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Forecasting Downloads for Gacha Games: A Comparative Study of Predictive Models and User Acquisition Strategies
Tasnim, Beran
Tasnim, Beran
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Abstract
This research aims to provide solutions to help game developers improve the quality of gacha games and increase the number of downloads. In this paper, forecasting techniques were used to predict the number of downloads for Genshin Impact V3.4 and Honkai Impact 3rd V6.6, and measure the forecast accuracy. Additionally, a survey was conducted with 177 participants to identify the most common issues that cause players to quit the games. Overall, this research provides insights into improving the quality of gacha games and increasing their popularity among players. The findings suggest that accurate forecasting and addressing common issues can lead to increased downloads and player retention. The results showed that linear regression was the most accurate method for forecasting future downloads of Genshin Impact V3.4, which are expected to be 3.85 million. The most accurate method for Honkai Impact 3rd was exponential smoothing, with an expected download count of 25.96 thousand. The data and information used in this research were collected from Statista, VG Insights, research articles, and YouTube videos.