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customer-research

Analyze customer interviews, reviews, and community posts into personas and VOC insights.

Updated Aug 2, 2026
Search Tags:#personas#customer research#voice of customer#icp#jobs to be done#review mining#reddit research
One-click install
npx skills add https://github.com/Pinkycherry/newbusinessideas3 --skill customer-research-pinkycherry
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: customer-research
Source: https://github.com/Pinkycherry/newbusinessideas3/tree/main/.claude/skills/customer-research
Command: npx skills add https://github.com/Pinkycherry/newbusinessideas3 --skill customer-research-pinkycherry

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Grounding positioning, messaging, and product decisions in real customer language is hard when research is scattered across transcripts, surveys, support tickets, and review sites. This Skill structures the analysis of existing research assets and guides the gathering of new intelligence from online communities. ## Core Features & Use Cases - Dual research modes: Analyze existing assets (interviews, surveys, tickets, NPS, win/loss notes) or gather new intel from digital watering holes like Reddit, G2, Hacker News, LinkedIn, and app stores. - Structured extraction framework: Pull jobs-to-be-done, pain points, trigger events, desired outcomes, verbatim language, and alternatives considered from every source. - Confidence-scored synthesis: Label insights high/medium/low confidence, cluster themes by frequency and intensity, and build personas only from 5-10+ real data points. - Use Case: You have 20 customer interview transcripts and want messaging input. The Skill extracts themes and money quotes, scores confidence, and produces a VOC quote bank ready for the copywriting skill. ## Quick Start Analyze my customer interview transcripts and online reviews to build a research-backed persona and VOC quote bank.

Frequently Asked Questions about customer-research

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

FAQPage Schema
How do I analyze customer interview transcripts for insights?▼

Extract jobs-to-be-done, pain points, trigger events, desired outcomes, exact vocabulary, and alternatives considered from each transcript. Then cluster themes across interviews, score by frequency and intensity, and capture verbatim money quotes for each theme.

How do I do customer research with no existing interviews?▼

Start with digital watering hole research: mine Reddit communities, G2 and Capterra reviews, Hacker News, and niche forums where your ICP speaks unfiltered. Form hypotheses first, then validate with 5-10 data points before building personas.

What review sites should I mine for competitor research?▼

G2 and Capterra are primary B2B sources; read competitor 4-star reviews for buried complaints and 3-star reviews for honest tradeoffs. For consumer products, use app store reviews, Trustpilot, and Amazon reviews in the same priority order.

How many data points do I need before building a customer persona?▼

Build personas only after collecting at least 5-10 independent data points from a consistent segment, such as interviews, reviews, or community posts. Personas built from fewer sources risk representing outliers rather than real patterns.

Why should I segment churn reasons before analyzing exit surveys?▼

Averaging across different churn causes (price, features, fit, timing) hides actionable signal. Segment responses by reason first, pair open-ended verbatims with quantitative data, and label each insight with a confidence level based on source consistency.

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