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inbharatai
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feedback-analyzer

Analyze customer feedback with sentiment analysis, theme clustering, and NPS interpretation.

22|8|Updated Mar 14, 2026
Search Tags:#feedback#analysis#roadmap#themes#sentiment#NPS
One-click install
npx skills add https://github.com/inbharatai/claude-skills --skill feedback-analyzer-inbharatai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feedback-analyzer
Source: https://github.com/inbharatai/claude-skills/tree/main/skills/feedback-analyzer
Command: npx skills add https://github.com/inbharatai/claude-skills --skill feedback-analyzer-inbharatai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill streamlines the analysis of customer feedback, transforming raw input into actionable insights for product and service improvement.

Core Features & Use Cases

  • Sentiment Analysis: Automatically determine the emotional tone (positive, negative, neutral) of feedback.
  • Theme Clustering: Identify recurring topics and themes within large volumes of feedback.
  • NPS Interpretation: Analyze Net Promoter Score data to understand drivers of loyalty and churn.
  • Roadmap Generation: Suggest concrete steps for improvement based on feedback analysis.
  • Use Case: A product manager receives hundreds of app reviews. This Skill can quickly identify that users are frequently complaining about a specific feature's usability and suggest UI/UX improvements.

Quick Start

Analyze the sentiment and key themes in the following customer feedback: "The new update is great, but the login process is still too complicated."

Frequently Asked Questions about feedback-analyzer

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

FAQPage Schema
How do I analyze customer feedback to identify recurring themes and sentiment?▼

Customer feedback analysis uses natural language processing to perform sentiment analysis and theme clustering, automatically identifying emotional tones and recurring topics within large volumes of input to reveal actionable insights.

How do I interpret NPS data to understand what drives customer churn?▼

NPS interpretation analyzes Net Promoter Score data by evaluating underlying user sentiment and clustered themes, isolating specific negative feedback patterns that drive customer churn and identifying areas requiring immediate product intervention.

How can I generate a product improvement roadmap from app reviews?▼

Roadmap generation from app reviews utilizes statistical methods to process clustered themes and sentiment scores, suggesting concrete product development steps and UI/UX improvements directly based on identified user pain points and feature requests.

What is the best way to process large volumes of feedback for actionable product insights?▼

Processing large feedback volumes leverages statistical methods and natural language processing to cluster recurring topics and evaluate sentiment, transforming raw user input into structured, actionable product development strategies.

Can I use sentiment analysis on mixed positive and negative feedback to prioritize fixes?▼

Sentiment analysis on mixed feedback determines the precise emotional tone of each input, allowing product managers to isolate specific usability complaints alongside positive remarks to accurately prioritize feature fixes.

Does theme clustering work on unstructured customer feedback without predefined categories?▼

Theme clustering processes unstructured customer feedback by using natural language processing to automatically discover and group recurring topics, operating effectively without requiring any predefined categories or manual tagging.

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