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Estimate customer lifetime value using campaign results

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Customer Lifetime Value (CLV) became a joke during the Internet boom.
When managing their campaigns, Web marketers were advised to consider the potential value of a customer’s lifetime loyalty. They also were encouraged to give these customers goodies up-front to inspire that loyalty. This justified eye-popping customer acquisition costs.

Lauren Keller Johnson examined one such case—that of flower retailer Gerald Stevens Inc.—for the Massachusetts Institute of Technology’s Sloan School of Business in a study published last winter.

Stevens estimated the lifetime value of its Internet customers would be $60 each, so it rejected an AOL customer acquisition deal at $75 a customer and signed a cheaper deal with Lycos in 1999. Stevens filed for Chapter 11 bankruptcy protection in April 2001.

What went wrong? Stevens used assumptions to estimate customer lifetime value. But the key to a valid calculation is hard data.

It’s time you started collecting some.

Dadi Akhavan, president-COO of e-centives Inc., a Bethesda, Md., Internet direct marketing company, said one key data point is your churn rate, or the rate at which you lose customers and must replace them to keep a stable customer base. If it’s 25%, he said, the customer’s "lifetime" with you is 4 years. The lower you can get your churn rate, the longer your customers "live" and the higher their lifetime value to you.

Calculating the cost of that relationship requires data on every contact, said Scott Kauffman, CEO of Coremetrics Inc., a San Francisco-based analytics company. Someone may visit a Web site five times before buying something on the sixth visit, but if you only track the last visit you won’t know how effective your previous marketing efforts were, he said. Track it all and you have a more accurate picture of your customer acquisition costs.

"Then you want to track the amount of ensuing sales and the effort needed to maintain the relationship," Kauffman said.

The result should be buckets of high-, medium- and low-value customers, along with the cost of marketing to each one and your churn rate. Then you base your decisions on the real return on those investments.

In the b-to-b space, both online and offline costs go into that equation, Kaufmann said. A Web site whose key pages are tagged and analyzed can be useful to an offline sales staff, he said.

The more the Web site tells a sales force about its prospects, the more efficient salespeople can be in meeting the prospects’ true needs. This way, "you’re cutting the sales cycle and increasing the likelihood of closing," Kauffman said.

Lee Sherman, director of the customer insight group for Avenue A, a Seattle-based interactive ad agency, said, "We can easily create a curve of the probability that people who purchased before will do so again, and how often," once the first sale is made and customer interaction moves online.

"This lets us create a predictive model for a customer segment or all purchasers, about the number of purchases to be made going forward," Sherman said.

But you don’t get a predictive model, or a CLV calculation that creates ROI, without hard data. It’s just another one of those hard lessons from the Internet bust that might, if you learn it, help you prosper as the economy starts to grow again.

Dana Blankenhorn is a free-lance journalist who specializes in Internet issues. He is publisher of the Web site www.a-clue.com

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