Going out of business: Auction house behavior in the Massively Multi-player Online Game Glitch

• Player profiling across 5 KPIs and their evolution as a function of time.
• Economic analysis of trading from 20,000 players, 650 products across 14 months.
• Analysis of player trading behavior in the online game Glitch from launch to death.
• Interactive visualization facilitating interaction with high-dimensional progression data.
• Hardcore auction house users were more likely to keep playing Glitch than casual users.

The in-game economies of Massively Multi-player Online Games are complex systems that have to be carefully designed and managed. This paper presents the results of an analysis of auction house data from the Massively Multi-player Online Games Glitch, across a 14 month period, the entire lifetime of the game. The data comprise almost 3 million data points, covering over 20,000 unique players and more than 650 products. Furthermore, an interactive visualization, based on Sankey flow diagrams, is presented which shows the proportion of the different clusters across each time bin, as well as the flow of players between clusters. The diagram allows evaluation of migration of players between clusters as a function of time, as well as a churn analysis. The presented work provides a template analysis and visualization model for progression-based or temporal-based analysis of player behavior broadly applicable to digital games.