The One Number You Need to Grow

The One Number You Need to Grow

Reprint: R0312C

Companies spend lots of time and money on complex tools to sess customer . But they’re meuring the wrong thing. The best predictor of top-line growth can usually be captured in a single survey question: Would you recommend this company to a friend?

This finding is bed on two years of research in which a variety of survey questions were tested by linking the responses with actual customer behavior—purching patterns and referrals—and ultimately with company growth. Surprisingly, the most effective question wn’t about customer or even loyalty per se. In most of the industries studied, the percentage of customers enthusitic enough about a company to refer it to a friend or colleague directly correlated with growth rates among competitors.

Willingness to talk up a company or product to friends, family, and colleagues is one of the best indicators of loyalty because of the customer’s sacrifice in making the recommendation. When customers act references, they do more than indicate they’ve received good economic value from a company; they put their own reputations on the line. And they will risk their reputations only if they feel intense loyalty.

The findings point to a new, simpler approach to customer research, one directly linked to a company’s results. By substituting a single question—blunt tool though it may appear to be—for the complex black box of the customer survey, companies can actually put consumer survey results to use and focus employees on the tk of stimulating growth.

Many companies—striving for unprecedented growth by cultivating intensely loyal customers—invest lots of time and money meuring customer . But most of the yardsticks they use are complex, yield ambiguous results, and don’t necessarily correlate to profits or growth.

The good news is: you don’t need expensive surveys and complex statistical models. You only have to k your customers one question: “How likely is it that you would recommend our company to a friend or colleague?” The more “promoters” your company h, the bigger its growth.

Why is willingness to promote your company such a strong indicator of loyalty—and growth? Because when customers recommend you, they’re putting their reputations on the line. And they’ll take that risk only if they’re intensely loyal.

By king this one question, you collect simple and timely data that correlate with growth. You also get responses you can eily interpret and communicate. Your message to employees—“Get more promoters and fewer detractors”—becomes clear-cut, actionable, and motivating, especially when tied to incentives.

The Idea in Practice

king a statistically valid sample of customers “How likely is it that you would recommend our company to a friend or colleague?” enables you to calculate your net-promoter score: the ratio of promoters to detractors.

Bed on their responses on a 0 to 10 rating scale, group your customers into “promoters” (9–10 rating—extremely likely to recommend), “psively satisfied” (7–8 rating), and “detractors” (0–6 rating—extremely unlikely to recommend). Then subtract the percentage of detractors from the percentage of promoters. Companies that garner world-cls loyalty receive net-promoter scores of 75% to more than 80%.

Your net-promoter score provides valuable insights into how to get more promoters and fewer detractors. For example, compare your company’s scores region to region, branch to branch, sales rep to sales rep, and customer segment to customer segment. Uncover root causes of differences and share best practices from your highest-scoring groups. Also survey your competitors’ customers using the same method. How does your company stack up against the very high bar of 75% to 80% net-promoter score?

Use your score to send a clear message to managers and employees about the importance of promoters—and the dangers of detractors. Consider these guidelines:


By making field managers ineligible for promotion unless their branch or group of branches matches or exceeds the company’s average net-promoter scores, Enterprise Rent-A-Car h seen its survey scores rise—and its growth incree relative to its rivals.

The CEOs in the room knew all about the power of loyalty. They had already transformed their companies into industry leaders, largely by building intensely loyal relationships with customers and employees. Now the chief executives—from Vanguard, Chick-fil-A, State Farm, and a half-dozen other leading companies—had gathered at a day forum to swap insights that would help them further enhance their loyalty efforts. And what they were hearing from Andy Taylor, the CEO of Enterprise Rent-A-Car, w riveting.

Taylor and his senior team had figured out a way to meure and manage customer loyalty without the complexity of traditional customer surveys. Every month, Enterprise polled its customers using just two simple questions, one about the quality of their rental experience and the other about the likelihood that they would rent from the company again. Because the process w so simple, it w ft. That allowed the company to publish ranked results for its 5,000 U.S. branches within days, giving the offices real-time feedback on how they were doing and the opportunity to learn from successful peers.

The survey w different in another important way. In ranking the branches, the company counted only the customers who gave the experience the highest possible rating. That narrow focus on enthusitic customers surprised the CEOs in the room. Hands shot up. What about the rest of Enterprise’s customers, the marginally satisfied who continued to rent from Enterprise and were necessary to its business? Wouldn’t it be better to track, in a more sophisticated way, mean or median statistics? No, Taylor said. By concentrating solely on those most enthusitic about their rental experience, the company could focus on a key driver of profitable growth: customers who not only return to rent again but also recommend Enterprise to their friends.

