New Thinking About Customer Value Metrics, Part 1

Measuring customer lifetime value (CLV) used to be considered — and for many it still is — a prerequisite to any investment in customer relationship management (CRM).

After all, without first measuring the potential value streams, how could one justify an investment in purchasing the software and hardware and engaging the professional and technical services to implement and integrate a CRM system? Without a specific financial measure of the amount and timing of the expected economic benefic, how could one develop the required return on investment (ROI) analysis for the feasibility study?

Over the past years, three important developments have emerged that have changed this line of thinking. And in my own not-so-humble opinion, they have changed the thinking about CLV and CRM for the better.

In Part 1 of this two-part series, we’ll look at how CLV has decreased in relevancy in the hyper-competitive, fast-changing, global electronic marketplace.

In Part 2, we’ll examine how changing attitudes and new reporting requirements have created a new category of metrics that could replace, or at least supplant, CLV as a benchmark for measuring customer value.

Development No. 1: In this hyper-competitive, ever-changing market, CLV has become a highly subjective, impractical projection.

In a few product/service categories with historically low churn rates and products typically held to term (such as whole life insurance), it may be possible to assume that at least some percentage of customers will be lifetime customers. Thus, in this rather unusual product space, it may be possible to reasonably forecast revenues, relative to projected costs, for the lifetime of a customer or market segment.

But for the majority of product and service types, calculating CLV — which requires a forecast for both future revenue and cost for the lifetime of a given customer — represents too much of a “blue sky” projection to be used as a valid investment metric.

Why? Because of today’s ever-rising customer expectations and the accelerating pace of new product and service offerings (and consequently declining product life cycles). Add into the mix the upheaval of corporate America in which companies regularly acquire and divest operations — literally jumping in and out of product areas and industries — and the attendant increased mobility of consumers in switching jobs, moving, and changing lifestyles. All of these power macroeconomic trends render the concept of computing customer lifetime value less and less valid — possibly, even to the point of being ridiculous.

In fact, it seems as if the concept of customer life-cycle value is an anachronism. This kind of thinking is a holdover from the post-WWII demand-starved consumer economy, in which customer loyalty could be had relatively simply with efficient mass production, attractive packaging, and clever mass media advertising.

In this world long gone by, it was simply assumed that, for example, if you were an Oldsmobile buyer, well then, by jiminy, you were an Olds customer for life. (Though one could make a strong argument that if Oldsmobile had really taken this concept to heart — using the implicit future revenue stream to invest more time and energy into designing and producing cars that better met the changing tastes and needs of their customers — the company wouldn’t have shut down. But the point is that these Wonder Years are just that — ancient history.)

Even if a company were to develop deep and rich knowledge of its customers’ unique personalities and buying behaviors — either through religiously cataloging these traits and attitudes through personal interaction or using the most sophisticated data mining applications and multidimensional customer data warehouses — attaining customer knowledge doesn’t necessarily translate into achieving customer loyalty. You can’t (or at least shouldn’t) presume that you’ll be able to successfully capitalize upon all these insights, relative to your competition. Simply too much is going on in the marketplace.

Thus, for most businesses and organizations, CLV is too damned difficult to accurately predict. It is best used as a means to measure the relative value of customers and customer segments, often based on current or short-term income streams and cost bases.

In next week’s column, we’ll look at two other factors driving the new thinking about customer value metrics.

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