customer-research

Analyze customer interviews, surveys, reviews, and community posts to extract personas and voice-of-customer insights.

Updated Aug 13, 2026
One-click install
npx skills add https://github.com/imMamdouhaboammar/marketing-skills --skill customer-research-immamdouhaboammar
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: customer-research
Source: https://github.com/imMamdouhaboammar/marketing-skills/tree/main/skills/customer-research
Command: npx skills add https://github.com/imMamdouhaboammar/marketing-skills --skill customer-research-immamdouhaboammar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Marketing and product decisions are often based on assumptions rather than what customers actually say and struggle with. This Skill turns raw research assets (transcripts, surveys, support tickets, reviews) and online community data into structured insights, personas, and voice-of-customer language. ## Core Features & Use Cases - Existing Asset Analysis: Extract jobs-to-be-done, pain points, trigger events, desired outcomes, and exact customer vocabulary from interview transcripts, surveys, support tickets, NPS responses, and win/loss notes. - Digital Watering Hole Research: Mine Reddit, G2, Capterra, Hacker News, LinkedIn, app store reviews, and niche communities for unfiltered customer language, with per-source playbooks in the references guide. - Persona Generation: Build evidence-based personas with confidence labels, minimum sample thresholds, and proxy-source strategies for products without first-party reviews. - Use Case: You have 20 customer interview transcripts and want messaging for your homepage. The Skill extracts themes with frequency and intensity scoring, produces a VOC quote bank, then hands off to the copywriting skill. ## Quick Start Analyze my customer interview transcripts and produce a research synthesis report with themes, representative quotes, and a persona draft.

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 marketing insights?

Extract jobs-to-be-done, pain points, trigger events, desired outcomes, exact vocabulary, and alternatives considered from each transcript. Then cluster findings by theme, score by frequency and intensity, and identify 5-10 representative verbatim quotes per theme.

How do I do customer research when I have no interviews or reviews yet?

Start with digital watering hole research: mine competitor reviews on G2 and Capterra, relevant subreddits, and adjacent product reviews on marketplaces. Tag personas built from proxy sources as provisional and replace with first-party evidence as it arrives.

What online sources are best for voice of customer research?

For B2B SaaS, use Reddit, G2, Capterra, Hacker News, and LinkedIn. For B2C, use app store reviews, hobby subreddits, YouTube and TikTok comments. Competitor 4-star G2 reviews are especially valuable for buried complaints.

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

Build personas only after collecting at least 5-10 data points from a consistent segment, such as interviews, reviews, or community posts. Avoid averaging across segments or inventing details not supported by the data.

How do I avoid bias when synthesizing customer research?

Label every insight with a confidence level based on source count and consistency, weight sources from the last 12 months more heavily, and account for sample bias: reviewers skew toward strong opinions, support tickets skew toward problems, and Reddit skews technical.