Net promoter score

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Net promoter score (NPS) is a market research metric that is based on 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. [1] The NPS is a proprietary instrument developed by Fred Reichheld, who owns the registered NPS trademark in conjunction with Bain & Company and Satmetrix. [2] Its popularity and broad use have been attributed to its simplicity and transparent methodology. [3]

Contents

Methodology

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. Calculating the net promoter score involves subtracting the percentage of detractors from the percentage of promoters collected by the survey item. [2]

The result of the calculation is typically expressed as an integer rather than a percentage.[ citation needed ] The core How likely would you be to recommend... question is almost always accompanied by an open-ended "Why?" and sometimes by so-called "driver" questions. [4]

The NPS is typically interpreted and used as an indicator of customer loyalty. [1] In some cases, it has been argued to correlate with revenue growth relative to competitors within an industry, [5] although it has also been demonstrated that NPS scores vary substantially between industries.[ citation needed ] NPS has been widely adopted by Fortune 500 companies and other organizations. [6] [3] 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. [7] : 199–200  As of 2020, versions of the NPS are now used by two-thirds of Fortune 1000 companies. [8]

A variation on NPS is Employee Net Promoter Score (eNPS), a measure of staff feelings about their workplace.[ citation needed ]

Origins

The origins of NPS date to a 2003 Harvard Business Review article by Reichheld titled "The One Number You Need To Grow". [2]

Predicting customer loyalty

Net Promoter Score (NPS) NetPromoterScore-NPS.png
Net Promoter Score (NPS)

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. [7] : 49–51  [7] : 61–65  [7] : 77–81  [9] 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. [10] 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. [11]

As it represents responses to a single survey item, the validity and reliability of any corporation's NPS 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. [12] [13] 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. [3] 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. [14]

Criticism

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. [3] Scholarly critique has questioned whether the NPS is at all a reliable predictor of company growth. [15] 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. [16]

See also

Citations

  1. 1 2 Project Management Institute 2021, §4.4.4 Other Methods.
  2. 1 2 3 Reichheld, Frederick F. (December 2003). "One Number You Need to Grow". Harvard Business Review . 81 (12): 46–54, 124. PMID   14712543. Archived from the original on 10 March 2013. Retrieved 5 October 2012.
  3. 1 2 3 4 Colvin, Geoff (18 May 2020). "The simple metric that's taking over big business". Fortune. Archived from the original on 3 June 2020. Retrieved 3 June 2020.
  4. ↑ 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. Archived from the original on 19 April 2021. Retrieved 16 April 2021.
  5. ↑ Call Centers for Dummies, By Real Bergevin, Afshan Kinder, Winston Siegel, Bruce Simpson, p.345
  6. ↑ jennymkaplan, Jennifer Kaplan (4 May 2016). "The Inventor of Customer Satisfaction Surveys Is Sick of Them, Too". Bloomberg.com. Archived from the original on 25 September 2016. Retrieved 5 June 2016.
  7. 1 2 3 4 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.
  8. ↑ "The simple metric that's taking over big business". Fortune. Archived from the original on 3 June 2020. Retrieved 6 February 2021.
  9. ↑ Markey, Rob; Reichheld, Fred (23 March 2012). "The Economics of Loyalty". Loyalty Insights. Bain & Company, Inc. Archived from the original on 6 September 2015. Retrieved 9 August 2015.
  10. ↑ "Maurice FitzGerald - Satmetrix". September 2015. Archived from the original on 18 December 2015. Retrieved 11 December 2015.
  11. ↑ 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.
  12. ↑ 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.
  13. ↑ 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.
  14. ↑ "Would You Recommend Us?". Business Week. 29 January 2006. Archived from the original on 7 July 2012.
  15. ↑ 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.
  16. ↑ Hayes (June 2008). "The True Test of Loyalty". Quality Progress: 20–26.

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References

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