Use CSAT when you need to know how a customer felt about a specific interaction, product, or service. Use NPS when you need a broader read on whether customers would recommend the organization. The two measures answer different questions, so choose the one that matches the decision you have to make. Run both only when you can act on what each one tells you.
What each metric asks
CSAT: satisfaction with a defined experience
CSAT (customer satisfaction score) asks how satisfied a customer was with a particular product, service, or interaction. The question is anchored to something that just happened, such as a support ticket, a checkout, or an onboarding call.
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CSAT has no single fixed formula. The result depends on two choices the surveyor makes: the response scale and the rule for what counts as “satisfied.” SurveyMonkey’s June 8, 2026 metric comparison illustrates one common convention: on a 1–5 scale, count the 4 and 5 ratings, divide by the total number of responses, and multiply by 100. That is an example of a convention, not a universal standard. If you publish or compare CSAT figures, state the question wording, the scale, and the satisfied cutoff alongside the number. Otherwise a figure such as “82%” cannot be interpreted.
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Worked arithmetic with hypothetical numbers: if 200 customers answer a 1–5 question, 164 of them give a 4 or 5, and the score is calculated with that convention, CSAT is 164 ÷ 200 × 100 = 82%. A different team counting only 5s would report a much lower figure from the same answers, which is why the cutoff matters.
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NPS: likelihood to recommend
Bain & Company’s standard NPS (Net Promoter Score) question is: “How likely are you to recommend us to a friend or colleague?” Respondents choose a whole number from 0 to 10. Bain groups them as follows:
- Promoters: scores of 9 or 10
- Passives: scores of 7 or 8
- Detractors: scores of 0 through 6
The score is the percentage of promoters minus the percentage of detractors. Passives count toward the total base but are not subtracted. Because the result is a difference of two percentages, it runs from −100 to +100. Bain’s methodology page puts it directly: the score is “simply the percentage of customers who are promoters (those who scored 9 or 10) minus the percentage who are detractors (those who scored 0 to 6).”
Worked arithmetic with hypothetical numbers: if 50% of respondents are promoters and 20% are detractors, the NPS is +30. The same +30 could come from very different customer bases, which is one reason NPS should be read with its collection context.
Bain also asks that teams state which kind of NPS they are measuring: after an individual experience or journey, at the relationship or brand level, or competitively. A relationship-level score and a post-support score are different instruments, even though both use the same 0–10 question.
Side by side
| Decision axis | CSAT | NPS |
|---|---|---|
| Main question | How satisfied were you with this product, service, or interaction? | How likely are you to recommend us to a friend or colleague? |
| Scope | A specific product, transaction, or service encounter | A broader brand or customer relationship; can also be collected at a defined journey point |
| Typical timing | Soon after the interaction, while details are fresh | Periodically for relationship sentiment, or at a clearly defined journey point |
| Useful action | Find and fix a specific experience or service problem | Track advocacy or loyalty signals and investigate the reasons behind them |
| Scoring | Depends on the chosen scale and the satisfied-response convention | Percentage of promoters minus percentage of detractors on the 0–10 scale |
| Main interpretation risk | Figures are misleading when the scale or satisfied cutoff is not disclosed | A single recommendation answer is not the whole relationship, and raising the score is not the goal in itself |
Sources for the comparison: Bain & Company’s NPS methodology guidance and SurveyMonkey’s June 8, 2026 metric comparison.
How to choose
Start with the decision you need to make, then pick the metric that can inform it.
- Choose CSAT when the question is “Did this specific thing work for the customer?” Examples include a support resolution, a delivery, a booking, or a setup session. Ask shortly after the event.
- Choose NPS when the question is “Are customers likely to vouch for us, and is that changing?” Examples include a quarterly relationship survey or a survey sent at a defined point in a long customer journey.
- Choose both only when each feeds a separate decision. For example, a support manager uses CSAT to review ticket quality, while a leadership team uses NPS to track relationship health.
Two worked setups
Post-support CSAT
After a support case closes, send one question: “How satisfied were you with the support you received today?” on a 1–5 scale. Report the percentage of 4 and 5 responses, state that convention in the report, and read the open-text comments for the specific failure. A falling CSAT on the billing queue points to a process to fix; it does not tell you whether customers would recommend the company.
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Send the standard recommendation question to a defined customer group on a fixed schedule, for example every quarter, and label the result as relationship-level NPS. Compare the same group over time rather than comparing it with a different group or a different collection method. Pair the score with a follow-up question asking why the customer gave that score, so the number has a reason attached.
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- Map each survey to one decision and one owner before you write the questions.
- Avoid asking the same customer a CSAT question and an NPS question about the same interaction in the same week.
- Use CSAT for transactional follow-up and NPS for periodic relationship checks, so the two do not compete for attention.
- Keep the scale, the satisfied cutoff, and the NPS measurement type documented in one place, so that the figures stay comparable across reports.
What the evidence does and does not show
Bain’s case-study history
Bain’s history of the metric reports a comparison across 14 industry case studies. In 11 of them, likelihood to recommend was the strongest question for predicting customer behavior. In two of the remaining three, another question performed better, but likelihood to recommend was close. Bain’s page does not give a study year, so the comparison should be cited as Bain’s own account of its research, with no year assigned. It is the originator’s evidence, not an independent test, and it does not establish that NPS predicts growth in every organization.
The validity debate
The metric’s predictive value is contested. In a 2018 arXiv preprint titled “What is Wrong with Net Promoter Score,” Nicholas I. Fisher and Raymond E. Kordupleski argue that NPS has weaknesses as a high-level market research measure. The abstract is strongly critical. It shows that serious researchers dispute the measure, but it is not a full independent evaluation that settles the comparison.
Why one score is not the whole picture
Bain itself warns against treating NPS as the objective. In a Bain-published article, Fred Reichheld, a Bain Fellow, writes: “The goal of the Net Promoter System® is not to increase your Net Promoter Score.” He also argues that one survey answer at one moment may not capture the whole relationship, and that direct feedback should be combined with operational and behavioral signals such as repeat purchases or service contacts. Those signals are useful context, but no source here validates them as a substitute for survey data in every setting.
No universal benchmark
There is no cross-industry “good score” that can be verified from these sources. CSAT and NPS levels vary by industry and by how the survey was collected, so a target copied from another company or sector will not tell you much about your own results.
Practical rules for reporting either metric
- State the question wording, the scale, and the collection timing with every score.
- For CSAT, disclose the satisfied cutoff. For NPS, disclose the measurement type.
- Track open-text reasons alongside the number, because a score alone does not identify the cause.
- Judge trends within the same group and method, not across different surveys.
If one metric is chosen, make it the one tied to the decision you have to make. Measuring both is worthwhile only when each one changes what your team does next.
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