Net Promoter


Net Promoter or Net Promoter Score 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 is claimed to be correlated with revenue growth. NPS has been widely adopted with more than two thirds of Fortune 1000 companies using the metric. The tool aims to measure 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. An NPS can be as low as −100 or as high as +100. NPS scores vary across different industries, but a positive NPS is generally deemed good, a NPS of +50 is generally deemed excellent, and anything over +70 is exceptional.
The metric was developed by Fred Reichheld, Bain & Company and Satmetrix. It was introduced by Reichheld in his 2003 Harvard Business Review article, "The One Number You Need to Grow". Its popularity and broad use have been attributed to its simplicity, as well as the fact that it was made openly available.

How it works

The Net Promoter Score is calculated based on responses to a single 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.
Those who respond with a score of 9 to 10 are called Promoters, and are considered likely to exhibit value-creating behaviors, such as buying more, remaining customers for longer, and making more positive referrals to other potential customers. Those who respond with a score of 0 to 6 are labeled Detractors, and they are believed to be less likely to exhibit the value-creating behaviors. Responses of 7 and 8 are labeled Passives, and their behavior falls between Promoters and Detractors. The Net Promoter Score is calculated by subtracting the percentage of customers who are Detractors from the percentage of customers who are Promoters. For purposes of calculating a Net Promoter Score, Passives count toward the total number of respondents, thus decreasing the percentage of detractors and promoters and pushing the net score toward 0.
Companies are encouraged to follow the likely-to-recommend 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. The open-ended question is often a conditional one meaning that it only appears if the customer gives below a certain threshold, such as below 7. 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.
Reichheld and Co-Author, Rob Markey say the rating and answers to the "Why?" question provide all that is needed to identify reference customers and improvement opportunities. Practitioners often claim that responses to the "Why" question provide more important information than the score, itself. USAA and Verizon, for example, both claim that the score is less important than the reasons why. For some, the lack of any easy way to automatically analyze the verbatim answers without human bias is problematic. Others, such as Dell or Intuit, claim that technology helps analyze the verbatim responses effectively.
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. Companies using the Net Promoter System often rely on software as a service vendors that offer a full suite of metrics, reporting, and analytics.
The primary objective of the Net Promoter Score methodology is to predict customer loyalty to a product, service, brand, or company. Reichheld and Markey developed the methodology by comparing the ability of several different questions to predict future purchases and referrals of individual respondents. They chose the likelihood to recommend question based on the observation that it best predicted these customer behaviors in 11 of 14 industries studied. They also found that differences in Net Promoter Scores among direct competitors in a market could explain substantial differences in revenue growth rates among competitors in that market. Importantly, Markey points out that "competitive benchmark" Net Promoter Scores collected through a carefully constructed double-blind Quantitative marketing research methodology provide the only valid basis for comparing scores.
Net Promoter System also requires a process to close the loop. In closing the loop, the provider actively intervenes to learn more from customers who have provided feedback, and also to change a negative perception, often converting a Detractor into a Promoter. The Net Promoter survey will identify customers who need follow-up, including Detractors, and should automatically alert the provider to contact the consumer and manage the follow-up and actions from that point, a practice followed by companies such as Scotiabank.
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. The Net Promoter approach has been adopted by several companies, including Australia Post, Siemens, E.ON, Philips, GE, Apple Retail, American Express, IBM, Vanguard, and Intuit. It has also emerged as a way to measure loyalty for online applications, as well as social game products.
Some proponents of the Net Promoter Score suggest that the same methodology can be used to measure, evaluate and manage employee loyalty. They claim that collecting the feedback from employees in a manner similar to Net Promoter customer feedback can provide companies a way to improve their culture. What is sometimes called the "employee Net Promoter Score" or eNPS has been compared to other employee satisfaction metrics and some companies have claimed that it correlates well with those other metrics.
For some industries, notably software and services, it has been shown that Detractors tend to remain with a company and Passives leave. This appears to be the case where switching barriers are relatively high.
In the face of criticisms 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 of similar predictive power to other metrics, but fail to address its practical benefits, which are at the heart of the argument Reichheld put forth. Proponents also counter 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 outweigh any statistical inferiority. They also allow that a survey using any other question can be used within the Net Promoter System, as long as it meets the criteria of sorting customers reliably into promoters, passives and detractors.

Criticism of NPS

While the Net Promoter Score has gained popularity among business executives, it has also attracted controversy from academic and market research circles.

Lack of superiority to other loyalty-related questions

Research by Keiningham, Cooil, Andreassen and Aksoy disputes that the Net Promoter metric is the best predictor of company growth. Furthermore, Hayes claimed there was no scientific evidence that the "likelihood to recommend" question is a better predictor of business growth than other customer-loyalty questions. Specifically, Hayes stated that the "likelihood to recommend" question does not measure anything different from other conventional loyalty-related questions.
The customer metrics included in this study perform equally well in predicting current company performance."

No evidence for 11 point scale superiority

While several studies, such as one by Preston and Colman, have shown that there is little statistical difference in reliability, validity, or discriminating power, an unpublished paper by Schneider et al found a more nuanced pattern. Out of four scales tested in two studies, the 7-point was a slightly better predictor of stated historical recommendations than the 11-point scale advocated by Reichheld.

Reliability compared to a composite index of questions

"A single item question is much less reliable and more volatile than a composite index."
"Furthermore, combining CFMs, along with simultaneously investigating multiple dimensions of the customer relationship, improves
predictions even further."

Lack of predictive power for 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."
"…given the present state of evidence, it cannot be recommended to use the NPI as a predictor of growth nor financial performance."