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customer-research

Extract customer insights from interviews, surveys, support tickets, and online reviews.

Updated Apr 3, 2026
Search Tags:#competitive intelligence#customer research#survey analysis#voice of customer#persona building#review mining#reddit research
One-click install
npx skills add https://github.com/lapaixkemsdortshlee-svg/AyitiMarket --skill customer-research-lapaixkemsdortshlee-svg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: customer-research
Source: https://github.com/lapaixkemsdortshlee-svg/AyitiMarket/tree/main/.agents/skills/customer-research
Command: npx skills add https://github.com/lapaixkemsdortshlee-svg/AyitiMarket --skill customer-research-lapaixkemsdortshlee-svg

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you replace guesswork with evidence by turning raw customer feedback, interviews, and online discussions into clear research insights.

Core Features & Use Cases

  • Analyze existing research: Review interview transcripts, surveys, support tickets, win/loss notes, and NPS verbatims to find recurring themes.
  • Mine digital watering holes: Gather authentic customer language from Reddit, G2, Capterra, LinkedIn, forums, and community discussions.
  • Synthesize findings: Organize jobs to be done, pain points, trigger events, desired outcomes, alternatives, and confidence levels into usable deliverables.
  • Use case: A product or marketing team can use this Skill to build personas, create a VOC quote bank, understand churn, or inform messaging with real customer language.

Quick Start

Analyze these customer interview transcripts and extract the top pains, triggers, desired outcomes, and exact language customers use.

Frequently Asked Questions about customer-research

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

FAQPage Schema
How do I extract customer insights from interview transcripts and support tickets?▼

Customer insights are extracted by analyzing raw feedback to identify recurring themes, jobs to be done, pain points, and trigger events. This process structures unstructured support tickets and interview transcripts into actionable deliverables with confidence levels and source quotes.

What is the best way to mine Reddit and G2 reviews for voice of customer data?▼

Mining digital watering holes like Reddit, G2, and forums captures authentic customer language and sentiment. This voice of customer synthesis organizes online discussions into desired outcomes, alternatives, and exact language patterns for messaging and persona building.

How do I build user personas from NPS verbatims and win/loss notes?▼

Building personas from NPS verbatims and win/loss notes involves synthesizing feedback to find recurring pain points and trigger events. This organizes qualitative data into structured ICP profiles, jobs to be done, and desired outcomes.

Can I analyze survey responses to understand customer churn and pain points?▼

Survey analysis for churn identifies recurring pain points and trigger events within response data. This synthesizes feedback into structured deliverables, highlighting desired outcomes, alternatives, and confidence levels to inform retention strategies.

Does customer research require specific data formats for competitive intelligence?▼

Customer research for competitive intelligence accepts raw text from interviews, surveys, support tickets, and online reviews. It processes this unstructured data to extract alternatives, language patterns, and source-by-source quotes without requiring rigid formatting.

What are the limitations of using automated review mining for VOC synthesis?▼

Automated review mining for VOC synthesis relies on the availability and quality of raw feedback. Confidence levels are assigned to findings to indicate data reliability, but insights are constrained by the depth of the source discussions.

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