I think it's dangerous to fail give any benefit of the doubt at all, and to assume they pulled a number completely out of their asses.
I am giving them the benefit of the doubt, I assume it was based on more than a guess.
Now, instead of assuming, I'm going to look it up.
It turns out they described what they did, and it seems that it was based on some actual data:
"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—repeat purchases and referral patterns—over time. I sought the assistance 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. loyaltyrules.com/loyaltyrules/acid_test_customer.html.) We administered the test 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.
"We 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, we waited six to 12 months and gathered information on subsequent purchases and referrals from those individuals. With information from more than 4,000 customers, we were able to build 14 case studies—that is, cases in which we had 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 us to determine which survey questions had the strongest statistical correlation with repeat purchases or referrals. We hoped that we would find at least one question for each industry that effectively predicted such behaviors, which can drive growth. We 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 first or second in 11 of the 14 cases studies. And in two of the three other cases, “would recommend” ranked so close behind the top two predictors that the surveys would be nearly as accurate by relying on results of this single question."
I am giving them the benefit of the doubt, I assume it was based on more than a guess.
Now, instead of assuming, I'm going to look it up.
It turns out they described what they did, and it seems that it was based on some actual data:
"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—repeat purchases and referral patterns—over time. I sought the assistance 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. loyaltyrules.com/loyaltyrules/acid_test_customer.html.) We administered the test 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.
"We 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, we waited six to 12 months and gathered information on subsequent purchases and referrals from those individuals. With information from more than 4,000 customers, we were able to build 14 case studies—that is, cases in which we had 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 us to determine which survey questions had the strongest statistical correlation with repeat purchases or referrals. We hoped that we would find at least one question for each industry that effectively predicted such behaviors, which can drive growth. We 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 first or second in 11 of the 14 cases studies. And in two of the three other cases, “would recommend” ranked so close behind the top two predictors that the surveys would be nearly as accurate by relying on results of this single question."
https://hbr.org/2003/12/the-one-number-you-need-to-grow