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What Is Customer Satisfaction Score?

Customer satisfaction score (CSAT) is a percentage measuring the share of survey respondents who rate an interaction as satisfactory or better on a defined scale, typically collected immediately after a support ticket, delivery, or product interaction. Most teams export CSAT data from their survey or helpdesk tool in a format that requires filtering and aggregation before the metric is meaningful at the segment level.

See the exact formula, which survey export columns to use, and how to segment the score by channel, agent, and product area in a spreadsheet.

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What is a good CSAT score benchmark?How do I calculate CSAT from a helpdesk export?How is CSAT different from NPS?How do I segment CSAT by support agent?How often should I collect CSAT surveys?

What this export contains

response_id
survey_date
customer_id
agent_name
ticket_category
rating
rating_scale
channel
product_area
response_comment

What usually goes wrong with it

  • Rating scale varies by survey tool

    Some tools use a 1–5 scale; others use 1–3 or 1–7 — combining exports from two helpdesk tools with different rating_scale values produces an incorrect blended score unless each is normalized first.

    DataMimi Datamimi normalizes rating values to a common scale across multiple exports before calculating the blended score.

  • Non-responses skew the denominator

    CSAT is calculated on responded surveys only, but some exports include unresponded or expired survey rows with null ratings — including them in the count inflates the response denominator and deflates the score.

    DataMimi It filters null-rating rows automatically before calculating the response denominator so only completed surveys count.

  • Score not segmented by channel or product area

    Aggregate CSAT hides the fact that support channel and product_area drive most of the variation — an overall score of 85% can mask a phone channel scoring 60% and a chat channel scoring 95%.

    DataMimi It segments the score by channel and product_area in parallel breakdowns so the overall figure and its components are visible in the same analysis.

  • Comment text requires separate analysis

    response_comment is the most actionable field for understanding low scores, but most teams analyze the numeric rating only and never look at the text that explains it.

    DataMimi It surfaces low-rating rows alongside their response_comment so the text evidence for low scores is immediately accessible without a separate query.

Common questions

What is customer satisfaction score?

Customer satisfaction score (CSAT) is the percentage of survey respondents who rate their experience as satisfactory or above, calculated as positive responses divided by total responses and multiplied by 100.

What is a good CSAT score benchmark?

CSAT benchmarks vary by industry; B2B SaaS support typically targets 85–95%; e-commerce and consumer services often see 75–85%; scores below 70% in any segment typically warrant immediate investigation.

How is CSAT different from NPS?

CSAT measures satisfaction with a specific interaction immediately after it occurs; NPS measures overall relationship loyalty and is collected periodically across the full customer relationship.

How do I calculate CSAT in a spreadsheet?

Filter to completed survey rows with a non-null rating; count rows where rating meets your 'satisfied' threshold (e.g., 4 or 5 on a 1–5 scale); divide by total response count and multiply by 100.

How much does Datamimi cost?

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