Winners & Sinners

Determining a Useful Metric

To determine a useful metric for gauging customer loyalty, Fred Reichheld did something rarely undertaken with customer surveys: match survey responses from individual customers to their actual behavior - repeat purchase and referral patterns - over time. With the assistance of Satmetrix, Reichheld started with the roughly 20 questions of the Loyalty Acid Test, a survey he designed with Bain colleagues, which establishes the state of relations between a company and its customers. The test was administered to thousands of customers recruited from public lists in six industries: financial services, cable and telephony, personal computers, e-commerce, auto insurance, and Internet service providers.

The team then obtained a purchase history for each person surveyed and asked those people to name specific instances in which they had referred someone else to the company in question. When this information wasn't immediately available, they waited 6 to 12 months and gathered information on subsequent purchases and referrals from those individuals. With information from more than 4,000 customers, they were able to build 14 case studies - that is, cases in which there were sufficient sample sizes to measure the link between survey responses of individual customers of a company and those individuals' actual referral and purchase behavior.

The data allowed the team to determine which survey questions had the strongest statistical correlation with repeat purchases or referrals. The team hoped they would find at least one question for each industry that effectively predicted such behaviors, which can drive growth. They found something more: One question was best for most industries. "How likely is it that you would recommend [company X] to a friend or colleague?" ranked so close behind the top two predictors that surveys would be nearly as accurate by relying on results of this single question.

The Growth Connection

All of the analysis to this point had focused on customer survey responses and how well those linked to customers' referral and purchase behavior at 14 companies in 6 industries. But the real test would be how well this approach explained relative growth rates for all competitors in an industry - and across a broader range of industry sectors.

In the first quarter of 2001, Satmetrix began tracking the "would recommend" scores of a new universe of customers, many thousands of them from more than 400 companies in more than a dozen industries. In each subsequent quarter, they then gathered 10,000 to 15,000 responses to a very brief e-mail survey that asked respondents (drawn again from public sources, not Satmetrix's internal customer lists) to rate one or two companies with which they were familiar.

Where the team could obtain comparable and reliable revenue-growth data for a range of competitors, and where there were sufficient consumer responses, the team plotted each firm's net promoters - the percentage of promoters minus the percentage of detractors - against the company's revenue growth rate.

The results were striking. In airlines, for example, a strong correlation existed between net promoter figures and a company's average growth rate over the 3-year period from 1999 to 2002.

Remarkably, this one simple statistic seemed to explain the relative growth rates across the entire industry; that is, no airline has found a way to increase growth without improving its ratio of promoters to detractors. That result was reflected, to a greater or lesser degree, in most of the industries examined - including rental cars, where Enterprise enjoys both the highest rate of growth and the highest Net Promoter percentage among its competitors.

For more on this topic, read the Harvard Business Review primer - The One Number You Need to Grow - to The Ultimate Question, and the book itself.