The aim of this project is to Predict Customer Lifetime Value in non-contractual situations in which customers can make purchases at any time.
In most cases value of a firm is profits from existing and future customers, also known as Customer Equity. Research done by Frederick Reichheld shows increasing customer retention rates by 5% increases profits by 25% to 95% (Reichheld 2001).
It is possible to calculate Customer Equity (CE) because Customer Lifetime Value (CLV) can be measured with a reasonable degree of precision. CLV is a prognostication of the net profit contributed to the whole future relationship with a customer. It is a forward-looking concept, not to be confused with historic customer profitability.
In every business it is important to find the most valuable customers. The Pareto Principle says 20% of your customers represent 80% of your sales. So it would be a great opportunity for the company, if we could identify that 20%, not only historically, but in the future as well. CLV can help us to identify these customers.
So not all customers are equally important to a firm. Maintaining long-term relation with all of them is not optimal because eventually marketing is all about attracting and retaining profitable customers (Kotler and Armstrong 1996). Hence the objective of CLV is firstly on general topics of firm’s profitability and secondly as an input in customer acquisition decision and customer acquisition/retention trade-offs (Berger and Nasr 1998).
The primary goal of this work is to build a probabilistic model for forecasting customer lifetime value in non-contractual setting on an individual level.
Using the results of this exercise, managers should be able to:
- Distinguish active customers from inactive customers.
- Generate transaction forecasts for individual customers.
- Predict the purchase volume of the entire customer base.