New Thinking About Customer Value Metrics, Part I
Before implementing a CRM strategy, one must first evaluate and measure the customer lifetime value (CLV). Arthur O'Connor takes a look at how CLV has decreased in relevancy in the hyper-competitive, fast-changing, global electronic marketplace.
Measuring CLV (customer lifetime value) used to be considered and for many it still is a prerequisite to any investment in CRM (customer relationship management).
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 ROI (return on investment) 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 I of this two-part series, we'll look at how Customer Lifetime Value has decreased in relevancy in the hyper-competitive, fast-changing, global electronic marketplace.
In the second installment, Part II, 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 #1: In this hyper-competitive, ever-changing market, customer lifetime value has become a highly subjective, impractical projection.
In a few product/service categories in which churn rates are historically low and products are 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 develop a reasonable forecast of project 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 projection 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 expectations of customers and the accelerating pace of new product and service offerings (and consequently declining product lifecycles). Add into the mix the upheaval of corporate America in which companies regularly acquire and/or 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 macro-economic 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 lifecycle value is an anachronism. This kind of thinking is a holdover from the industrial age when, in the post WWII demand-starved consumer economy, customer loyalty could be had by the relatively simple tactics of efficient mass production, attractive packaging and clever mass media advertising.
In this world long gone by, it was simply assumed that, let's say, if you were an Oldsmobile buyer, well then, by jiminy, you were an Olds customer for life. [While 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 be shutting down this year. 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 and/or using the most sophisticated data mining applications and multi-dimensional 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. There's simply too much 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 and/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.
Got an opinion on this stuff? Willing to share it? If so, please write me at Arthur.firstname.lastname@example.org.
Arthur O'Connor is one of the nation's leading experts on customer relationship management (CRM) and customer-facing IT systems and strategies. He's currently the national columnist for eCRMGuide.com and this year serves as the chairperson of the Institute for International Research's CRM Conference. Arthur has over 20 years leadership and management experience in the area of customer management, strategy and new business development, including 15 years as a senior corporate officer of two NYSE-listed inter national corporations, and over five years experience as an independent management consultant and Big 5 firm practice manager selling and managing large-scale IT engagements.