• A mid-sized casino the mid-west was experiencing poor repeat visits of first time visitors coupled with increased churn of their repeat customers


  • 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


  • First time Visitors’ retrial increased by 20%
  • Reduced customer churn by 15%
  • The above two aspects contribute to $750K/year in incremental revenue