Net Promoter

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Net Promoter or Net Promoter Score (NPS) is a management tool that can be used to gauge the loyalty of a firm's customer relationships. It serves as an alternative to traditional customer satisfaction research and claims to be correlated with revenue growth.[1]

Overview[edit]

"Net Promoter Score" is a customer loyalty metric developed by (and a registered trademark of) Fred Reichheld, Bain & Company, and Satmetrix. It was introduced by Reichheld in his 2003 Harvard Business Review article "One Number You Need to Grow".[2] NPS can be as low as −100 (everybody is a detractor) or as high as +100 (everybody is a promoter). An NPS that is positive (i.e., higher than zero) is felt to be good, and an NPS of +50 is excellent.

Net Promoter Score (NPS) measures the loyalty that exists between a provider and a consumer. The provider can be a company, employer or any other entity. The provider is the entity that is asking the questions on the NPS survey. The consumer is the customer, employee, or respondent to an NPS survey.

A note on source criticism[edit]

When it comes to the information provided from the proponents of the Net Promoter Score (for example "The Ultimate Question 2.0" is used in reference in the article) it is important to note that proponents of the Net Promoter Score are promoting their own work in those books and may also be criticizing other ways of measuring.

How It Works[edit]

NPS is based on a direct question: How likely is it that you would recommend our company/product/service to a friend or colleague? The scoring for this answer is most often based on a 0 to 10 scale.[3]

Promoters are those who respond with a score of 9 or 10 and are considered loyal enthusiasts. Detractors are those who respond with a score of 0 to 6 - unhappy customers. Scores of 7 and 8 are passives, and they will only count towards the total number of respondents, but not directly affect the formula. NPS is calculated by subtracting the percentage of customers who are Detractors from the percentage of customers who are Promoters.[4]

Companies are encouraged to follow the direct question with an open-ended request for elaboration, soliciting the reasons for a customer's rating of that company or product. These reasons can then be provided to front-line employees and management teams for follow-up action.[2] Local office branch managers at Charles Schwab Corporation, for example, call back customers to engage them in a discussion about the feedback they provided through the NPS survey process, solve problems, and learn more so they can coach account representatives.[5]

Additional questions can be included to assist with understanding the perception of various products, services,and lines of business. These additional questions help a company rate the relative importance of these other parts of the business in the overall score. This is especially helpful in targeting resources to address issues that most impact the NPS. The NPS marketplace is dominated by providers that offer a full suite of metrics, reporting, analytics, best practices and consulting services. In the most advanced systems promoters are given the opportunity to promote immediately using social media connectors.[6]

The primary purpose of the NPS methodology is to evaluate customer loyalty to a brand or company, not to evaluate their satisfaction with a particular product or transaction. The ability to measure customer loyalty is a more effective methodology to determine the likelihood that the customer will buy again, talk up the company and resist market pressure to defect to a competitor.[7] Measuring loyalty can be done in several ways and when it comes to giving recommendations "satisfaction" and "liking" are better predictors of recommendations than "likelihood to recommend.[8]

Recommend intention alone will not suffice as a single predictor of customers' future loyalty behaviors. Use of multiple indicators instead of a single predictor model performs significantly better in predicting customer recommendations and retention.[9]

Net Promoter methodology also includes a process to close the loop. Closing the loop is a process by which the provider actively intervenes to change a negative perception and convert a detractor into a promoter. In order to do this the survey respondent can not be anonymous, something that can have a negative impact in the willingness tor take the survey or to give low grades. The Net Promoter survey will identify a detractor and should automatically alert the provider to contact the consumer and manage the followup and actions from that point.

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 for consumers.[10] They further claim that a company's Net Promoter Score correlates with revenue growth. Discussed at length in The Ultimate Question: Driving Good Profits and True Growth by Fred Reichheld, and "Answering the Ultimate Question" by Satmetrix Executives Richard Owen and Laura Brooks, the Net Promoter approach has been adopted by several companies, including E.ON, Philips, GE,[11] Apple Retail,[12] American Express, and Intuit.[13] It has also emerged as a way to measure loyalty for online applications, as well as social game products.[14]

A customer is able to leave comments in the surveys sent to them. This is what allows a company to use the VOC (Voice of Customer) to ensure that company is meeting the expectations.

Proponents of Net promoter score also suggest that the same methodology can be used to measure and evaluate employee satisfaction with their employer and that tracking and managing the internal score is a way that companies can keep a focus on their culture. This measures more than just an employee's satisfaction with common KPI (key performance indicator) points in the company (what more is unclear). It claims expands to include the importance of various factors rather than just focusing on list of workplace issues to improve.[15]

Criticism of NPS[edit]

Despite the lack of support in form of scientific studies NPS have gained popularity among business executives. The Net Promoter concept has attracted some controversy from academic and market research circles. Research by Keiningham, Cooil, Andreassen and Aksoy disputes that the Net Promoter metric is the best predictor of company growth.[16]

Does not ad anything compared to other loyalty-related questions Furthermore, Russell Hayes (2008) claimed there was no scientific evidence that the "likelihood to recommend" question is a better predictor of business growth compared to other customer-loyalty questions (e.g., overall satisfaction, likelihood to purchase again). Specifically, Hayes stated that the "likelihood to recommend" question does not measure anything different from other conventional loyalty-related questions.[17]