Enterprise’s approach surprised me, too. Most customer surveys aren’t very useful. They tend to be and complicated, yielding low response rates and ambiguous implications that are difficult for operating managers to act on. Furthermore, they are rarely challenged or audited because most senior executives, board members, and investors don’t take them very seriously. That’s because their results don’t correlate tightly with profits or growth.

But Enterprise’s method—and its ability to generate profitable growth through what appeared to be quite a simple tool—got me thinking that the company might be on to something. Could you get similar results in other industries—including those seemingly more complex than car rentals—by focusing only on customers who provided the most enthusitic responses to a short list of questions designed to sess their loyalty to a company? Could the list be reduced to a single question? If so, what would that question be?

It took me two years of research to figure that out, research that linked survey responses with actual customer behavior—purching patterns and referrals—and ultimately with company growth. The results were clear yet counterintuitive. It turned out that a single survey question can, in fact, serve a useful predictor of growth. But that question isn’t about customer or even loyalty—at let in so many words. Rather, it’s about customers’ willingness to recommend a product or service to someone else. In fact, in most of the industries that I studied, the percentage of customers who were enthusitic enough to refer a friend or colleague—perhaps the strongest sign of customer loyalty—correlated directly with differences in growth rates among competitors.

By substituting a single question for the complex black box of the typical customer survey, companies can actually put consumer survey results to use and focus employees on the tk of stimulating growth.

Certainly, other factors besides customer loyalty play a role in driving a company’s growth—economic or industry expansion, innovation, and so on. And I don’t want to overstate the findings: Although the “would recommend” question generally proved to be the most effective in determining loyalty and predicting growth, that wn’t the ce in every single industry. But evangelistic customer loyalty is clearly one of the most important drivers of growth. While it doesn’t guarantee growth, in general profitable growth can’t be achieved without it.

Furthermore, these findings point to an entirely new approach to customer surveys, one bed on simplicity that directly links to a company’s results. By substituting a single question—blunt tool though it may appear to be—for the complex black box of the typical customer survey, companies can actually put consumer survey results to use and focus employees on the tk of stimulating growth.

Before I describe my research and the results from a number of industries, let’s briefly look at the concept of loyalty and some of the mistakes companies make when trying to meure it. First, a definition. Loyalty is the willingness of someone—a customer, an employee, a friend—to make an investment or personal sacrifice in order to strengthen a relationship. For a customer, that can mean sticking with a supplier who trs him well and gives him good value in the term even if the supplier does not offer the best price in a particular transaction.

Consequently, customer loyalty is about much more than rep purches. Indeed, even someone who buys again and again from the same company may not necessarily be loyal to that company but instead may be trapped by inertia, indifference, or exit barriers erected by the company or circumstance. (Someone may regularly take the same airline to a city only because it offers the most flights there.) Conversely, a loyal customer may not make frequent rep purches because of a reduced need for a product or service. (Someone may buy a new car less often he gets older and drives less.)

True loyalty clearly affects profitability. While regular customers aren’t always profitable, their choice to stick with a product or service typically reduces a company’s customer acquisition costs. Loyalty also drives top-line growth. Obviously, no company can grow if its customer bucket is leaky, and loyalty helps eliminate this outflow. Indeed, loyal customers can raise the water level in the bucket: Customers who are truly loyal tend to buy more over time, their incomes grow or they devote a larger share of their wallets to a company they feel good about.

And loyal customers talk up a company to their friends, family, and colleagues. In fact, such a recommendation is one of the best indicators of loyalty because of the customer’s sacrifice, if you will, in making the recommendation. When customers act references, they do more than indicate that they’ve received good economic value from a company; they put their own reputations on the line. And they will risk their reputations only if they feel intense loyalty. (Note that here, too, loyalty may have little to do with rep purches. someone’s income increes, she may move up the motive ladder from the Hond she h bought for years. But if she is loyal to the company, she will enthusitically recommend a Honda to, say, a nephew who is buying his first car.)

The tendency of loyal customers to bring in new customers—at no charge to the company—is particularly beneficial a company grows, especially if it operates in a mature industry. In such a ce, the tremendous marketing costs of acquiring each new customer through advertising and other promotions make it hard to grow profitably. In fact, the only path to profitable growth may lie in a company’s ability to get its loyal customers to become, in effect, its marketing department.

