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lamngit1995
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sentiment-analysis

Analyze user feedback to identify market segments with sentiment scores.

Updated Aug 23, 2026
Search Tags:#market research#sentiment analysis#product insights#user feedback#user segmentation#customer satisfaction
One-click install
npx skills add https://github.com/lamngit1995/phuryn-pm-skills --skill sentiment-analysis-lamngit1995
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sentiment-analysis
Source: https://github.com/lamngit1995/phuryn-pm-skills/tree/main/pm-market-research/skills/sentiment-analysis
Command: npx skills add https://github.com/lamngit1995/phuryn-pm-skills --skill sentiment-analysis-lamngit1995

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill analyzes large volumes of user feedback to identify distinct market segments, understand their sentiment, and pinpoint key drivers of satisfaction or dissatisfaction.

Core Features & Use Cases

  • Segment Identification: Groups feedback into meaningful user segments.
  • Sentiment Scoring: Assigns sentiment scores to understand overall satisfaction.
  • Insight Synthesis: Provides actionable recommendations for product improvement tailored to each segment.
  • Use Case: Analyze thousands of app reviews to understand why different user groups love or hate specific features, and identify the top 3 improvements needed for each group.

Quick Start

Analyze user feedback for 'our new mobile app' and identify key segments with sentiment scores.

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 to identify market segments and satisfaction patterns?▼

To analyze user feedback, ingest qualitative and quantitative sources like app reviews or surveys to identify market segments, assign sentiment scores, and pinpoint drivers of satisfaction or dissatisfaction.

What is the best way to extract jobs-to-be-done insights from app reviews?▼

Extracting jobs-to-be-done insights from app reviews requires synthesizing user feedback data to group responses into meaningful user segments and reveal specific product satisfaction needs for each group.

Can I run sentiment analysis on surveys to understand why users hate specific features?▼

Yes, you can run sentiment analysis on surveys and reviews to understand why users love or hate features by assigning sentiment scores to distinct market segments and synthesizing actionable improvement recommendations.

Does this sentiment analysis approach work for processing thousands of mixed user feedback sources?▼

Yes, this sentiment analysis approach works for processing thousands of mixed user feedback sources at scale, synthesizing both qualitative and quantitative inputs to identify satisfaction patterns across user groups.

What type of user feedback data do I need to identify product satisfaction insights?▼

To identify product satisfaction insights, you need to ingest qualitative and quantitative user feedback data, such as app reviews or survey responses, which the analysis synthesizes into actionable product recommendations.

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