Daily Churn Prediction

The next project gone off I want to talk about is when my group created daily attrition forecasts for a company.

Attrition is when a customer leaves a company. I was charged with producing daily attrition forecasts that had to be within 5% of the actual values over a month. The forecast vs. actual numbers would be feed up to upper management to understand the attrition issues of the company and the effect new company programs were having on attrition.

Because my group had been working at the company for a few years we were able to break the attrition down by line of business, into voluntary and involuntary (when customers don't pay their bills), we were able to build day-of-week factors (more people call to leave the company on a Monday) and system processing factors (delays from the time a person calls to have their service canceled and when the service is actually canceled). Our forecasts performed within 3% of actual attrition. Often we were asked to explain individual day's deviations from predictions which we were always able to do – invariably major deviations were the result of processing issues, such as the person that processed a certain type of attrition taking a vacation and doubling up their processing the next week.

We were able to break down the problem like this because we knew the structure of the information that the company data contained and we were able to build a system that respected that information.

The analysis was a complete success but the project died. Why tommorrow.