Net Promoter Score History
Explore the history of Net Promoter Score, how the metric was introduced, key facts about its methodology, Fred Reichheld’s role in developing it, and major research studies on NPS.
How Net Promoter Score started
Net Promoter Score, or NPS, is a customer loyalty metric built around one recommendation question: how likely someone is to recommend a company, product, or service to a friend or colleague.
According to Wikipedia, the metric was developed by Fred Reichheld and was popularized in his 2003 Harvard Business Review article “The One Number You Need to Grow.”
The core NPS methodology
The standard scoring model groups respondents into promoters, passives, and detractors based on a 0 to 10 rating scale.
The score is calculated by subtracting the percentage of detractors from the percentage of promoters.
| Response | Group | Role in the score |
|---|---|---|
| 9–10 | Promoters | Positive advocates who raise the score |
| 7–8 | Passives | Neutral respondents counted in the sample but not in the formula |
| 0–6 | Detractors | Unhappy respondents who lower the score |
- NPS ranges from -100 to +100.
- A score of +100 means every respondent is a promoter.
- A score of -100 means every respondent is a detractor.
Timeline and adoption facts
Wikipedia traces the origins of NPS to 2003, when Reichheld argued that the recommendation question was a stronger practical predictor of repeat business and word of mouth than several other customer-attitude questions.
The same article notes that NPS later became widely adopted by large companies because the methodology is simple, easy to explain, and easy to track over time.
Wikipedia also notes that, as of 2020, versions of NPS were used by roughly two-thirds of Fortune 1000 companies.
Key studies and research on NPS
The research literature on Net Promoter Score is mixed. Some studies support using NPS as a practical brand-health or loyalty signal, while others argue it is not clearly superior to customer satisfaction or other metrics when predicting business performance.
That balance matters. A strong history page should show both the original case for NPS and the later academic debate around it.
| Year | Study | Main takeaway |
|---|---|---|
| 2003 | Frederick F. Reichheld, The One Number You Need to Grow | Introduced the NPS idea and argued that recommendation intent could serve as a powerful management metric. |
| 2006 | Morgan and Rego, Marketing Science | Found that recommendation-based metrics had little or no predictive value compared with some satisfaction metrics. |
| 2007 | Keiningham, Cooil, Andreassen, and Aksoy, Journal of Marketing | Failed to replicate claims that NPS is clearly superior for predicting firm revenue growth. |
| 2013 | van Doorn, Leeflang, and Tijs, International Journal of Research in Marketing | Concluded that NPS was neither superior nor inferior to other customer metrics and that predictive power for future growth was limited. |
| 2021 | Journal of the Academy of Marketing Science empirical investigation | Argued that changes in NPS can have predictive value under certain conditions, but also confirmed earlier methodological critiques. |
Foundational sources and direct links
Below are some of the most cited and useful sources for understanding the development of NPS and the debate around it.
- Frederick F. Reichheld, The One Number You Need to Grow (Harvard Business Review, December 2003): https://hbr.org/2003/12/the-one-number-you-need-to-grow
- Bain & Company, About the Net Promoter System: https://nps.bain.com/about/
- Bain & Company, The Economics of Loyalty: https://www.bain.com/insights/the-economics-of-loyalty/
- Morgan and Rego, The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Business Performance (Marketing Science, 2006): https://ideas.repec.org/a/inm/ormksc/v25y2006i5p426-439.html
- Keiningham, Cooil, Andreassen, and Aksoy, A Longitudinal Examination of Net Promoter and Firm Revenue Growth (Journal of Marketing, 2007): https://zendy.io/title/10.1509/jmkg.71.3.039
- van Doorn, Leeflang, and Tijs, Satisfaction as a Predictor of Future Performance: A Replication (2013): https://research.rug.nl/en/publications/satisfaction-as-a-predictor-of-future-performance-a-replication/
- The use of Net Promoter Score to predict sales growth: insights from an empirical investigation (Journal of the Academy of Marketing Science, 2021): https://link.springer.com/article/10.1007/s11747-021-00790-2
What the research says in practice
The original practitioner case for NPS was simplicity. Leaders could explain the score easily, compare results across teams, and build operating routines around promoter and detractor feedback.
The academic critique focused on a different question: whether NPS is actually the single best predictor of growth. Several widely cited studies challenged that claim and found that other customer metrics perform similarly or better in some contexts.
More recent research suggests a middle ground. NPS may be useful when teams track changes over time, connect the score to specific operational follow-up, and avoid treating it as a perfect standalone predictor of revenue.
Who is Fred Reichheld?
Fred Reichheld, born in 1952, is an American author, speaker, and business strategist best known for his work on loyalty, retention, and advocacy.
Wikipedia describes him as the creator of the Net Promoter System and notes that he has been a Fellow at Bain & Company, where he has worked since 1977.
He studied at Harvard College and later earned an MBA from Harvard Business School.
Books and ideas associated with Reichheld
Fred Reichheld’s best-known books include The Loyalty Effect, Loyalty Rules!, The Ultimate Question, and The Ultimate Question 2.0.
His later work expanded the discussion beyond the score itself and framed NPS as part of a broader management system focused on customer loyalty and durable growth.
Wikipedia also notes that he published Winning on Purpose in 2021, extending his work on Net Promoter thinking and earned growth.
Important context and criticism
The Wikipedia article on NPS also points out that the metric has critics. Debate has centered on whether one question can fully predict customer loyalty or revenue growth across all industries.
The academic papers by Morgan and Rego in 2006, Keiningham and coauthors in 2007, and van Doorn and coauthors in 2013 are frequently cited in that debate because they question whether NPS is consistently superior to other metrics.
That matters because NPS is best used as one practical signal among several, not as the only measure of customer experience performance.
Source: https://en.wikipedia.org/wiki/Net_promoter_score
- Industry context matters when interpreting a score.
- Survey timing and sampling quality can influence the result.
- Trends over time are often more useful than a single isolated score.
Why the history still matters today
Understanding the history of NPS helps explain why the metric became so popular: it offered a simple framework that leaders could understand quickly and act on consistently.
It also helps explain the limits of the metric. NPS is strongest when teams combine it with open-ended feedback, operational follow-up, and comparisons against their own historical data.
If you want to apply these ideas directly, use the Net Promoter Score Calculator on this site to calculate your own score.
Related pages on Calculator for NPS
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Frequently Asked Questions
Who created Net Promoter Score?
Net Promoter Score was developed by Fred Reichheld and popularized through his 2003 Harvard Business Review article.
When was NPS introduced?
The origins of NPS are commonly traced to 2003, when Reichheld introduced the idea in Harvard Business Review.
What is Fred Reichheld known for?
Fred Reichheld is best known for his research on loyalty and for creating the Net Promoter System.
Is NPS only a metric?
Not always. Reichheld later framed it as part of a broader management approach, often called the Net Promoter System.
What research is most often cited in debates about NPS?
Frequently cited sources include Reichheld’s 2003 Harvard Business Review article, Morgan and Rego’s 2006 Marketing Science paper, Keiningham and coauthors’ 2007 Journal of Marketing paper, van Doorn and coauthors’ 2013 replication study, and a 2021 Journal of the Academy of Marketing Science article that revisited the debate.