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customer-research

Analyze customer research transcripts and surveys to extract jobs-to-be-done and verbatim quotes.

Updated Apr 11, 2026
Search Tags:#surveys#persona#transcripts#jobs-to-be-done#customer-research#online-research#voc
One-click install
npx skills add https://github.com/tamarin-vanreenen/marketingskills --skill customer-research-tamarin-vanreenen
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: customer-research
Source: https://github.com/tamarin-vanreenen/marketingskills/tree/main/skills/customer-research
Command: npx skills add https://github.com/tamarin-vanreenen/marketingskills --skill customer-research-tamarin-vanreenen

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Extracts and synthesizes real customer voice from transcripts, surveys, support tickets, and online sources to ground product, messaging, and experiences in actual customer language.

Core Features & Use Cases

  • Analyze Existing Assets: extract pains, JTBD, triggers, outcomes, language, and alternatives from transcripts, surveys, and tickets.
  • Go Find Research: perform digital watering hole research across Reddit, G2 reviews, forums, and niche communities to gather fresh signals.
  • Synthesis & Deliverables: cluster themes by frequency and intensity, identify money quotes, and produce VOC quote banks, personas, and JTBD maps.
  • Mode 2 Strategy: plan ICP-targeted research and deliver actionable insights for copy, product, and CRO.
  • Portability: produce outputs suitable for copywriting and on-page optimization.

Quick Start

Analyze transcripts, surveys, tickets, and online sources to extract JTBDs, pains, triggers, outcomes, and verbatim language, then deliver a structured research synthesis and VOC-ready quotes.

Frequently Asked Questions about customer-research

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

FAQPage Schema
How do I extract jobs-to-be-done from customer transcripts and support tickets?▼

Customer research synthesis analyzes transcripts, surveys, and support tickets to extract jobs-to-be-done, pains, triggers, and desired outcomes. It clusters themes by frequency and intensity, delivering structured outputs with exact quotes and recommended next actions for messaging and product improvements.

What is digital watering hole research and when do I need it for VOC analysis?▼

Digital watering hole research gathers fresh customer signals from Reddit, G2 reviews, forums, and niche communities. It is needed when existing assets lack depth, applying Mode 2 strategy to plan ICP-targeted research and deliver actionable insights for copy, product, and CRO.

Can I use online research to find customer pains and triggers from G2 reviews and forums?▼

Online research analyzes G2 reviews and forums to identify customer pains, triggers, desired outcomes, and alternatives. It synthesizes these sources into organized theme clusters with confidence labels and a VOC quote bank suitable for positioning and product decisions.

What's the best way to build a VOC quote bank from customer surveys and reviews?▼

The best way to build a VOC quote bank is synthesizing customer surveys and reviews to extract verbatim language and money quotes. This process clusters themes by frequency and intensity, producing portable outputs suitable for copywriting and on-page optimization.

Does customer research synthesis work for both existing assets and fresh online research?▼

Customer research synthesis applies both Mode 1 analyzing existing assets and Mode 2 digital watering hole research. It processes transcripts, surveys, tickets, and online sources to deliver personas, JTBD maps, and structured research synthesis with confidence labels.

How do I cluster customer feedback themes by frequency and intensity for product decisions?▼

Clustering customer feedback themes by frequency and intensity involves synthesizing transcripts, tickets, and online sources to identify recurring pains and desired outcomes. This produces organized theme clusters with confidence labels and recommended next actions for product improvements.

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