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Glossary · Metrics

Net Promoter Score.

A widely used customer loyalty metric calculated from a single 0–10 "likelihood to recommend" question. Net Promoter Score, NPS, and Net Promoter are registered trademarks.

Definition

Net Promoter Score (NPS) is a customer loyalty metric derived from one survey question: "How likely are you to recommend this company or product to a friend or colleague?" on a 0–10 scale. Respondents are grouped into Promoters (9–10), Passives (7–8), and Detractors (0–6). NPS = % Promoters − % Detractors, producing a number from −100 to +100.

Definition

NPS was introduced by Fred Reichheld in a 2003 Harvard Business Review article, "The One Number You Need to Grow." It is calculated from responses to a single question — "On a scale of 0 to 10, how likely are you to recommend [company/product] to a friend or colleague?" — with an optional open-ended follow-up: "What is the main reason for your score?"

Respondents are classified as Promoters (9–10), Passives (7–8), or Detractors (0–6). The score is the percentage of Promoters minus the percentage of Detractors. Passives are counted in the base but excluded from the numerator. The result ranges from −100 (every respondent is a Detractor) to +100 (every respondent is a Promoter).

Why it matters

NPS remains the most common customer loyalty metric reported at board level. Its strengths are simplicity, benchmark availability, and the paired open-text "why" that gives a VoC program qualitative feedback alongside the number. Its weaknesses are response-scale cultural bias (promoters skew higher in some markets than others), sensitivity to sample composition, and overuse as a target that then drives gaming behavior rather than improvement.

For consumer brands selling through retail, NPS is rarely available at the SKU level because the survey is run by the brand, not the retailer. That gap is why complementary metrics — CSAT on direct interactions, Net Sentiment Score on review corpora, return rate per SKU — are usually tracked alongside it.

Example

A beauty brand emails 5,000 customers a 30-day post-purchase survey. 2,100 respond. Among them, 950 score 9 or 10 (Promoters), 640 score 7 or 8 (Passives), and 510 score 0–6 (Detractors). NPS = (950 / 2,100) − (510 / 2,100) = 45.2% − 24.3% = 21.

The open-text responses cluster into three themes on the Detractor side — "shade match wrong," "arrived leaking," "scent changed from last purchase." The brand routes the shade theme to its R&D group, the leaking theme to packaging engineering, and the scent theme to QA. A month later a follow-up cohort shows NPS at 26, with the packaging theme down 40%.

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See the "why" behind the number.

A score alone does not fix a product. Indellia ingests the open-text responses, links them to SKUs, and routes themes to the team that can change something. Unlimited users, unmetered data.