Posted on May 7, 2012 · Posted in Uncategorized

Customer Lifetime Value analysis (CLV) is one of those marketing topics that nearly all marketers talk about but only a few measure. Instead, mass marketers spend extraordinary advertising dollars on acquiring (e.g. Super Bowl ads) rather than retaining existing customers. How much should you invest in acquiring new customers vs. servicing current customers?  How can these be assessed? CLV can help.

First a definition: Arthur Hughes (author of “Strategic Database Marketing” and a frequent DMAW presenter) defines CLV as “the net present value of the profit that you will realize on the average new customer during a given number of years.”

The key variables in calculating CLV are as:

Average customer spending rate: if it goes up, CLV goes up.
Customer retention rate: if it goes up, CLV goes up.
Variable cost (cost to service a customer): if it goes up, CLV goes down.
Acquisition cost (to attract 1 new customer): if it goes up, CLV goes down.
Discount rate: if it goes up, CLV goes down (only slightly).

By far the most controllable variable for a marketer is your retention rate. It turns out it is also the most influential on CLV, which places a greater emphasis on customer service and long-term customer satisfaction, rather than on maximizing short-term sales.  The theory is that loyal, returning customers with strong value sales are better for an organization than many one-time customers with high value sales.

However, a modifying factor, often overlooked in the Customer LV formulation is Risk Factor. As Hughes points out, the CLV of an enterprise is subject to serious risks, including interest rate fluctuation, product obsolescence, and new competitive products. But how can risk be measured?

Risk Adjusted Lifetime Value (RALTV) deals with the problem of unpredictable customer behavior by following the practices of sophisticated investors in stocks, whose prices fluctuate in unforeseen ways. Since customers can be considered a risky asset, this same type of analysis can be applied to a “portfolio” of customers as well. The model is similar to that of investment. Before a firm decides whether to acquire a customer (at a certain acquisition cost), it must first decide whether the addition of the customer will have the desired effect on the riskiness of the portfolio.

If you are familiar with the “beta” formula for the valuation of stock, you may find this approach useful. (If not, you’ll need to continue to trust your gut when you assign a risk factor in your LTV calculations).

Measuring repeat customers is a key component of Customer Lifetime Value that you don’t want to ignore. Contact us for a free copy of our LTV Excel spreadsheet – it might show you dramatic ways to improve your own marketing efforts!  You can then perform “what if” analysis on the variables from your own organization, and calculate your own customer lifetime value!

Contact:; or (703) 941-8109.

Professor's CornerProfessor’s Corner:

Love Me Two Times – Getting That Elusive Second Order
Some years ago I was helping a client analyze their customer buying patterns. We discovered what now seems obvious: customers who ordered a 2nd time were likely to order 3 or more times in the future with a probability of 40%. I was reminded of this during my Database Marketing class at Johns Hopkins, when a student of mine presented a very similar buying pattern from his own experience. Some marketers will say that until a customer buys a 2nd time, they really are not yet your customer: they may be just a “tire kicker” without enduring loyalty. What can you do to find the first time customers who may truly become future loyal customers?

In the case of my own client, we instituted a call back campaign. The very next day after a customer’s first order, the customer was called with incentives to order a 2nd time. This resulted in a dramatic increase in repeat customers – and higher customer lifetime value!

Learn More: “Hedging Customers”, Dhar & Glazer, Harvard Business Review. May, 2003.