Net promoter score
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 percentage of detractors from the percentage 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. Employee net promoter score, or in short eNPS, is said to help measure how loyal employees are, similar to NPS. 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 Reichheld and Satmetrix 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. A detractor could be considered a 0-4 score, not necessarily a score of 6 and below.
Predicting customer loyalty
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. The use of the NPS score in addition to revenue retention rates and customer retention rates may offer valuable customer insights and may offer a better predictibility of customer loyalty rates.
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.
NPS scores typically range from -100 to +100.
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.
- Reichheld, Frederick F. (December 2003). "One Number You Need to Grow". Harvard Business Review. 81 (12): 46–54, 124. PMID 14712543.
- Colvin, Geoff (18 May 2020). "The simple metric that's taking over big business". Fortune. Retrieved 3 June 2020.
- "Measuring Your Net Promoter Score℠". Bain. Retrieved 13 February 2021.
- Burnham, Thomas A.; Jefferey A. Wong (2018). "Factors influencing successful net promoter score adoption by a nonprofit organization: a case study of the Boy Scouts of America". International Review on Public and Nonprofit Marketing. 15 (4): 475–495. doi:10.1007/s12208-018-0210-x. S2CID 169663147.
- "How Does Employee NPS Matter? The Ultimate Guide to Enps". 25 August 2019.
- Call Centers for Dummies, By Real Bergevin, Afshan Kinder, Winston Siegel, Bruce Simpson, p.345
- "Net Promoter Score - The Ultimate Guide | Feedough". Retrieved 13 February 2021.
- jennymkaplan, Jennifer Kaplan. "The Inventor of Customer Satisfaction Surveys Is Sick of Them, Too". Bloomberg.com. Retrieved 5 June 2016.
- Reichheld, Fred; Markey, Rob (2011). The Ultimate Question 2.0: How Net Promoter Companies Thrive in a Customer-Driven World. Boston, Mass.: Harvard Business Review Press. p. 52. ISBN 978-1-4221-7335-0.
- "The simple metric that's taking over big business". Fortune. Retrieved 6 February 2021.
- Markey, Rob; Reichheld, Fred (23 March 2012). "The Economics of Loyalty". Loyalty Insights. Bain & Company, Inc. Retrieved 9 August 2015.
- "Maurice FitzGerald - Satmetrix". September 2015. Archived from the original on 18 December 2015. Retrieved 11 December 2015.
- Wierckx, Patrick J. (11 October 2020). "The Retention Rate Illusion - Understanding the Relationship between Retention Rates and the Strength of Subscription-Based Businesses". Journal of Applied Business and Economics. Rochester, NY. SSRN 3629281.
- Sheehan, Kim Bartel (23 June 2006). "E-mail Survey Response Rates: A Review". Journal of Computer-Mediated Communication. 6 (2): 0. doi:10.1111/j.1083-6101.2001.tb00117.x. ISSN 1083-6101.
- Boyle, John; Berman, Lewis; Dayton, James; Iachan, Ronaldo; Jans, Matt; Zuwallack, Randy (5 August 2020). "Physical measures and biomarker collection in health surveys: Propensity to participate". Research in Social and Administrative Pharmacy. 17 (5): 921–929. doi:10.1016/j.sapharm.2020.07.025. ISSN 1551-7411. PMID 32800458.
- "Would You Recommend Us?" Business Week, 29 January 2006.
- "How To Use Your Net Promoter Score (NPS) Effectively In Health Care, August 2021.
- Atilla Wohllebe; Florian Ross; Szilárd Podruzsik (November 2020). "Influence of the net promoter score of Retailers on the Willingness of Consumers to Install Their Mobile App". International Journal of Interactive Mobile Technologies. 14 (19): 124–139. doi:10.3991/ijim.v14i19.17027.
- Timothy L. Keiningham; Bruce Cooil; Tor Wallin Andreassen; Lerzan Aksoy (July 2007). "A Longitudinal Examination of Net Promoter and Firm Revenue Growth" (PDF). Journal of Marketing. 71 (3): 39–51. doi:10.1509/jmkg.71.3.39. S2CID 54726616. Archived from the original (PDF) on 16 July 2020.
- Hayes (2008), "The True Test of Loyalty," Quality Progress, June 2008, 20–26.
- Preston, Carolyn C.; Colman, Andrew M. (14 September 1999). "Optimal number of response categories in rating scales: reliability, validity, discriminating power, and respondent preferences" (PDF). Acta Psychologica. 104 (1): 1–15. doi:10.1016/s0001-6918(99)00050-5. hdl:2381/3937. PMID 10769936.