. AB Testing: Overhauling an AB test regarding the player retention rate of two groups: one of which has the game’s gate at level 30, and the other at level 40.
  4. Bootstrap Analysis: Performing bootstrap analysis to statistically distinguish between the two groups’ retention rates.

Apparently, moving the gate would unveil that putting the gate on level 40 results in the minimization of the 1-DAY and 7-DAY retention rates. This discovery means that when the gate is introduced at an earlier stage of the game, it helps in maintaining the players’ interest by breaking the continuity of the game which may cause boredom. These observations can help game designers to understand how to allocate the layout of the game level in a manner that would encourage players’ participation and sustain their interest significantly.

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