Definition
Customer Satisfaction Score is the oldest and simplest of the post-experience metrics. The canonical question is "How satisfied were you with [the thing you just experienced]?" on a Likert scale — usually 1–5 or 1–7, with 1 being "very dissatisfied" and the top score being "very satisfied." Teams deploy it after a support ticket closes, after a purchase, after a product arrives, or after a specific feature is used.
The standard formula reports the percentage of "top-box" responses — 4 or 5 on a 5-point scale, 6 or 7 on a 7-point scale. Some teams report the mean. CSAT is not trademarked, so specific implementations vary; whatever you pick, document the scale and formula alongside the number, because a 4.2/5 mean and an 84% top-two are not the same thing and will be read differently. Response rate matters too — a CSAT built on 4% response is a different instrument than one built on 40%, and both are different from review text, which is self-selected at a different moment.
Why it matters
CSAT's strength is specificity. Unlike Net Promoter Score, which asks about overall relationship, CSAT measures one interaction or one purchase. That makes it useful for operational feedback loops: a CSAT score on a Zendesk ticket can be tied to the agent, the product, the issue type, and the resolution path. A CSAT score on a shipped order can be tied to the SKU, the carrier, and the unboxing.
Its weakness is the same specificity: CSAT doesn't tell you whether the customer will stay, repurchase, or recommend. That's why most mature programs run CSAT for transactional read and NPS for relationship read, and pair both with behavioral signals (repurchase, review sentiment, return rate) before making a call. Treat CSAT as one instrument in a panel, not the panel itself.
Example
A small-kitchen-appliance brand sends a two-question CSAT survey via Typeform 14 days after a Shopify purchase. Question one: "How satisfied are you with your [product]?" on a 5-point scale. Question two: open text. Post-launch CSAT on a new espresso machine is 72% top-two — below the brand's 85% baseline.
The open-text responses, themed against Amazon and Bazaarvoice reviews for the same SKU, point to the same cluster: water-tank leak on a specific production batch. The brand pauses shipments, inspects remaining inventory, escalates to the factory, and re-runs CSAT four weeks later — 86% top-two. Without joining CSAT to the rest of the record, the team would have seen only a dip, not the cause.