The net present value or lifetime value of a customer is calculated by adding predicted future cashflows combined with a risk factor unique to each industry, with the cost of acquisition of that customer, over a specified time n.

Due to the complexity of determining an NPV for each individual customer, and the difficulty of predicting future behavioural changes, NTF recommends that the methodology be applied to groups of like customers. This involves very sophisticated analytic techniques that yield sufficient precision to achieve the appropriate business outcome.

The diagram below shows an example of clusters, or groups of like customers, their current value, and how that value is expected to change over time.

Finance Industry Example

In this example, cluster number 34 is most attractive as not only is total current interest income high, but this annual interest income is increasing at a great rate and hence net present value is maximised.

The next steps in this analysis are to look at the differentiating characteristics of this cluster ie. Age, gender, income, the total number of customers of this type in the market, their total value over time and our current share of that value.

We would also be able to determine what product line was driving the change in interest income over time and hence what products to target the customer segment with.

The inputs required to drive this analysis are historical data on customer buying behaviour, and survey data to determine future potential buying behaviour. The outputs of the analysis are potentially:

• Prediction of customer defection potential
• Prediction of future behaviour and profitability
• Understanding of customer preference structure
• Robust basis for strategic resource allocation
• Decision making infrastructure to support differential customer management