Because loyalty is so important to profitable growth, meuring and man it make good sense. Unfortunately, existing approaches haven’t proved very effective. Not only does their complexity make them practically useless to line managers, but they also often yield flawed results.

The best companies have tended to focus on customer retention rates, but that meurement is merely the best of a mediocre lot. Retention rates provide, in many industries, a valuable link to profitability, but their relationship to growth is tenuous. That’s because they bically track customer defections—the degree to which a bucket is emptying rather filling up. Furthermore, I have noted, retention rates are a poor indication of customer loyalty in situations where customers are held hostage by high switching costs or other barriers, or where customers naturally outgrow a product because of their , increed income, or other factors. You’d want a stronger connection between retention and growth before you went ahead and invested significant money bed only on data about retention.

An even less reliable means of gauging loyalty is through conventional customer- meures. Our research indicates that lacks a consistently demonstrable connection to actual customer behavior and growth. This finding is borne out by the short shrift that investors give to such reports the American Consumer Index. The ACSI, published quarterly in the Wall St Journal, reflects the customer ratings of some 200 U.S. companies. In general, it is difficult to discern a strong correlation between high customer scores and outstanding sales growth. Indeed, in some ces, there is an inverse relationship; at Kmart, for example, a significant incree in the company’s ACSI rating w accompanied by a sharp decree in sales it slid into bankruptcy.

Even the most sophisticated meurement systems have serious flaws. I saw this firsthand at one of the Big Three car manufacturers. The marketing executive at the company wanted to understand why, after the firm had spent millions of dollars on customer surveys, ratings for individual dealers did not relate very closely to dealer profits or growth. When I interviewed dealers, they agreed that customer seemed like a reonable goal. But they also pointed out that other factors were far more important to their profits and growth, such keeping pressure on salespeople to close a high percentage of leads, filling showrooms with pects through aggressive advertising, and charging customers the highest possible price for a car.

In most ces, dealers told me, the survey is a charade that they play a with to remain in the good graces of the manufacturer and to ensure generous allocations of the hottest-selling models. The pressure they put on salespeople to boost scores often results in postsale pleading with customers to provide top ratings—even if they must offer something like free floor mats or oil changes in return. Dealers are usually complicit with salespeople in this process, a circumstance that further degrades the integrity of these scores. Indeed, some savvy customers negotiate a low price—and then offer to sell the dealer a set of top survey ratings for another $500 off the price.

Figuring out a way to accurately meure customer loyalty and is extremely important. Companies won’t realize the fruits of loyalty until usable meurement systems enable firms to meure their performance against clear loyalty goals—just they now do in the ce of profitability and quality goals. For a while, it seemed though information technology would provide a means to accurately meure loyalty. Sophisticated customer-relationship-management systems promised to help firms track customer behavior in real time. But the successes thus far have been limited to select industries, such credit cards or grocery stores, where purches are so frequent that changes in customer loyalty can be quickly spotted and acted on.

So what would be a useful metric for gauging customer loyalty? To find out, I needed to do something rarely undertaken with customer surveys: Match survey responses from individual customers to their actual behavior—rep purches and referral patterns—over time. I sought the sistance of Satmetrix, a company that develops software to gather and analyze real-time customer feedback—and on whose board of directors I serve. Teams from Bain also helped with the project.

We started with the roughly 20 questions on the Loyalty Acid Test, a survey that I designed four years ago with Bain colleagues, which does a pretty good job of establishing the state of relations between a company and its customers. (The complete test can be found at http://www. We administered the test to thousands of customers recruited from public lists in six industries: financial services, cable and telephony, personal computers, e-commerce, insurance, and Internet service providers.

We then obtained a purche history for each person surveyed and ked those people to name specific instances in which they had referred someone else to the company in question. When this information wn’t immediately available, we waited six to 12 months and gathered information on subsequent purches and referrals from those individuals. With information from more than 4,000 customers, we were able to build 14 ce studies—that is, ces in which we had sufficient sample sizes to meure the link between survey responses of individual customers of a company and those individuals’ actual referral and purche behavior.

