Marketing

• Predicting Lifetime Value (LTV)
  • what for: if you can predict the characteristics of high LTV customers, this supports customer segmentation, identifies upsell opportunties and supports other marketing initiatives
  • usage: can be both an online algorithm and a static report showing the characteristics of high LTV customers
• Wallet share estimation
  • working out the proportion of a customer’s spend in a category accrues to a company allows that company to identify upsell and cross-sell opportunities
  • usage: can be both an online algorithm and a static report showing the characteristics of low wallet share customers
• Churn
  • working out the characteristics of churners allows a company to product adjustments and an online algorithm allows them to reach out to churners
  • usage: can be both an online algorithm and a statistic report showing the characteristics of likely churners
• Customer segmentation
  • If you can understand qualitatively different customer groups, then we can give them different treatments (perhaps even by different groups in the company). Answers questions like: what makes people buy, stop buying etc
  • usage: static report
• Product mix
  • What mix of products offers the lowest churn? eg. Giving a combined policy discount for home + auto = low churn
  • usage: online algorithm and static report
• Cross selling/Recommendation algorithms/
  • Given a customer’s past browsing history, purchase history and other characteristics, what are they likely to want to purchase in the future?
  • usage: online algorithm
• Up selling
  • Given a customer’s characteristics, what is the likelihood that they’ll upgrade in the future?
  • usage: online algorithm and static report
• Channel optimization
  • what is the optimal way to reach a customer with certain characteristics?
  • usage: online algorithm and static report
• Discount targeting
  • What is the probability of inducing the desired behavior with a discount
  • usage: online algorithm and static report
• Reactivation likelihood
  • What is the reactivation likelihood for a given customer
  • usage: online algorithm and static report
• Adwords optimization and ad buying
  • calculating the right price for different keywords/ad slots