KDD cup 2009: Fast Scoring on Large Databases

This challenge uses important marketing problems to benchmark classification methods in a setting typical of large-scale industrial applications. Three large databases made available by the French Telecom company, Orange, were used, each with tens of thousands of examples and variables. These data are unique in that they have both a large number of examples and a large number of variables, making the problem particularly challenging to many state-of-the-art machine learning algorithms. The problems used to illustrate this technical difficulty were the marketing problems of churn, appetency and up-selling. Churn is the propensity of customers to switch between service providers, appetency is the propensity of customers to buy a service, and up-selling is the success in selling additional good or services to make a sale more profitable. The challenge participants were given customer records and their goal was to predict whether a customer will switch provider (churn), buy the main service (appetency) and buy additional extras (up-selling), hence solving simultaneously three 2-class classification problems. Large prizes were donated by Orange (10000 Euros) to encourage participation. Winners were designated for gold, silver and bronze prizes, sharing the total amount.