In a multi-room, multi-game environment what are all your players doing right now?  With 500,000+ players, in multi-room, multi-game environments spread across the globe…   The challenge is to intervene with individual players to reduce churn and improve conversion.  Creating a “player journey” to track each player and identify the most appropriate intervention points in real-time.


Using a mixture of data relationship discovery, data analysis, pattern recognition, algorithms and machine learning are the starting point for fraXses.  Automatically creating the metadata from the live feeds to enable fraXses to know both what and where the data is, thus allowing the system to federate data in real-time.  Then by deploying the fraXses decision making engine on the live data streams,  it enables the analysis and actions to be completed before the data was written to a data store.  This ensures that the operators are able to trigger intervention and create alerts at precisely the right moment.  The fathom module allows rules to be built and tested in a sand box before being deployed, while the impact of bespoke algorithms can also be tested and refined.


By understanding what each individual player is doing at any moment and comparing this with past behaviour, spending patterns, game preferences, previous responses to marketing intervention in real-time, it is possible to identify the most appropriate action to be taken at the most opportune time.  By tailoring the incentive to the player it is possible to maximise the players engagement and satisfaction. The resulting increase in conversion and reduction in churn was measured within days of fraXses being deployed.