NPS vs CSAT vs CES: Questions, Scoring & Examples

Net Promoter Score (NPS) measures willingness to recommend, Customer Satisfaction (CSAT) measures satisfaction with a specified experience and Customer Effort Score (CES) measures task ease or difficulty. Choose the question for the decision. Each needs its own timing, audience, scoring and action; the three numbers cannot simply be combined.

Example: three broadband-service questions

Northline is a hypothetical broadband provider improving customers’ first month. The counts below illustrate scoring; they are not collected customer research.

Its team needs to know whether customers would recommend the service, whether support leaves them satisfied and where router activation requires too much work. Each question needs its own timing, customer group and person responsible for acting on the answer.

Those questions belong at different moments. A recommendation question immediately after a friendly support call may capture gratitude for the agent. An activation-effort question months later relies on distant recall. A satisfaction question that says only “How was your experience?” leaves the customer to choose which experience to rate.

NPS: would customers recommend the service?

The standard NPS question asks how likely someone is to recommend the company, product or service to a friend or colleague, using a 0–10 scale. Scores of 9–10 are promoters, 7–8 are passives and 0–6 are detractors. NPS is the percentage of promoters minus the percentage of detractors, as set out in Bain's measurement guidance.

Suppose Northline receives 200 valid ratings: 90 promoters, 70 passives and 40 detractors.

NPS = (90 ÷ 200 × 100) − (40 ÷ 200 × 100) = +25.

Passives remain in the denominator. Removing them would inflate the result to about +38.5. NPS is a score ranging from −100 to +100; report this example as +25 NPS, rather than “25% satisfaction.”

Survey a defined group of customers who have used the service long enough to have a view on recommending it. Keep the timing and eligibility stable. For Northline, a sample of established customers answers a different question from people who have just activated a router or contacted support.

Ask what drove the rating and check the reasons. Price, connection reliability and complaint handling could all affect recommendation. The score can identify a relationship concern, but it does not identify the cause or establish that someone will actually renew, refer a friend or cancel. Compare it with subsequent behavior where appropriate.

CSAT: were customers satisfied with this experience?

For a support interaction, Northline could ask: “How satisfied were you with the help you received on this request?” Specify whether the intended object is the agent's help, the resolution or the whole contact. They can receive different answers.

A common CSAT format uses a 1–5 scale from very dissatisfied to very satisfied and reports the percentage selecting 4 or 5. Qualtrics' CSAT guidance describes this top-two-response calculation and distinguishes satisfaction with a specific experience from the wider relationship.

If 80 of 100 valid respondents select 4 or 5:

CSAT = 80 ÷ 100 × 100 = 80%.

Use all valid answers to that satisfaction question, including neutral and dissatisfied ratings. Do not restrict the total to positive and negative answers. A mean, such as 4.1 out of 5, is a different summary and needs that label.

For a discrete contact, ask while the interaction is recent. Check separately whether the underlying issue was resolved. A customer might appreciate a helpful agent while waiting for an engineer to restore the connection. Northline would make the wrong operational decision if it treated satisfaction with the conversation as proof that the broadband problem had ended.

Also examine who receives the survey. A trigger that includes only neatly resolved cases can miss customers whose requests remain open or who abandoned the process. Report the eligible contacts and responses so that “80% satisfied” remains a statement about the respondents who answered.

CES: how easy was the task to complete?

CES focuses on a particular interaction or task. Qualtrics' effort-score guidance describes its use after requests, purchases, returns and issue resolution, while the experience is fresh.

Northline could ask after an activation attempt: “How easy or difficult was it to activate your router?” For this program, use 1 = very difficult and 5 = very easy, then report the mean of valid answers. If 80 customers provide ratings that sum to 312:

Mean activation ease = 312 ÷ 80 = 3.9 out of 5. Higher means easier.

Show all rating shares beside the mean. The same average can hide many difficult experiences in one group and mostly neutral ratings in another.

CES is used with different question formats, scale directions and summaries. A question about how much effort someone expended can run in the opposite direction from one asking whether the company made things easy. Some programs report a favorable-response percentage instead of a mean. Record the exact item, anchors and calculation; do not turn 3.9 out of 5 into “78% of customers found activation easy.”

Include failed attempts in the research design. If the survey appears only after successful activation, the customers with the most serious friction may never see it. Compare the survey with activation completion, repeat attempts, time spent and subsequent support contacts.

Three scores, three respondent bases

Northline's three example results have three different bases: 200 recommendation ratings, 100 support-satisfaction ratings and 80 activation-ease ratings. They may concern different people, episodes and periods. There is no meaningful arithmetic in averaging +25, 80% and 3.9 into a single “CX score.”

Keep nonresponses, “not applicable” and incomplete answers separate. They are not zero ratings. A respondent who skips the NPS item but answers CSAT contributes to the CSAT base only. Report responses relative to eligible invitations, and check repeated contacts or multiple responses from the same customer before making customer-level claims.

Suppose 200 of 800 invited customers answer the relationship survey. The response rate is 25%, while NPS remains +25. The matching numbers mean different things. Neither tells you how the 600 nonrespondents would have rated the service.

Keep trend comparisons stable. More password questions and fewer outages may raise CSAT without a policy improvement. Compare issue types, channels and customer stages. Assess uncertainty before treating a small movement as meaningful.

Each score needs an investigation someone can act on

Difficult activation with satisfactory support points toward setup, equipment or the activation process. Check failures and customer accounts before selecting a fix. If activation is easy but recommendation is weak, investigate the wider offer, reliability, price and expectations.

Read explanations beside the numbers. A score tells you that a problem may exist; a useful customer account helps locate the mechanism. Our consumer-insights guide explains how to move from an account to a testable interpretation and a concrete change.

For Northline, Sapien could compare proposed activation instructions with a data-grounded simulated audience and investigate how people interpret each step. Those simulated reactions would inform hypotheses about friction or expectations. Keep them separate from scores collected after actual customer experiences: a simulated recommendation rating isn’t Northline’s customer NPS, and an easy-sounding journey doesn’t establish that its routers activate successfully.

If the immediate decision is how to reduce activation friction, start with a specific effort question and the corresponding behavior. Use CSAT to understand the defined support experience and NPS to track the wider recommendation relationship. Add each measure when someone owns a decision it can inform, then return to customers and observed outcomes to determine whether the change worked.