What Is Net Promoter Score (NPS)?
A single-question loyalty metric that sorts respondents into Promoters, Passives, and Detractors based on how likely they are to recommend you, then nets the results into one score from -100 to 100.
Net Promoter Score comes from one question: “How likely are you to recommend [company/product] to a friend or colleague?” on a 0–10 scale. Fred Reichheld introduced it in a 2003 Harvard Business Review article, and it’s since become the most widely used loyalty metric in CX and product feedback.
Answers sort into three buckets: 0–6 are Detractors, 7–8 are Passives, and 9–10 are Promoters. The score is Promoters minus Detractors, expressed as a percentage-point difference — not a percentage itself, which is why NPS can run from -100 to 100 rather than 0–100. A score of 100% Promoters and 0% Detractors gives NPS 100; an even split gives NPS 0.
NPS is deliberately a single number, which is both its strength and its most common criticism. It’s easy to track over time and easy to communicate to a board — but on its own, it doesn’t say why people answered the way they did. That’s why most NPS surveys pair the rating with an open-ended follow-up: “What’s the main reason for your score?”
Example
NPS = (120/200) - (30/200) = 60% - 15% = 45.
How to Use NPS in SurveyRock
SurveyRock scores and buckets NPS automatically once you add the standard 0-10 question. Pair it with an open-ended "why" follow-up, and text analysis reads every response — not a sample — to surface the themes behind the score, with an AI executive summary you can hand to stakeholders as-is.
See how text analysis works