The data allowed us to determine which survey questions had the strongest statistical correlation with rep purches or referrals. We hoped that we would find at let one question for each industry that effectively predicted such behaviors, which can drive growth. We found something more: One question w best for most industries. “How likely is it that you would recommend [company X] to a friend or colleague?” ranked first or second in 11 of the 14 ces studies. And in two of the three other ces, “would recommend” ranked so close behind the top two predictors that the surveys would be nearly accurate by relying on results of this single question. (For a ranking of the best-scoring questions, see the sidebar “k the Right Question.”)

part of our research into customer loyalty and growth, my colleagues and I looked for a correlation between survey responses and actual behavior—rep purches, or recommendations to friends and peers—that would ultimately lead to profitable growth. Bed on information from 4,000 consumers, we ranked a variety of survey questions according to their ability to predict this desirable behavior. (Interestingly, cring a weighted index—bed on the responses to multiple questions and taking into account the relative effectiveness of those questions—provided insignificant predictive advantage.)

The top-ranking question w far and away the most effective across industries:

Two questions were effective predictors in certain industries:

Other questions, while useful in a particular industry, had little general applicability:

These findings surprised me. My personal bet for the top question (probably reflecting the focus of my research on employee loyalty in recent years) would have been “How strongly do you agree that [company X] deserves your loyalty?” Clearly, though, the abstract concept of loyalty w less compelling to customers than what may be the ultimate act of loyalty, a recommendation to a friend. I also expected that “How strongly do you agree that [company X] sets the standard for excellence in its industry?”—with its implications of offering customers both economic benefit and fair trment—would prove more predictive than it did. One result did not startle me at all. The question “How satisfied are you with [company X’s] overall performance?” while relevant in certain industries, would prove to be a relatively weak predictor of growth.

So my colleagues and I had the right question—“How likely is it that you would recommend [company X] to a friend or colleague?”—and now we needed to develop a scale to score the responses. This may seem somewhat trivial, but, statisticians know, it’s not. Making customer loyalty a strategic goal that managers can work toward requires a scale simple and unambiguous the question itself. The right one will effectively divide customers into practical groups deserving different attention and organizational responses. It must be intuitive to customers when they sign grades and to employees and partners responsible for interpreting the results and taking action. Ideally, the scale would be so ey to understand that even outsiders, such investors, regulators, and journalists, would grp the bic messages without needing a handbook and a statistical abstract.

For these , we settled on a scale where ten means “extremely likely” to recommend, five means neutral, and zero means “not at all likely.” When we examined customer referral and repurche behaviors a this scale, we found three logical clusters. “Promoters,” the customers with the highest rates of repurche and referral, gave ratings of nine or ten to the question. The “psively satisfied” logged a seven or an eight, and “detractors” scored from zero to six.

By limiting the promoter designation to only the most enthusitic customers, we avoided the “grade inflation” that often infects traditional customer- sessments, in which someone a molecule north of neutral is considered “satisfied.” (This w the danger that Enterprise Rent-A-Car avoided when it decided to focus on its most enthusitic customers.) And not only did clustering customers into three categories—promoters, the psively satisfied, and detractors—turn out to provide the simplest, most intuitive, and best predictor of customer behavior; it also made sense to frontline managers, who could relate to the goal of increing the number of promoters and reducing the number of detractors more readily than increing the mean of their index by one standard deviation.

All of our analysis to this point had focused on customer survey responses and how well those linked to customers’ referral and repurche behavior at 14 companies in six 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.

The only path to profitable growth may lie in a company’s ability to get its loyal customers to become, in effect, its marketing department.

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 ked respondents (drawn again from public sources, not Satmetrix’s internal client customer lists) to rate one or two companies with which they were familiar. Where we could obtain comparable and reliable revenue-growth data for a range of competitors, and where there were sufficient consumer responses, we 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 three-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 h found a way to incree growth without improving its ratio of promoters to detractors. That result w reflected, to a grer or lesser degree, in most of the industries we examined—including rental cars, where Enterprise enjoys both the highest rate of growth and the highest net-promoter percentage among its competitors. (See the exhibit “Growth by Word of Mouth.”)

The “would recommend” question wn’t the best predictor of growth in every ce. In a few situations, it w simply irrelevant. In databe software or computer systems, for instance, senior executives select vendors, and top managers typically didn’t appear on the public e-mail lists we used to sample customers. king users of the system whether they would recommend the system to a friend or colleague seemed a little abstract, they had no choice in the matter. In these ces, we found that the “sets the standard of excellence” or “deserves your loyalty” questions were more predictive.

