Archive for 14 August, 2012
Roger spotted this interesting use of database marketing building on response modelling for gamblers in Analytics Tool Predicts Customer Behavior.
“Seminole Gaming operates seven casinos in Florida on behalf of the Seminole Tribe, and two of these facilities are Hard Rock-branded hotel casinos. The company has more than 11,000 slot machines, 300 table games, dozens of restaurants and nearly 10,000 employees.“
“Our segmentation strategy relied solely on prior behavior, largely using traditional RFS (recency, frequency, spend)-driven segmentations. We needed to be able to “see into the future” when it came to our customers’ behavior …“
While the newer electronic channels are very important marketing tools, in the casino business the more expensive channel of direct mail is much more effective. A predictive response model was used to prioritise prospect selection:
“We identified the 35 percent of our customers most likely to respond to one of these offers. For the 65 percent least likely to respond, we consolidated mailers—advertising multiple concerts, instead of a single concert, in each mailer. While the single-mailer-per-concert approach proved most effective for customers likely to respond, advertising multiple concerts in a single mailer saved mail costs and increased response. This response model was a second success, generating another incremental gain of more than $1 million in profit annually.“
It is interesting to see some of the measures used by casinos explained:
“Traditional casino direct-mail programs rely heavily on metrics such as average daily actual (a measure of how much money a player loses on a given day), average daily theoretical (a measure of how much a player would have lost if he or she had no more or no less luck than expected, per day), average daily worth (a calculation that combines the two metrics above) and points earned (a measure of how much total play a player has given the casino).“