Customer satisfaction metrics explained

Get the right score for the right job

Use our free calculator to get your NPS, CSAT, CES, UMUX, and Product-Market Fit scores - and learn what each one actually tells you.

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At a glance: which metric does what?

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The score is just the start: choose the right metric, then go deeper

Most people know NPS. Fewer know when (or how) to use it well. And almost no one asks the follow-up question that actually unlocks insight.

This guide is here to fix that.

We'll walk through five essential metrics - what they're for, when to use them, and where they mislead. Then we'll show you why scores are just a starting point. To get real insight, you need to ask, "Why?" - and use a tool like AddMaple to make sense of the answers.

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NPS: the loyalty signal everyone knows

What it is Net Promoter Score asks one simple question:

"How likely are you to recommend [product/brand] to a friend or colleague?"

Respondents answer on a 0–10 scale. You subtract the percentage of detractors (0–6) from promoters (9–10). The result is your NPS.

Why it exists Developed by Bain & Company in the early 2000s as a simple, standardized way to measure brand loyalty.

When to use it When you want a benchmark of overall customer sentiment, or you need to compare across products or companies.

Strengths Familiar. Easy to track over time. Great for external comparisons.

Weaknesses Lacks context. Can be gamed by timing or audience. Doesn't tell you why someone gave their score.

Our take NPS is overused and misinterpreted. It's fine as a benchmark - but it tells you nothing on its own. Always pair it with:

"Why did you give that score?"

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CSAT: did this interaction go well?

What it is Customer Satisfaction Score (CSAT) is usually phrased like this:

"How satisfied were you with [interaction/product/experience]?"

Rated on a 1–5 or 1–7 scale.

Why it exists It's one of the oldest feedback metrics - designed to capture immediate satisfaction.

When to use it Right after specific interactions: support tickets, feature use, purchases.

Strengths Fast. Simple. Familiar. Great for transactional insights.

Weaknesses Highly subjective. Influenced by expectations and cultural norms. Poor predictor of long-term behavior.

Our take Use it for micro-moments, not macro-trends. Always follow up with:

"What could we have done better?"

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CES: how hard was that?

What it is Customer Effort Score measures how easy it was to complete a task. The original phrasing:

"How much effort did it take to resolve your issue today?" Usually answered on a 1–7 scale (lower effort = better).

Why it exists CEB (now Gartner) found that reducing effort builds loyalty more effectively than delighting customers.

When to use it After service interactions, account setup, cancellations, or returns.

Strengths Highly predictive of churn. Excellent for diagnosing service flows.

Weaknesses Doesn't explain what made something hard. Only works in task-based contexts.

Our take If you're not using CES in your support funnel, you're missing huge signals. Pair it with:

"What made this harder than expected?"

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UMUX: the underrated UX MVP

What it is The Usability Metric for User Experience uses 2–4 Likert questions to measure perceived ease of use and usefulness. The short version:

"[Product] is easy to use." "[Product] meets my needs."

Scored on a 1–7 scale and normalized to 0–100.

Why it exists Created as a faster, more actionable alternative to SUS (System Usability Scale).

When to use it After product interactions, usability tests, or design sprints.

Strengths Compact. Validated. Correlates with satisfaction and loyalty.

Weaknesses Still needs interpretation. Less widely known.

Our take UMUX should be your default for UX research. It's lean, reliable, and modern. Ask alongside:

"What would you improve first?"

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PMF Score: do users actually need this?

What it is The Product-Market Fit Score is based on Sean Ellis's golden question:

"How would you feel if you could no longer use this product?" Options: Very disappointed, Somewhat disappointed, Not disappointed.

Your PMF Score is the % of users who answer "Very disappointed."

Why it exists To help startups gauge traction and product indispensability.

When to use it During early validation, pivots, or post-MVP testing.

Strengths Blunt but powerful. Strong signal when asked at the right time.

Weaknesses Less useful for mature products. Score depends heavily on your sample.

Our take It's a sharp knife - don't use it for butter. Follow up with:

"What would you use instead if this didn't exist?"

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Which one should you use?