Not surprisingly, “would recommend” also didn’t predict relative growth in industries dominated by monopolies and near monopolies, where consumers have little choice. For example, in the local telephone and cable TV businesses, population growth and economic expansion in the region determine growth rates, not how well customers are tred by their suppliers. And in certain ces, we found small niche companies that were growing fter than their net-promoter percentages would imply. But for most companies in most industries, getting customers enthusitic enough to recommend a company appears to be crucial to growth. (To calculate your own net-promoter number, see the sidebar “A Net-Promoter Primer.”)

Tracking net promoters—the percentage of customers who are promoters of a brand or company minus the percentage who are detractors—offers organizations a powerful way to meure and manage customer loyalty. Firms with the highest net-promoter scores consistently garner the lion’s share of industry growth. So how can companies get started?

Survey a statistically valid sample of your customers with the following question: “How likely is it that you would recommend [brand or company X] to a friend or colleague?” It’s critical to provide a consistent scale for responses that range from zero to ten, where zero means not at all likely, five means neutral, and ten means extremely likely.

Resist the urge to let survey questions multiply; more questions diminish response rates a with the reliability of your sample. You need only one question to determine the status—promoter, psively satisfied, or detractor—of a customer. (Follow-up questions can help unearth the for customers’ feelings and point to profitable remedies. But such questions should be tailored to the three categories of customers. Learning how to turn a psively satisfied customer into a promoter requires a very different line of questioning from learning how to resolve the problems of a detractor.)

Calculate the percentage of customers who respond with nine or ten (promoters) and the percentage who respond with zero through six (detractors). Subtract the percentage of detractors from the percentage of promoters to arrive at your net-promoter score. Don’t be surprised if your score is lower than you expect. The median net-promoter score of more than 400 companies in 28 industries (bed on some 130,000 customer survey responses gathered over the pt two-plus years by Satmetrix, a maker of software for man real-time customer feedback) w just 16%.

Compare net-promoter scores from specific regions, branches, service or sales reps, and customer segments. This often reveals root causes of differences well best practices that can be shared. What really counts, of course, is how your company compares with direct competitors. Have your market researchers survey your competitors’ customers using the same method. You can then determine how your company stacks up within your industry and whether your current net-promoter number is a competitive set or a liability.

Improve your score. The companies with the most enthusitic customer referrals, including eBay, Amazon, and USAA, receive net-promoter scores of 75% to more than 80%. For companies aiming to garner world-cls loyalty—and the growth that comes with it—this should be the target.

The battle for growth among Internet service providers AOL, MSN, and EarthLink brings to life our findings. For years, market leader AOL aggressively focused on new customer acquisition. Through those efforts, AOL more than offset a substantial number of defections. But the company paid much less attention to converting these new customers into intensely loyal promoters. Customer service lapsed, to the point where customers couldn’t even find a phone number to contact company representatives to answer questions or resolve problems.

Today, AOL is struggling to grow. Even though AOL’s customer count surged to an eventual peak of 35 million, its deteriorating mix of promoters and detractors eventually choked off expansion. The fire hose of new customer flow—filled with people attracted to free trial promotions—couldn’t keep up with the leaks in AOL’s customer bucket. Defection rates exceeded 200,000 customers per month in 2003. Marketing costs were ratcheted up to stem the tide, and those expenditures, a with the collapse of online advertising, contributed to declines in ch flow of almost 40% between 2001 and 2003.

By 2002, our research found, 42% of the company’s customers were detractors, while only 32% were promoters, giving the company a net-promoter percentage of -10%. The current management team is working on the problem, but it’s a challenging one because disappointed customers are undoubtedly spreading their opinions about AOL to family, friends, colleagues, and acquaintances.

AOL’s experience vividly illustrates the folly of seeking growth through shortcuts such msive price cuts or other incentives rather than through building true loyalty. It also illustrates the detrimental effect that detractors’ word-of-mouth communications can have on a business—the flip side of customers’ recommendations to their friends. Countering a damaged reputation requires a company to cre tremendously appealing incentives that will persuade skeptical customers to give a product or service a try, and the incentives drive up already significant customer acquisition costs.

Furthermore, detractors—and even customers who are only psively satisfied but not enthusitically loyal—typically take a toll on employees and incree service costs. Finally, every detractor represents a missed opportunity to add a promoter to the customer population, one more unpaid salesperson to market your product or service and generate growth.

One of the main takeaways from our research is that companies can keep customer surveys simple. The most bic surveys—employing the right questions—can allow companies to report timely data that are ey to act on. Too many of today’s survey processes yield complex information that’s months out of date by the time it reaches frontline managers. Good luck to the branch manager who tries to help an employee interpret a score resulting from a complex weighting algorithm bed on feedback from anonymous customers, many of whom were surveyed before the employee had his current job.

