CSAT (Customer Satisfaction Score)

General definition

CSAT (Customer Satisfaction Score) asks one question right after an interaction: how satisfied were you with this conversation, this delivery or this product? Answers are on a scale, most commonly 1 to 5 (very dissatisfied to very satisfied), sometimes 1 to 3 or a smiley scale. The formula is the number of positive responses divided by the total number of responses, multiplied by 100, where positive means the top two boxes (4 and 5) on a five-point scale. Fifty satisfied responses out of eighty gives a CSAT of 62.5%.

• Transactional: it measures one moment, so it is collected continuously and reported per agent, per channel, per topic and per week
• Fast: one tap at the end of a chat keeps response rates high; an optional comment field captures the reason
• Benchmarks: support teams commonly aim for 80% or higher; anything below 70% usually points to a process or staffing problem rather than individual agents
• Bias: only people who finish the interaction answer, and unhappy customers respond more readily than content ones, so the trend matters more than the absolute number

CSAT sits alongside two other survey metrics. Net Promoter Score (NPS) asks how likely you are to recommend on a 0 to 10 scale and subtracts the percentage of detractors (0 to 6) from promoters (9 and 10); it measures relationship loyalty rather than one interaction. Customer Effort Score (CES) asks how easy it was to get the issue resolved and predicts repeat contact better than satisfaction does. Teams typically run CSAT after every chat, CES after support resolutions, and NPS quarterly.

In chat, the survey is usually a widget step: the conversation ends, a rating prompt appears in the same window, and the score is stored against the conversation, the agent or bot that handled it, and the tags applied. Increasingly, AI sentiment analysis of the transcript is used as a proxy when the customer does not answer the survey, covering every conversation rather than the fraction that respond.

In the Ethora ecosystem

Ethora does not ship a fixed survey screen; it gives you the pieces to build one that fits your flow. With the Chat SDK a post-chat rating step can be added to the conversation UI in the chat widget or in-app chat, stored through your own backend against the room and the participants, and reported however your support stack expects. API-provisioned users mean the rating is tied to your customer record, not to a separate chat identity.

For coverage beyond survey responses, an AI agent attached to a room or channel can score the sentiment of the conversation as it happens, and Trust and Safety reporting can send flagged conversations to your systems by message bus, API or email. Combined across web, mobile and other channels in an omnichannel setup, that gives a satisfaction signal for every conversation, with the surveyed CSAT as the anchor.