Using survival analytics to estimate lifetime value

Abstract

Typically, lifetime value (LTV) is merely a calculation using descriptive/ historical data. This calculation makes some rather heroic assumptions to project into the future but most importantly gives no insights into why a customer is, for example, lower valued, or how to make a customer higher valued. That is, descriptive techniques offer no insights into predicting, incentivising or changing customer behaviour. Using predictive techniques — in this case survival analysis — can give an indication into what causes purchases to happen. This means marketers get insights — levers — into how to increase LTV. This predictive modelling is strategically lucrative. This paper appeared in a different format in Marketing Analytics, Kogan Page, June, 2015.