csat-nps-analysis
Analyse CSAT / NPS / CES survey results and turn the score into actions. Use when asked to analyse NPS, CSAT, or CES data, compute an NPS score, interpret survey verbatims, or build a voice-of-customer readout. Produces a readout — the computed score, the trend & benchmark, themed analysis of the comments (what drives promoters vs. detractors), and prioritised actions. Includes a stdlib NPS/CSAT calculator.
npx skills add mohitagw15856/pm-claude-skills --skill csat-nps-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# CSAT / NPS Analysis Skill A satisfaction score on its own is a vanity number — the value is in *why* it's that number and *what to do*. This skill computes the score correctly (NPS is %promoters − %detractors, not an average), reads the verbatims for the themes driving promoters and detractors, and turns it into a prioritised action list — so a survey becomes a roadmap, not a slide. ## Required Inputs Ask for these only if they aren't already provided: - **The metric & data** — NPS (0–10 ratings), CSAT (e.g. 1–5 or % satisfied), or CES; the response counts/distribution. - **The verbatims** — open-text comments (the gold; paste what you have). - **Context** — segment, time period, and the prior score for trend. ## Output Format ### [CSAT / NPS / CES] Readout: [segment, period] **1. The score** — computed (use the helper for NPS/CSAT): the headline number, the **distribution** (promoters/passives/detractors for NPS), the **trend** vs. last period, and the **benchmark** (industry/your target). State the formula — NPS is a net of percentages, not an average. **2. What's driving it** — theme the verbatims: - **Promoters love:** the 2–3 recurring reasons people rate high (protect/ampli
- Required Inputs
- Output Format
- [CSAT / NPS / CES] Readout: [segment, period]
- Programmatic Helper
- Quality Checks
- Anti-Patterns
- Based On
NPS from 0-10 counts (11 numbers, ratings 0..10): python3 scripts/nps.py nps 12 5 8 ... CSAT % satisfied (ratings 4-5 on a 1-5 scale): python3 scripts/nps.py csat 2 3 10 40 55 python3 scripts/nps.py nps "...counts..." --json
What does the csat-nps-analysis skill do?
Analyse CSAT / NPS / CES survey results and turn the score into actions. Use when asked to analyse NPS, CSAT, or CES data, compute an NPS score, interpret survey verbatims, or build a voice-of-customer readout. Produces a readout — the computed score, the trend & benchmark, themed analysis of the comments (what drives promoters vs. detractors), and prioritised actions. Includes a stdlib NPS/CSAT calculator.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill csat-nps-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.