But now—was that really happening? Cook wasn’t sure. When the company was in its start-up phase, operating out of cozy offices in Silicon Valley, he had known every employee personally, and he could coach them all on the importance of making products and delivering services that customers truly loved. They could all hear him working the service phones himself, talking to customers. They could see him taking part in Intuit’s famous “follow-me-home” program, where employees asked customers if they could watch them set up the software in order to note any problems. But now the company had thousands of people in multiple locations. Like many rapidly growing businesses, it had hired a lot of professional managers, who had been trained to run things by the numbers.
And what were those numbers? There were two requirements for growth, Cook liked to say: profitable customers and happy customers. Everyone knew how to measure profits, but the only measurements of customers’ happiness were vague statistics of “satisfaction”—statistics derived from surveys that nobody trusted and nobody was accountable for.
So managers naturally focused on profits, with predictable consequences. The executive who cut staffing levels in the phone-support queue to reduce costs wasn’t held accountable for the increased hold times or the resulting customer frustration. The phone rep who so angered a longtime customer that he switched to another tax-software product could still receive a quarterly bonus, because she handled so many calls per hour. Her batting average on productivity was easy to measure, but her batting average on customer goodwill was invisible. The marketing manager who kept approving glitzy new features to attract more customers was rewarded for boosting revenues and profits, when in fact the added complexity created a bewildering maze that turned off new users. Now, Cook was hearing more complaints than in the past. Some market-share numbers were slipping. For lack of a good system of measurement—and for lack of the accountability that accurate measurement creates—the company seemed to be losing sight of exactly what had made it great: its relationships with its customers.
The Challenge: Measuring Customer Happiness
In a way, Cook’s experience recapitulated business history. Back in the days when every business was a small business, a proprietor could know what his customers were thinking and feeling by the looks on their faces. He knew them personally. He could see with his own eyes what made them happy and what made them mad. Customer feedback was immediate and direct—and if he wanted to stay in business, he paid attention to it.
But soon companies were growing too big for their owners or managers to know every customer. Individual customers came and went; the tide of customers ebbed and flowed. Without the ability to gauge what people were thinking and feeling, corporate managers naturally focused on how much those customers were spending, a number that was easily measurable. If our revenue is growing and we’re making money, so the thinking ran, we must be doing something right.
Later, of course—and particularly after the arrival of powerful computers—companies tried to assess customers’ attitudes more directly. They hired market-research firms to conduct satisfaction surveys. They tried to track customer-retention rates. These endeavors were so fraught with difficulties that managers outside marketing departments generally, and wisely, ignored the efforts. Retention rates, for example, track customer defections—how fast the customer bucket is emptying—but say nothing on the equally important question of how fast the bucket is filling up. They are a particularly poor indication of attitudes whenever customers are held hostage by high switching costs or other barriers. (Think of those US Airways Baltimore-Washington travelers before Southwest Airlines arrived on the scene.)
Conventional customer-satisfaction measures are even less reliable. There is only a tenuous connection between satisfaction rates and actual customer behavior, and between satisfaction rates and a company’s growth. That’s why investors typically ignore reports on customer satisfaction. In some cases, indeed, the relationship between satisfaction and performance is exactly backward. In the spring of 2005, for example, General Motors was taking out full-page newspaper ads trumpeting its numerous awards from J.D. Power and Associates, the biggest name in satisfaction studies. Meanwhile, the headlines in the business section were announcing that GM’s market share was sinking and its bonds were being downgraded to junk status. A few years later GM would find itself in bankruptcy proceedings.
So as we continued our study of loyalty, we searched for a better measure—a simple and practical indicator of what customers were thinking and feeling about the companies they did business with. We wanted a number that reliably linked these attitudes to what customers actually did, and to the growth of the company in question.
What a chore it turned out to be! We started with the roughly twenty questions on the Loyalty Acid Test, a survey Bain designed several years ago to assess the state of relations between a company and its customers. (Sample questions: How likely are you to purchase Company X’s products or services again? What was your overall satisfaction with the products and services provided by Company X?) Then we sought the assistance of Satmetrix Systems Inc., a company that develops software to gather and analyze real-time customer feedback. (Full disclosure: Fred serves on Satmetrix’s board of advisers and worked with the company to develop its NPS certification course.)
The process began with the recruitment (from public lists) of thousands of customers in six industries: financial services, cable and telecommunications, personal computers, e-commerce, auto insurance, and Internet service providers. We then obtained a purchase history for every person surveyed. We also asked these people to name specific instances when they had referred someone else to the company in question. When this information wasn’t immediately available, we waited six to twelve months and then gathered information on subsequent purchases and referrals by those individuals. Eventually we had detailed information from more than four thousand customers, and we were able to build fourteen case studies—that is, cases for which we had sufficient sample sizes to measure the link between individual customers’ survey responses and those same individuals’ purchase or referral behavior.
Discovering the Right Question
All this number crunching had one goal: to determine which survey questions showed the strongest statistical correlation with repeat purchases or referrals. We hoped to find for each industry at least one question that effectively predicted what customers would do, and hence helped predict a company’s growth. We took bets on what the question would be. Our own favorite—probably reflecting our years of research on loyalty—was, “How strongly do you agree that Company X deserves your loyalty?”
But what we found was different, and it surprised us all. It turned out that the same question—the ultimate question—worked best for most industries. And that question was, “How likely is it that you would recommend Company X to a friend or colleague?” In eleven of the fourteen cases, this question ranked first or second. In two of the three others, it was so close to the top that it could serve as a proxy for those that did rank number one or number two.
Reflecting on our findings, we realized they made perfect sense. Loyalty, after all, is a strong and value-laden concept, usually applied to family, friends, and country. People may be loyal to a company that they buy from, but they may not describe what they feel in those terms. If they really love doing business with a particular provider of goods or services, however, what’s the most natural thing for them to do? Of course: recommend that company to someone they care about.
We also realized that two conditions must be satisfied before customers make a personal referral. They must believe that the company offers superior value in terms that an economist would understand: price, features, quality, functionality, ease of use, and other such factors. But they also must feel good about their relationship with the company. They must believe the company knows and understands them, values them, listens to them, and shares their principles. On the first dimension, a company is engaging the customer’s head. On the second, it is engaging the heart. Only when both sides of the equation are fulfilled will a customer enthusiastically recommend a company to a friend. The customer must believe that the friend will get good value—but he or she also must believe that