Life Time Value is A Fabulous Concept

... but there are more practical approaches for retailers

By Brian Woolf
February 22, 2015

Customer Life Time Value (CLTV) is the estimated future profit that will be earned from a customer. Its two primary conceptual appeals are that it shows how much extra you can spend ("invest") in a customer before you start losing money on that customer; and it shows the wide disparity in profitability in customers over their shopping lifetime which encourages management to invest extra in building and retaining those customers projected to create the most profits.

Where CLTV Works Well
The best practical use of CLTV is seen where annual transactions are few and relatively standard. Magazine subscriptions, donations for charities and causes, insurance, and telecoms are good examples. Consider the first mentioned: a magazine publisher knows his publication, distribution, and associated costs. He has three key variables to play with: the cost and frequency of soliciting subscriptions, the range of prices (cover price and its discount variations), and the various subscription periods offered. From past experience, he knows the average "ustomer subscription life" and how it varies by subscription source and other factors. From this simplified set of data, he can calculate the CLTV in a variety of combinations and make offers accordingly to optimize his CLTV. He may have found, for example, that readers who also read the Economist have a long subscription life with his magazine so he may position better introductory offers in that magazine.

Where CLTV Doesn't Work So Well
The answer is opposite to that above, ie, where annual transactions are many, involve many different items, and customer frequency and spending is volatile throughout the year. Food retailers are a great example. Consider a typical US food retailer with 10,000-20,000 unique customers per store, offering a range of 30,000-100,000 items. Imagine calculating the LTV for each customer and then making offers ("investments") to optimize their LTV figure. Making such a comprehensive CLTV proposal to a retail CEO would probably trigger a fairly quick exit from his or her office.

On The Other Hand...
If we consider the intent of CLTV, then optimizing customer profitability by focusing on the retention and addition of profitable customers would be in harmony with the concept but without requiring CLTV's theoretical accuracy and huge data processing requirements. Here's one approach to accomplish that objective.

Customer Optimization
Consider this store profile, drawn from a composite of food retailers' quarterly data.

Segment	Avg Spend Per Week	Attrition Rate (YTY)
Diamonds                 Rubies                 Opals                 Pearls	> $100                 $50 - $100                 $25 - $50                 < $25	2%                 4%                 8%                 50%
Existing                 New		36%                 67%
Total Cust		43%

From a CEO's perspective, it's easy to see which customer segment provides the greatest CLTV. The highest spending customers (Diamonds) spend the most (over $100 week) and the company retains 98% of them. Conversely, the Pearls, the lowest average weekly spending (under $25 week) segment, retains only 50% of its customers year-on-year. And the biggest challenge of all is the difficulty in holding onto new customers; only a third are still buying a year later while two-thirds have come and gone.

Among the existing customer categories, the Gross Profit% and Operating Costs% do differ, but not dramatically, as customers buy from the same range of merchandise with the same prices and are processed through the same checkouts.
Looking at the table above, the question is how to best optimize overall customer (ie, company) profitability? How should resources among the customer segments be reallocated to increase profits?

Before proceeding on this quest, understand that attrition rates are the percentages of customers in each segment this quarter last year that didn't buy anything in the same quarter this year. Retained customers are, by definition, still shopping with us but are not necessarily in the same spending segment as last year: they may have increased or decreased their spending. (Such customer movement management sees in a separate report.)

Obviously, it makes intuitive sense to increase the number of Diamonds and Rubies. We want to hold them at their existing spending levels, and higher. But a number will have dropped their average weekly spending for reasons that may be internal (eg, poor quality or service) or external (family changes, new competitors). This is where grounded testing steps in. For example:

• Will we spend resources finding out why the spending of high spending customers has dropped?
• Will we identify the larger decliners and make offers with the intent of them regaining their previous spending levels?
• Should we, to show our appreciation for their business (and to minimize any inclination for them to split their shopping with competitors) create special offers, privileges, or surprises for them?
• Should each store randomly call five such customers who shopped the previous week and seek their feedback on their experience along with any other comments?

Questions, with a similar mindset, could be asked of each segment. All, no doubt will be worthy. The decision to be made is which questions will lead to actions that will yield the best returns. To assist in the economics in making that decision, it would make sense to charge club card costs (special rewards, price discounts, discounts to events, free turkeys, etc) to their respective segments which are, of course, a broad-based proxy for the large numbers of individual customers with different CLTVs.

The process is a matter of trial and success as the lessons are absorbed and applied. For food retailers, it is less theoretical than what the proponents of CLTV suggest but it is pragmatic, practical ... and productive.

The Bottom Line
Sensible approximation is sometimes preferred to exquisite exactitude, even when the concept is a fabulous one.

About the author...

The techniques and metrics Brian Woolf has developed have become guiding principles for those operating some of the world's most successful programs. He is the President of the Retail Strategy Center, and has consulted, and spoken at conferences, in the US, Europe, Japan, and Australasia.

Prior to his total commitment to loyalty marketing, his corporate roles included Deputy Managing Director of Progressive Enterprises, a major New Zealand retailer; and Chief Financial Officer of Food Lion, a leading US food retailer. He has an M.Com. (Economics) from the University of Auckland, New Zealand, and an MBA from the Harvard Business School.