The AI layer marks the main area in which Stacked distinguishes itself from other solutions in terms of game analysis. Instead of static reports and manual data interpretation, studios receive an AI-based tool that actively examines player activities and uses accumulated experience to make predictions. This way, the raw data is transformed into actionable information without the need for a separate team of data specialists.
The AI-powered game economist enables deep research of player cohorts and understanding of the peculiarities in their interaction with a game economy. Moreover, it helps to discover whether player activity drops, when does it occur, and why. For instance, the software will help to find out that some players start losing interest on days three and seven due to lack of rewards, progression challenges, or unbalance in the economy.
In addition, with Stacked, it is possible to learn what behaviors, loops, and game mechanics drive loyalty in particular player cohorts. The AI analyses all users who manage to stay in the game after day thirty. Developers may use the information to predict what results their attempts at changing something in the game will bring. It is possible to check several hypotheses and prioritize testing the experiments that provide a greater chance of success.
It is worth noting that AI also enables studios to connect specific game mechanics to retention rates and monetization. Thanks to this feature, it is easy to detect which gameplay elements positively affect players' experience and how the economy should be designed to attract and retain users and earn money.