Customer loyalty myths cause many CRM project failures


Virtually every assumption floating around the business mindsphere about customer loyalty is just plain wrong. And this faulty thinking is the source of a lot of dysfunctional corporate behaviour, including sinking big bucks in customer relationship management (CRM) systems that fail to deliver any value.

That’s the ominous message of Loyalty Myths: Hyped Strategies That Will Put You Out of Business, a book authored by a team of researchers headed by Timothy Keiningham, senior vice-president of Ipsos Loyalty, a market research firm headquartered in Parsippany, N.J.

The book systematically demolishes many cherished beliefs about customer loyalty with a relentless but fascinating barrage of facts, figures, and case histories.

“We kept finding that all the promises made about what our clients would get from customer loyalty weren’t materializing,” says Keiningham, explaining the impetus for writing the book.

Perplexed, he and a group of senior researchers at Ipsos Loyalty examined scientific data based on their client findings, testing and tracking each and every fundamental loyalty assumption back to bottom-line outcomes. “We quickly realized that many of these premises are not true or gross over-simplifications.”

At the core are misinterpretations of the Pareto Principle, or the 80/20 rule, which states that a small number of causes are responsible for a great number of effects.

Years ago, Harvard University’s cost accounting researchers noticed this recurring pattern in business: about 20 per cent of customers are profitable, with the remaining 80 per cent typically broken down into 20 per cent unprofitable and 60 per cent break-even customers.

But companies that want to focus on those 20 per cent profitable customers without doing proper analysis to sniff them out are asking for trouble. “Focusing on customers who spend the most money is a really bad idea,” says Keiningham. “The problem is that the highest-revenue customers can either be the most or the least profitable.” The undesirable ones are customers that may buy a lot of product but only on deal, or demand so much in service they become unprofitable, he explains. “But companies think they’re making money because these customers spend so much.”

Another sacred cow is the idea that it is more profitable to retain an existing customer than to acquire a new one. But this is like throwing good money after bad if a company doesn’t analyze and qualify its customers. “So how is it more profitable to spend more money retaining all your customers when you only break even or lose money with 80 per cent of them?” Keiningham asks pointedly. “The problem with the loyalty movement is that it treats all customers the same.”

In the book, he illustrates this fallacy with a case study called the Parable of the Costly Customer. During the early 1990s, First National Bank of Chicago (now Banc One) observed its return on equity was five per cent, well below the industry benchmark of 15 per cent.

Examinations of the bank’s customer base revealed a key distinguishing characteristic of its profitable customers: they tended to use ATMs and other self-service channels the bank offered. The bank also noted that interactions with its branch tellers were one of its highest operational costs. So in 1995, First National announced it would begin to charge some low-balance checking customers $3 if they sought human assistance for transactions available on ATMs.

Not surprisingly, this raised a public outcry and the bank was lambasted in the media. Competing banks leaped into the fray, singing the praises of their own customer service. First National was even skewered on NBC-TV’s Tonight Show, where Jay Leno cracked: “For $3 you can talk to a human teller – and for $4, they’ll talk dirty to you.”

Banking experts opined that First Chicago’s contrarian approach was sure to erode loyalty to the bank. And the bank’s average deposits per branch did indeed decline in the immediate wake of the debacle. But by the end of 1995, 80 per cent of its transactions were being conducted electronically, and the bank’s profits jumped 28 per cent. So First National had the last laugh.

Keiningham says the reason all these loyalty myths are accepted uncritically is because some do have a small grain of truth in a particular set of circumstances, but the science in this area is still incomplete. And business leaders don’t have time to analyze theories in the rush to beat the competition. “An idea gets some supporting evidence that looks scientific, and suddenly, it passes a barrier and we never challenge it again. This has a corrupting influence,” he says.

The evolution of CRM systems

Keiningham believes customer loyalty myths play a big role in the high rate of CRM failures , pegged at about 50 per cent by the Gartner Group. Lack of a proper CRM strategy coupled with the tantalizing promises made about the ROI of CRM systems has led companies, flying blind, to over-spend in this area.

Understanding customer behaviour is the ultimate point of CRM, but he says many companies fail to incorporate an attitudinal component to sniff out the “squishy stuff”: the complicated reasons customers have for behaving the way they do . “You not only need to know what customers are doing, you need to know why,” he says.

Most companies don’t do a good job of collecting information for customer databases and warehouses even to satisfy the part about knowing what their customers are doing, he says. “I’m always amazed at how bad customer databases are , even in big companies that claim they have a CRM system in place,” says Keiningham. To truly understand customer behaviour, databases would require continuous updating to capture sequential information about when and why customers buy, and few companies do this well.

Keiningham says a CRM system working in isolation without linkages to data about profits can’t provide meaningful information. Companies that really want to achieve this need to go whole hog and implement enterprise business intelligence (BI) systems that link to financial, supply chain and other systems and provide the analytical tools needed to make sense of the mass of customer data generated.

Mauricio Rodriquez, senior research analyst at the Info-Tech Research Group in London, Ont., agrees that an enterprise BI is critical to realize the value of CRM. But he says it’s difficult to separate CRM implementations that fail due to strategic or tactical reasons, alluding to the high rate of IT implementations of all kinds that fail due to poor project management. “A large number of companies don’t have the proper mechanisms to measure the ROI of any IT project,” he says.

Due to the high failure rate, CRM is getting a bad reputation, and the same thing happened with enterprise resource planning (ERP) systems in the past, he says. “A high percentage of these projects fail due to a lack of a clear business strategy, and it’s <a href="

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