Game user behavior analysis method and computer readable storage medium

Abstract

The invention provides a user behavior analysis method and a computer readable storage medium. The method comprises the following steps that a neural network model including a cyclic neural network model and an attention model is trained by using user behavior data samples so as to acquire the corresponding weight value of each motor of different behavior types of users, wherein the user behaviordata samples include the motion sequences of different behavior types of users. The objective reasons of loss of the user or the behavior of no paying and other behaviors caused by the game can be analyzed in a short period of time by acquiring the weight relation between the motion sequences of the user in the game and the loss of the user and user payment, and the game content can be improved ina targeted way through the result obtained by analysis so that loss of the user can be reduced and even the user can be attracted back to the game.

Description

technical field [0001] The present invention relates to the technical field of game data analysis, in particular to a game user behavior analysis method and a computer-readable storage medium. Background technique [0002] Generally speaking, some online games often lose some players due to various reasons, that is, users no longer play the game. If a large number of players are lost, it will seriously affect the revenue of the game company. Therefore, how to reduce or even avoid the loss of players is an important issue that plagues game companies. At the same time, some games will have paid items. How to improve the paid items, how to attract players to pay for the paid items, and how to make paying users deepen their payment are issues of great interest to game companies. At present, most game companies analyze player loss status and player payment behavior through manual operation and planning. Usually, operations and planning are mainly based on a series of objective ...

AI Technical Summary

Problems solved by technology

Usually, operations and planning are mainly based on a series of objective factors such as player churn indicators, player payment levels, and activities on the game day to analyze player churn status and player payment behavior. By analyzing these objective factors, only objective influence on players can be obtained. Reasons for Churn and Player Payments

The reasons found through these methods do not aim at improving the game itself, will not improve the quality of the game itself, and have not found the root cause that affects player loss and player payment behavior

Moreover, the workload of manually analyzing player behavior is very large, which will generate high human capital and low efficiency

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