With today’s technology, casino slot and marketing systems generate thousands of data points almost every minute. However, the two panelists at a TribalNet seminar, “Slot Data Performance,” urged vendors to give us even more slot and player data, not less.
They also said that we need better methods to understand what it all means.
Richard Rader, CIO of Seven Feathers Casino, and Brian Montano, vice president of operations for Certus Technologies, agreed that there are three key components in the lifecycle of data: reporting, analysis, and analytics.
Most importantly, they argued that all our analytics need to be actionable.
Massive reports with multiple rows and columns of data can be impressive, but at the same time almost impossible to understand in any meaningful way. They noted that recent improvements with dashboards and data visualizations have dramatically improved the accessibility of information on what’s occurring on casino floors. But there’s plenty of room for more.
Rader asked, “Why did a player move from being a $5 player to a $500 player? Was it because he just won a $499 jackpot? Or did something else change?” He continued, “How does a player’s behavior change when winning or losing? How do bonuses impact play? What impact does volatility have on players?”
Analytics and analysis, he insisted, could answer countless valuable questions such as those.
Montano showed a slide noting that the current version of SAS (the slot-accounting protocol used by almost all slot machines) provides data from 168 individual meters on each slot machine. However, he said that most reporting systems and analytical software utilize only 19 of them. The rest are ignored or discarded.
However, handling all data from so many meters can present problems.
Montano cautioned, “Without automation and consistent data, analysts can spend as much as 80% of their time gathering data from various sources and doing data hygiene to develop benchmarks.”
Both men argued this process needs to be handled by software and presented to operators with good dashboard visualizations versus text reports. They also noted, “Hundreds of canned reports presenting raw data don’t combine it intuitively for actionable analytics.”
They compared current analytical efforts with those of Amazon, Google, and Facebook. They commented that popular online-shopping programs track your likes and dislikes, examining your browser history, then offer products you’re most likely to buy in the future. Rader said casinos should strive to do the same.
“With more data, we can learn player preferences, track anonymous players, and determine true player value.”
In one example that resonated with all operators he asked, “Who plays my participation and fee-based games? Can I find games they also like so we can reduce our participation fees?”
Both presenters had mixed views about predictive analytics. They cited an effort by British Railways where the predicted future data was extremely successful in accurately forecasting future passenger demand. The system was used to efficiently schedule trains, staff, and fares. However, Rader related early efforts in predicting returns on casino-marketing promotions that didn’t reflect what had really happened. While they were excited about this future technology, they cautioned that results need to be verified before adopting and trusting these new technologies too quickly.
They concluded their presentation by urging the audience to ask questions of their vendors and demand that they supply more of the available data – and especially make it meaningful and actionable.