Contrt that scenario with one in which a manager presents employees with numbers from the previous week (or day) showing the percentages (and names) of a branch office’s customers who are promoters, psively satisfied, and detractors—and then issues the managerial charge, “We need more promoters and fewer detractors in order to grow.” The goal is clear-cut, actionable, and motivating.

In short, a customer feedback program should be viewed not “market research” but an operating management tool. Again, consider Enterprise Rent-A-Car. The first step in the development of Enterprise’s current system w to devise a way to track loyalty by meuring service quality from the customer’s perspective. The initial effort yielded a , unwieldy research questionnaire, one that included the pet questions of everyone involved in drafting the survey. It only captured average service quality on a regional bis—interesting, but useless, since managers needed to see scores for each individual branch to establish clear accountability. Over time, the sample w expanded to provide this information. And the number of questions on the survey w sharply reduced; this simplified the collating of answers and allowed the company to post monthly branch-level results almost soon they were collected.

The company then began examining the relationships between customer responses and actual purches and referrals. This is when Enterprise learned the value of enthusits. Customers who gave the highest rating to their rental experience were three times more likely to rent again than those who gave Enterprise the second-highest grade. When a customer reported a neutral or negative experience, marking him a potential detractor, the interviewer requested permission to immediately forward this information to the branch manager, who w trained how to apologize, identify the root cause of the problem, and resolve it.

The meurement system cost more than $4 million per year, but the company made such significant progress in building customer loyalty that the company’s management considers it one of the company’s best investments. And the new system had definitely started to get employees’ attention. In fact, a few branch managers (perhaps taking a cue from car dealers) attempted to manipulate the system to their benefit. Enterprise responded with a process for spotting—for example, by ensuring that the phone numbers of dissatisfied respondents hadn’t been changed, making it difficult to follow up—and punishing “gamers.”

Despite the system’s success, CEO Andy Taylor felt something w missing. Branch scores were not improving quickly enough, and a big gap continued to separate the worst- and best-performing regions. Taylor’s sessment: “We needed a grer sense of urgency.” So the management team decided that field managers would not be eligible for promotion unless their branch or group of branches matched or exceeded the company’s average scores. That’s a pretty idea when you think about it: giving customers, in effect, veto power over managerial pay raises and promotions.

The rigorous implementation of this simple customer feedback system had a clear impact on business. the survey scores rose, so did Enterprise’s growth relative to its competition. Taylor cites the linking of customer feedback to employee rewards one of the most important that Enterprise h continued to grow, even the business became bigger and, arguably, more mature. (For more on Enterprise’s customer survey program, see “Driving Customer ,” HBR July 2002.)

If collecting and applying customer feedback is this simple, why don’t companies already do it this way? I don’t want to be too cynical, but perhaps the research firms that administer current customer surveys know there is very little profit margin for them in something bare-bones this. Complex loyalty indexes, bed on a dozen or more proprietary questions and weighted with a black-box scaling function, simply generate more business for survey firms.

The market research firms have an even deeper fear. With the advent of e-mail and analytical software, leading-edge companies can now byps the research firms entirely, cutting costs and improving the quality and timeliness of feedback. These new tools enable companies to gather customer feedback and report results in real time, funneling it directly to frontline employees and managers. This can also thren in-house market research departments, which typically have built their power be through controlling and interpreting customer survey data. Marketing departments understandably focus surveys on the are they can control, such brand image, pricing, and product fures. But a customer’s willingness to recommend to a friend results from how well the customer is tred by frontline employees, which in turn is determined by all the functional are that contribute to a customer’s experience.

For a meure to be practical, operational, and reliable—that is, for it to determine the percentage of net promoters among customers and allow managers to act on it—the process and the results need to be owned and accepted by all of the business functions. And all the people in the organization must know which customers they are responsible for. Overseeing such a process is a more appropriate tk for the CFO, or for the general manager of the business unit, than for the marketing department. Indeed, it is too important (and politically charged) to delegate to any one function.

The path to sustainable, profitable growth begins with cring more promoters and fewer detractors and making your net-promoter number transparent throughout your organization. This number is the one number you need to grow. It’s that simple and that profound.

Frederick F. Reichheld (fred.reichheld@bain.comLoyalty Rules! (Harvard Business School Press, 2001). His next book, The Ultimate Question, is due in early 2006 from Harvard Business School Press.

The One Number You Need to Grow