Net Promoter or Net Promoter Score (NPS) is a widely used market research metric that typically takes the form of a single survey question asking respondents to rate the likelihood that they would recommend a company, product, or a service to a friend or colleague. The NPS is a proprietary instrument developed by Fred Reichheld, who owns the registered NPS trademark in conjunction with Bain & Company and Satmetrix. Its popularity and broad use have been attributed to its simplicity and transparent methodology of use.
The NPS assumes a subdivision of respondents into "Promoters" who provide ratings of 9 or 10, "Passives" who provide ratings of 7 or 8, and "Detractors" who provide ratings of 6 or lower. Usually, users of the NPS perform a calculation that involves subtracting the proportion of Detractors from the proportion of Promoters collected by the survey item, and the result of the calculation is typically expressed as an integer rather than a percentage. The core How likely would you be to recommend... question is sometimes accompanied by additional open-ended or so-called "driver" questions.
The NPS is typically interpreted and used as an indicator of customer loyalty. In some cases, it has been argued to correlate with revenue growth relative to competitors, although it has also been demonstrated that NPS scores vary substantially between industries. NPS has been widely adopted by Fortune 500 companies and other organizations. Proponents of the Net Promoter approach claim the score can be used to motivate an organization to become more focused on improving products and services.:199–200 As of 2020, versions of the NPS are now used by two-thirds of Fortune 1000 companies.
The origins of NPS as a proprietary instrument date to 2001, at which point Reichwald and Satamatrix built on their earlier, ongoing market research efforts to distill and promote a single survey item that was easy to administer to large numbers of respondents, as well as easy for stakeholders to use and interpret. Early efforts to promote the use of the NPS to corporate clients notably include a 2002 Harvard Business Review article by Reichheld entitled The One Number You Need To Grow.
Predicting customer loyaltyEdit
The primary objective of the Net Promoter Score methodology is to infer customer loyalty (as evidenced by repurchase and referral) to a product, service, brand, or company on the basis of respondents' responses to a single survey item.:49–51:61–65:77–81 For some industries, in particular annuity-based business-to-business software and services, it has been shown that Detractors tend to remain with a company, while Passives are more likely to leave.
As it represents responses to a single survey item, the validity and reliability of any corporation's NPS score ultimately depend on collecting a large number of ratings from individual human users. However, market research surveys are typically distributed by email, and response rates to such surveys have been declining steadily in recent years.   In the face of criticism of the Net Promoter Score, the proponents of the Net Promoter approach claim that the "recommend" question is of similar predictive power to other metrics, but that it presents a number of practical benefits to other more complex metrics. Proponents also argue that analyses based on third-party data are inferior to those conducted by companies on their own customer sets, and that the practical benefits of the approach (including a short survey, a simple concept to communicate, and corporations' ability to follow up with customers) outweigh possible statistical inferiority to other metrics.
While the Net Promoter Score has gained popularity among business executives and is considered a widely used instrument for measuring customer loyalty in practice, it has also generated controversy in academic and market research circles. Scholarly critique has questioned whether the NPS is at all a reliable predictor of company growth. Other researchers have noted that there is no empirical evidence that the "likelihood to recommend" question is a better predictor of business growth than other customer-loyalty questions (e.g., overall satisfaction, likelihood to purchase again, etc.), and that the "likelihood to recommend" question does not measure anything different from other conventional loyalty-related questions. Several studies have shown that there is little statistical difference in reliability, validity, or discriminating power between the NPS and other metrics.
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