How to Define “Customer Equity” - The Right Way, Not the Wrong Way

Originally published by Don Peppers on LinkedIn: How to Define “Customer Equity” - The Right Way, Not the Wrong Way

For the last three weeks I’ve been in Hong Kong and Australia for a number of meetings and presentations (returning to the U.S. tomorrow). Several times in my conversations with business executives, the subject of “customer equity” has come up. Usually, it happens when an somebody asks how they should think about the value to their business of being customer-centric, or how they should quantify the financial value of delivering a better customer experience.

One or two executives have mentioned the idea of “customer equity” as something that might be useful in answering these questions, and they’re correct, but first we have to agree on the correct definition of customer equity.

This may be a term you last heard in your university marketing class, but customer equity is actually a genuine economic quantity, and it does have a precise definition.

A business’s customer equity is:

This second element of value in the definition of customer equity – the lifetime values of a company’s future customers – is critical, but unfortunately this part is often overlooked or omitted in books and articles by authors who really ought to know better (for instance, Peter Fader’s otherwise excellent book Customer Centricity, as well as the Wikipedia entry for “customer equity”). Before discussing the problem caused by this omission, however, let’s first define “lifetime value,” or LTV.

A customer’s lifetime value is:

From this definition, it should be obvious that LTV requires predicting the future, and since no one can truly know what the future holds, this means that both LTV and customer equity are probabilistic numbers.

However, with increasingly sophisticated analytics, and especially for a data-rich or subscription-oriented business (such as a credit card, for instance, or a mobile phone carrier, or maybe a grocer), it isn’t all that difficult to make a reasonable estimate with respect to how much a statistically typical customer will spend with the business, and how long the customer is likely to remain a customer, on average.

When economists try to define the enterprise value of an operating company, they also rely on this kind of formula, trying to forecast and then calculate the net present value of the enterprise’s future cash flow. And when the stock price goes up or down on a publicly traded company, it is because the investors that are buying or selling that stock have different expectations for the company’s future cash flow.

Nor do these calculations have to be precise in order to be useful. Fischer Black, one of the creators of the famous Black-Scholes equation for valuing stock options, once wrote that he would consider a stock market to be “efficient” if a firm’s stock price was always between 50% and 200% of its true economic value (i.e., the net present value of its future cash flow). This is a pretty wide margin of error, but given the fact that no one can really know what the future holds in store, it’s not a bad guide.

And it might not be a bad guide for evaluating customer lifetime values, either. We often write about LTVs as if they could be calculated precisely, but the pure randomness of any single customer’s future behavior, as seen from today’s perspective, means that the only way a business can actually “calculate” LTV is by applying statistical techniques to a large population of customers and inferring their likely future behaviors from their known historical patterns and other indications. As with stock markets, if your estimate of an individual LTV is no more than 50% less than or 100% more than actual, perhaps we should count it as accurate enough.

Because virtually all of the cash flow generated by a business’s operations comes from customers, if you sum up the lifetime values of its customers, the economic value you are calculating should be equal to the firm’s enterprise value, right?

WRONG. If you only look at the customers that a business already has, you’ll be missing a big part of the equation. Every business has a constant “flow” of incoming and outgoing customers. When we estimate a customer’s LTV, we’re explicitly incorporating the estimated time the customer is likely to spend with a business before leaving, so we’re already taking into account the outflow of customers from the customer base. But what about the inflow? If we don’t include the cash that will be generated in the future by new customers – customers a business doesn’t yet even have – then we aren't really making an accurate calculation at all.

You could think about it this way: A high-growth company will almost always have a higher stock market valuation than a low-growth or no-growth company that is the same size today. This is because the market expects much higher cash flows for the high-growth company in the future, as it rapidly acquires more customers.

Or think about it this way: Suppose two companies each have a million customers, and generate the same amount of cash flow. But Company A has also identified a million prospective customers, while Company B has no prospective customers at all. Which company is more valuable today?

The point is, if we want customer equity to approximate the actual enterprise value of a firm (and we do!), then the true definition of customer equity must always include not just a business’s current customers, but its future customers, as well.

Alright, but why is it so important to agree on the precise definition of customer equity in the first place? Because this is the quantifiable financial asset that will increase in value when you improve your customer experience. And the amount of increase you generate should translate directly into shareholder value.