Performs Worse than Satisfaction & Liking Questions "Satisfaction" and "liking" are better predictors of recommendations than "likelihood to recommend". - The paper "Measuring Customer Satisfaction and Loyalty. [18]

Influenced by environmental factors Environmental factors may exert an influence on customers' response to the "recommend" question—making comparisons across business units or industries difficult in certain cases. Examples include comparing businesses with an associated social stigma (e.g., cigarettes or online dating) and businesses with different levels of service fulfillment (e.g., delivery services as compared to gyms). Moreover, determining when the survey should be delivered may be more obvious in some cases than in others (such as in the case of a gym), where customer attitudes may be likely to change over time.[citation needed]

Uses a scale of low predictive validity Daniel Schneider, Jon Krosnick, et al. found that out of four scales tested, the 11-point scale advocated by Reichheld had the lowest predictive validity of the scales tested.[19]

Culturally-insensitive The validity of NPS scale cut-off points across industries and cultures has also been questioned.[20]

Loss of information Others have taken issue with the calculation methodology, claiming that by collapsing an 11-point scale to three components (e.g., Promoters, Passives, Detractors), significant information is lost and statistical variability of the result increases.[13] </ref>

Doesn't Accurately Differentiate Promoters and Detractors "The rule-of-thumb score classes proposed by Reichheld (promoters are those respondents who give a likelihood of recommendation of 9 or 10 while the detractors give 6 or less) are not supported statistically, mask important changes and potentially mislead management that there is negative NPS when this may not be the case." [21]

Less Accurate than Composite Index of 3 Questions "A single item question is much less reliable and more volatile than a composite index." [22]

Fails to Predict Loyalty Behaviors "Recommend intention alone will not suffice as a single predictor of customers' future loyalty behaviors. Use of multiple indicators instead of a single predictor model performs significantly better in predicting customer recommendations and retention." [23]


Despite all these shortcoming of the Net promoter score the proponents of the Net Promoter approach claim that the statistical analyses presented prove only that the "recommend" question is similar in predictive power to other metrics, but fail to address the practical benefits of the approach, which are at the heart of the argument Reichheld put forth. Proponents of the approach also counter that analyses based on third-party data are inferior to analyses conducted by companies on their own customer sets, and that the practical benefits of the approach (short survey, simple concept to communicate) outweigh any statistical inferiority of the approach.[13] However a survey using any other question can be use the same approach.

See also[edit]

References[edit]

  1. ^ Call Centers for Dummies, By Real Bergevin, Afshan Kinder, Winston Siegel, Bruce Simpson, p.345
  2. ^ a b Reichheld, Frederick F. (December 2003). "One Number You Need to Grow". Harvard Business Review. 
  3. ^ The Ultimate Question 2.0 p 12
  4. ^ The Official Net Promoter web site, The Net Promoter Score and System
  5. ^ Markey, Rob; Fred Reichheld; Andreas Dullweber (December 2009). "Closing the Customer Feedback Loop". Harvard Business Review. 
  6. ^ The Ultimate Question 2.0 P 48-49
  7. ^ Answering the Ultimate Question
  8. ^ "Measuring Customer Satisfaction and Loyalty: Improving the ‘Net-Promoter' Score" by Daniel Schneider, Matt Berent, Randall Thomas and Jon Krosnick ".
  9. ^ The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Customer Retention, Recommendation, and Share-of-Wallet" (Timothy L. Keiningham, Bruce Cooil, Lerzan Aksoy, Tor W. Andreassen, Jay Weiner).
  10. ^ Net Promoter Score
  11. ^ "With Its Stock Still Lackluster, G.E. Confronts the Curse of the Conglomerate," New York Times, 16 August 2006
  12. ^ "Another Myth Bites The Dust: How Apple Listens To Its Customers," Forbes.com, 26 August 2011
  13. ^ a b c "Would You Recommend Us?" Business Week, 29 January 2006.
  14. ^ "Net Promoter Score for Social Gaming," 28 February 2011.
  15. ^ The Ultimate Question 2.0 p.165
  16. ^ Timothy L. Keiningham; Bruce Cooil; Tor Wallin Andreassen; Lerzan Aksoy (July 2007). "A Longitudinal Examination of Net Promoter and Firm Revenue Growth". Journal of Marketing 71 (3): 39–51. doi:10.1509/jmkg.71.3.39. 
  17. ^ Hayes (2008), "The True Test of Loyalty," Quality Progress, June 2008, 20–26.
  18. ^ ‘Net-Promoter' Score" Daniel Schneider, Matt Berent, Randall Thomas and Jon Krosnick
  19. ^ Schneider, Daniel; Berent, Matt; Thomas, Randall; Krosnick, Jon (2007): "Measuring Customer Satisfaction and Loyalty: Improving the 'Net-Promoter' Score"; paper presented at the Annual Conference of the World Association for Public Opinion Research (WAPOR); Berlin (Germany)
  20. ^ "Customer advocacy metrics: the NPS theory in practice" Admap, February, 2008.
  21. ^ - Ken Roberts, Forethought Research Australia.
  22. ^ - Customer Satisfaction - The customer experience through the customer's eyes, Nigel Hill, Greg Roche and Rachel Allen, p. 7
  23. ^ - "The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Customer Retention, Recommendation, and Share-of-Wallet" (Timothy L. Keiningham, Bruce Cooil, Lerzan Aksoy, Tor W. Andreassen, Jay Weiner).

External links[edit]