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customer-research

Analyze customer research to extract pains, triggers, and desired outcomes.

Updated Jul 4, 2026
Search Tags:#persona#research-synthesis#jtbd#customer-research#survey-analysis#voc#review-mining
One-click install
npx skills add https://github.com/mrsknetwork/mrsknetwork --skill customer-research-mrsknetwork
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: customer-research
Source: https://github.com/mrsknetwork/mrsknetwork/tree/main/.agents/skills/customer-research
Command: npx skills add https://github.com/mrsknetwork/mrsknetwork --skill customer-research-mrsknetwork

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Helps teams move beyond assumptions by extracting what customers actually think, feel, say, and struggle with so positioning, product decisions, and messaging are grounded in evidence rather than guesswork.

Core Features & Use Cases

  • Research synthesis: Extract jobs-to-be-done, pain points, triggers, desired outcomes, and exact customer language from interviews, surveys, support tickets, and reviews.
  • Digital watering-hole mining: Identify and mine Reddit, G2, forums, LinkedIn, and social platforms for verbatim quotes, sentiment, and switching triggers when primary research is not available.
  • Deliverables & templates: Produce research synthesis reports, VOC quote banks, personas (when minimum sample thresholds are met), JTBD maps, and competitive review summaries with confidence labels and recency guardrails.
  • Quality guardrails: Provides confidence scoring, sample-bias checks, segmentation advice, and instructions to check product-marketing-context files before starting.

Quick Start

Ask the skill to analyze customer research by stating your goal (e.g., improve messaging, build personas), listing available assets (interviews, surveys, reviews), and requesting a deliverable such as a research synthesis or 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 synthesize customer research from interview transcripts and support tickets?▼

Customer research synthesis extracts jobs-to-be-done, pain points, triggers, and desired outcomes from interview transcripts and support tickets. The skill analyzes existing assets to surface verbatim language, frequency, and intensity scoring for evidence-based positioning and product decisions.

Can I mine Reddit and G2 reviews for customer sentiment and switching triggers?▼

Yes, digital watering-hole mining identifies and extracts verbatim quotes, sentiment, and switching triggers from Reddit, G2, forums, and social platforms. This gathers online intelligence when primary research or direct interviews are not available.

What's the best way to build personas and VOC quote banks from customer reviews?▼

Building personas and VOC quote banks requires synthesizing customer reviews with confidence scoring and sample-bias checks. Personas are generated when minimum sample thresholds are met, producing research reports with exact customer language and confidence labels.

Does customer research analysis work without existing interview data?▼

Yes, when primary research is unavailable, the analysis gathers online intelligence from social platforms and review sites. It mines digital watering holes for verbatim quotes and sentiment, applying recency guardrails to ensure data relevance.

How do I extract jobs-to-be-done from survey responses and customer feedback?▼

Extracting jobs-to-be-done from survey responses involves analyzing customer feedback to identify pains, triggers, and desired outcomes. The skill applies frequency and intensity scoring to survey data, producing JTBD maps with confidence labels.

What are the limitations of using review mining for customer research synthesis?▼

Review mining limitations include sample bias and recency issues, addressed through confidence scoring and recency guardrails. The skill checks for product-marketing-context files and provides segmentation advice to mitigate bias from online sources.

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