What is a good CSAT score?
Short answer
· 5 min read
How is a CSAT score calculated?
Here is how to calculate CSAT: a CSAT score is calculated by dividing satisfied responses by total responses and multiplying by 100. On a 5-point scale, satisfied responses are usually the top two ratings, 4 and 5, a convention called top-two-box.
Example: a team collects 500 post-contact surveys, and 420 respondents rate the interaction 4 or 5. CSAT = (420 / 500) x 100 = 84 percent.
Switch to top-box only, counting just the rating of 5, and the same 500 responses might yield 310 satisfied answers: (310 / 500) x 100 = 62 percent. Nothing about customer sentiment changed. Only the counting rule did, which is why that rule has to be fixed before comparing scores across periods or teams.
What is a good CSAT score compared to industry benchmarks?
No universal good CSAT score exists across industries, but support teams commonly use the ranges below as working conventions.
Range | What it usually signals | What to check next |
|---|---|---|
Below 60% | A breakdown tied to a specific issue or repeat contact reason | Group low-score comments by topic and look for the one or two causes driving the drag |
60-74% | Inconsistent experience | Segment by channel and contact reason to find what is pulling the average down |
75-85% | The commonly cited good CSAT score range for transactional support | Confirm it holds across channels, not just one strong segment |
Above 85% | Strong performance by convention | Check response rate and sample size before trusting the number |
The American Customer Satisfaction Index (ACSI) reported a national U.S. score of 76.9 out of 100 for the fourth quarter of 2025. That is not a CSAT benchmark in the transactional sense: ACSI builds a 0-100 index from a large modeled sample, while CSAT is a percentage built from top-box or top-two-box answers to a single post-contact question. Treating a 76.9 ACSI score as equivalent to a 76.9 percent CSAT score misreads both.
Average CSAT score by industry also varies for reasons that have nothing to do with service quality. A billing dispute carries different stakes than a product question. A quick chat resolution and a long phone escalation produce different emotional starting points. Survey timing and CSAT response rate shift results further: a low response rate narrows the sample to the most frustrated and most satisfied customers, pushing the score toward the extremes.
How do I judge whether my own CSAT score is healthy?
Your own CSAT score is healthy when it holds steady or improves against your own baseline, segmented by channel and contact reason, with enough responses behind each reading to trust it.
Fix the counting rule and survey trigger first: decide what counts as satisfied and when the survey fires, then lock both before comparing periods.
Set a baseline from a full recent period, such as a rolling 90 days, not a single week that one outage can skew.
Segment the baseline by channel and contact reason, since billing disputes, technical escalations, and simple status checks carry different baseline expectations.
Set a minimum response count per segment. A sample of around 100 responses carries a margin of error near 13 percent at 95 percent confidence, while 400 to 500 responses brings that down to roughly 4 to 5 percent.
Track the trend against your own baseline, not a published benchmark. To improve CSAT score when it drops, group the low-score comments into causes, read the conversations behind them through root cause analysis, fix the issue, then re-measure.
Teams with no CSAT process yet should start smaller: one post-contact question, one clear scale, and a stated minimum response threshold before reading results as a trend. No CSAT move counts as a win until it is tied to a specific topic or change.
How does OnClarity help with this?
Tying a CSAT drop to its cause is where most teams get stuck without full conversation data. OnClarity (www.onclarity.com) Voice of Customer reads 100 percent of conversations across calls, chats, tickets, reviews, surveys and social, and ties CSAT and NPS movements to specific topics and root causes. Copilot answers questions in plain language over that full dataset, and alerts flag a topic the moment it starts trending.
OnClarity analyses survey results; it does not send or build surveys. OnClarity is SOC 2 Type II certified, GDPR and HIPAA Ready, and Saudi PDPL aligned.
Frequently asked questions
Is 80 percent a good CSAT score?
Yes, by the commonly used convention, 80 percent falls within the 75 to 85 percent range support teams treat as good for transactional support. What is a good CSAT score still depends on your industry, channel, and contact reason, so check 80 percent against your own baseline and response rate before calling it confirmed good.
What is the difference between CSAT and NPS?
CSAT measures satisfaction with a single interaction, scored as a percentage of satisfied responses out of total responses. NPS measures overall loyalty, scored on a -100 to +100 scale from an 11-point question. CSAT answers how the last contact went, while NPS answers how customers feel about the relationship overall.
How many responses do I need before my CSAT score is reliable?
Around 400 to 500 responses brings the margin of error down to roughly 4 to 5 percent at a 95 percent confidence level, a commonly used research threshold. Around 100 responses carries a margin of error near 13 percent, too wide for a segment with only a handful of responses to support a confident verdict.
Key terms
CSAT
CSAT, or customer satisfaction score, is a post-contact rating averaged across responses and usually collected with a single question immediately after an interaction closes. Because only a small fraction of customers respond, CSAT reflects the experience of people motivated to answer rather than the whole contact population.
Net promoter score
Net Promoter Score is a likelihood-to-recommend score used as a loyalty benchmark, calculated by subtracting the percentage of detractors from the percentage of promoters. It produces a single comparable number, but the free-text comment attached to each score carries most of the diagnostic value.
Customer satisfaction index
A customer satisfaction index is a composite score that combines multiple satisfaction measures into a single number, usually scaled from 0 to 100. The term covers two distinct uses. The American Customer Satisfaction Index, founded at the University of Michigan and now run by ACSI LLC, applies a standardized econometric model across roughly 400 companies to benchmark satisfaction by industry and over time. A company-internal customer satisfaction index instead blends its own CSAT, effort, and loyalty responses into one weighted figure. Unlike a single-question CSAT percentage, which reflects one interaction, a CSI aggregates several attributes. Its weighting method has to stay documented and unchanged for the score to be comparable period over period. See OnClarity’s CSAT glossary entry for how the single-question version works.
Root cause analysis
Root cause analysis is the practice of tracing a symptom, such as a spike in complaints, back to the underlying process, policy, or product defect that produced it. The alternative, resolving each ticket in isolation, never stops the symptom from recurring. Established methods include 5 Whys (repeated questioning to reach the originating cause), fishbone (Ishikawa) diagrams (mapping possible causes by category), and Pareto analysis (isolating the small number of causes driving most of the volume). In CX, this starts with clustering tickets by theme, then tracing the largest theme to its source. OnClarity’s Voice of Customer automates this by surfacing root causes directly from feedback. Grubhub uses it to turn feedback into insights that shape its roadmap. The real test of success is recurrence: a fix that addresses the root cause should stop the issue from reappearing.
