Background A mid-sized casino the mid-west was experiencing poor repeat visits of first time visitors coupled with increased churn of their repeat customers Approach Score all new guests following their first visit - What is their likelihood of returning 2+ times within 12 months and spending at least $100? Each new customer has a scores of their likelihood to repeat visits Developed another model to score customer churn probability Each repeat customer has churn probability score Developed both models based on logistic regression Used model drivers to recommend media, offer and creative Results First time Visitors’ retrial increased by 20% Reduced customer churn by 15% The above two aspects contribute to $750K/year in incremental revenue
