Are you satisfied or satiated by the games you play? An empirical study about game play and purchase patterns by genres

Abstract

Abstract This study reveals how users’ play patterns can predict their next purchase after recommending the game. While prior research has recognized what convinces users to choose the games, what has been lacking is considering unique characteristics of video games allowing consumers to experience video games permanently until satiation. Thus, this study examines: (1) How does user play time influence next purchase timing after expressing opinions via the review systems? and (2) How does the relationship between play patterns and re-purchase timing patterns change by game genres? To answer these research questions, we collected data from Valve Corporation’s Steam. Using an R program to crawl the data, we gathered 244,360 reviews from 6,170 games between February 2018 and March 2018. With Cox proportional-hazards models, we found that user play patterns were dependening on their satisfaction with the games. We also found that if a user stops playing, even after recommending a game, they are less likely to buy a new game. Additionally, frustrated players turn to variety-seeking behavior, thus spending time playing other games, and are more likely to buy new games. In the sub-group analysis, we also found that users who recently played a Casual game have the highest probability of buying a new game. Video games are an interesting experience goods due to their unique characteristics; consumers can keep consuming products until they are satiated. However, to our best knowledge, there is a lack of study about satiation’s effect on game consumption. Many researches on video games have examined various topics with many research methodologies, such as descriptive statistics, experiments, survey, observational studies, or network analyses. However, unlike previous studies, we directly collected user play pattern and purchase data from Valve and examined how the behavior of purchasing a new game is related to user play pattern after the recommendation. This is a novel methodology of using data crawling and econometrics modeling to investigate game users’ purchase behavioral patterns with the observational data. So, we believe that our study can benefit marketing managers and game developers, providing critical information regarding target markets and play patterns of potential consumers.