Strict Standards: Declaration of JParameter::loadSetupFile() should be compatible with JRegistry::loadSetupFile() in /home/content/94/5783694/html/ on line 512

Warning: Cannot modify header information - headers already sent by (output started at /home/content/94/5783694/html/ in /home/content/94/5783694/html/ on line 107
Identifying most valuable patrons

Thanks For Your Feedback!

Five plus seven is? (answer as number)

Facebook Comments

Click to open/close fB Comments

Identifying most valuable patrons

In addition to developing models to predict future worth, there are other analytical methods to determine a patron’s value to the business. One way to identify the best patrons is to try and separate the skilled gamblers from the unskilled. It is possible to look at whether a patron is usually a loser or winner. A quick and easy way to evaluate a player’s skill is by calculating the percentage of trips where the player actually lost money.

Although slot machines are not really skill based, we can still differentiate between patrons by looking at the strategies and behaviors of slot players. One quick and easy way to separate slot patrons is compare how much play they have on participation machines relative to owned machines. Since casinos have to pay a certain percentage of win or handle to the slot manufacturer for participation games, patrons that primarily play non-participation games are slightly more valuable to the casino. A slightly more complex metric for slot players is to look at their average bet relative to the maximum bet on the games they play. Usually, the maximum bet has to be played in order to be eligible for jackpots and progressives. Given two patrons of similar theoretical worth, the one that plays closer to the maximum allowed bet is more likely to hit a jackpot than the one who doesn’t. Usually the patron with the higher average bet would seem to be more valuable, but since the lower bet patron is less likely to hit a jackpot, the lower bet patron might be a lower risk. This metric could be useful on its own, or could be used as either a predictor in a model for future worth or a decision tree predicting whether a patron will respond. These are just a few examples of how data mining, along with predictive modeling, can provide useful information to differentiate between players that might otherwise seem very similar.