How can we predict the effect an investment in loyalty will have on the future of the business? While no method can ever be perfect, measuring loyalty's effect on Customer Lifetime Value (CLV) is one of the best - and most accurate - ways, particularly if the management wants to maximise customer profitability during the whole of each customer's life cycle with the company. This article is copyright 2017 The Best Customer Guide.

CLV is increasingly being recognised as one of the most important measures of the worth of a customer. It takes into account not only the customer's value now but the expected value over their projected lifetime as a customer.

In fact, it is quite sobering to see how big the CLV can be. It is particularly important in high ticket value, low frequency businesses (motor sales or insurance, for example). The costs of setting up an account and establishing the customer are offset over many years so, in terms of profitability, the customer becomes annually more valuable as time passes.

Turning data into profit
The increased interest that managers have shown over the past decade or so in CRM, customer databases, data warehouses, and data mining is a positive development. Having such a system in place provides essential data that can be analysed to provide better business intelligence and decision-making support.

There are many business models that can be used to get an overall picture of the kind of relationships and correlations that form the basis of CLV calculations, and the effectiveness of investments in customer loyalty, profitability, and CLV will differ depending on various factors:

  1. The sector
    When comparing data, or conclusions based on its analysis, it is necessary to define the market sector, the type of company, the market segment and the company strategy, etc. Research shows that in different market sectors there are different correlation curves between, say, customer satisfaction and loyalty, or between customer satisfaction and profitability. Furthermore, the drivers of loyalty will be different - as will the drivers of profitability. For example, the correlation curve (satisfaction vs. loyalty) in a stable monopoly market will differ significantly from the correlation curve for a turbulent market with fierce competition.
  2. The product
    The correlation curve for a short term tangible product will differ significantly from the correlation curve for a long-term service product. Clearly, this means that the expected outcome of investment in increased satisfaction will yield different results depending on the market sector.
  3. The period of analysis
    The future period on which the analysis is based also has to be defined: results for CLV will differ depending on the projected length of time into the future or past (e.g. 3 years, 5 years, 10 years, etc.)

Building your own CLV model
Many different ways of measuring and calculating CLV have been developed, to suit different trading situations and purposes. While the values calculated can only be a guide to real future value, using the same formula over many customers does at least give a fairly accurate idea of the comparative value of different customers, or groups of customers. The calculation and use of CLV should be an essential part of every business if maximising future profit is the objective.