skills.rest
stefanomartiradonna
stefanomartiradonnaCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

sentiment-analysis

Analyze user feedback data to identify segments with sentiment scores and JTBD insights.

Updated Apr 8, 2026
Search Tags:#market research#sentiment analysis#product insights#user feedback#nps#jtbd#customer segments
One-click install
npx skills add https://github.com/stefanomartiradonna/claude-skills --skill sentiment-analysis-stefanomartiradonna
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sentiment-analysis
Source: https://github.com/stefanomartiradonna/claude-skills/tree/main/pm-market-research-sentiment-analysis
Command: npx skills add https://github.com/stefanomartiradonna/claude-skills --skill sentiment-analysis-stefanomartiradonna

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Analyzing large volumes of user feedback manually is slow and inconsistent, making it hard to identify which user segments are satisfied, which are at risk of churn, and what product improvements matter most. ## Core Features & Use Cases - Segment Identification: Detects at least 3 distinct user segments or personas from feedback data with JTBD profiles. - Sentiment Scoring: Assigns sentiment scores (-1 to +1) per segment with satisfaction drivers, detractors, and NPS proxies. - Prioritized Recommendations: Ranks insights by frequency, severity, and business impact, delivering 2-3 actionable improvements per segment. - Use Case: You have hundreds of survey responses and app store reviews for your SaaS product. Use this Skill to segment users, score sentiment per segment, and produce a prioritized list of product improvements. ## Quick Start Analyze the attached customer survey CSV and identify user segments with sentiment scores and top pain points.

Frequently Asked Questions about sentiment-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze user feedback at scale for sentiment?▼

Provide your feedback sources such as CSVs, survey responses, or reviews, and the analysis follows six steps: data ingestion, segment identification, thematic analysis, sentiment scoring, impact assessment, and synthesis into segment profiles.

What data formats work for sentiment analysis of customer feedback?▼

The analysis accepts CSV files, PDFs, survey responses, review data, and social listening reports. All sources are read directly and patterns, themes, and sentiment signals are extracted from the raw text.

How is sentiment scored for each user segment?▼

Each segment receives an overall sentiment score from -1 to +1 based on satisfaction drivers and detractors found in the feedback. An NPS proxy is included when the data supports it.

Can sentiment analysis handle small feedback samples?▼

Yes, but segments with small sample sizes or uncertain sentiment are explicitly flagged in the output. This prevents over-generalizing conclusions from limited data.

What are the limitations of qualitative sentiment analysis?▼

Results depend on the quality and representativeness of the input feedback. The analysis distinguishes feature requests from fundamental pain points but cannot validate statistical significance without quantitative survey data.

Related Skills

Explore More Product & Management Skills→
omeragaakbasomeragaakbas

sentiment-analysis

Analyze user feedback to compute sentiment scores and identify market segments.

Community
Intermediate
moonzffmoonzff
1

user-segmentation

Segment users from feedback data based on behavior, jobs-to-be-done, and needs.

Community
Intermediate
WebWakaHubWebWakaHub
20

Feedback Synthesizer

Synthesize fragmented user feedback into prioritized product actions.

Official
Advanced
Owl-ListenerOwl-Listener
2.5k

survey-design

Design unbiased survey instruments with question wording, scales, and sampling methodology.

Community
Intermediate