Marketing SkillsView repo

Marketing Skill

Customer Research

Extracts what customers actually think and say — from transcripts, surveys, tickets, and reviews you already have, or from online communities where they speak unfiltered. Point your agent at it when your positioning, copy, or roadmap is running on assumption instead of evidence.

Maintained by Corey Hainesv2.0.1Updated 2026-07-101 references
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Installs the full library — Customer Research included

MarkdownView source

Customer research uncovers what buyers actually think, feel, and struggle with so decisions rest on reality, not assumption. It runs in two modes: analyzing existing assets (interview transcripts, surveys, support tickets, win/loss notes, NPS) and going to find research in digital watering holes (Reddit, G2/Capterra, Hacker News, forums). For each source, extract six things — jobs to be done, pain points, trigger events, desired outcomes, exact customer language, and alternatives considered — then cluster by theme and score by frequency and intensity. Label every insight High/Medium/Low confidence (High = 3+ independent sources, mentioned unprompted), and never build a persona from fewer than 5-10 data points per segment.

When to use it

Your agent reaches for this skill when you ask for things like:

“customer research,”“ICP research,”“talk to customers,”“analyze transcripts,”“customer interviews,”“survey analysis,”“support ticket analysis,”“voice of customer,”

What's inside

The playbook covers

Before StartingTwo Modes of ResearchMode 1: Analyzing Existing Research AssetsMode 2: Digital Watering Hole ResearchTop Themes (ranked by frequency × intensity)Persona Generation[Persona Name] — [Role/Title]Deliverable FormatsQuestions to Ask Before Proceeding

Reference library — 1 deep-dives

Customer Research — Source GuidesDetailed, source-by-source playbooks for gathering customer intelligence from online watering holes.

Key data

The recommendations are grounded in benchmarks, not opinion:

1. 3-star reviews — these are the most honest. Customer liked it enough to stay but felt something was missing.
2. 1-star reviews — understand the failure modes. Separate product issues from support/onboarding issues.
3. 5-star reviews — extract the "what they love" language. These are your proof points.
4. 4-star reviews — often contain "the only thing I wish…" buried in praise.
G2 structure to exploit:**
Capterra has similar structure. Trustpilot skews B2C. AppSumo** reviews are useful for SMB/prosumer SaaS.

See it in action

You ask

I have 20 customer interview transcripts. Help me analyze them.

The skill delivers
VOC theme

Theme: Drowning in manual spreadsheet work Frequency: 7 of 12 sources | Intensity: High (emotional language) Quotes: - "We were drowning in spreadsheets before we found a tool." — r/projectmanagement, Mar 2026 - "I spend half my Friday copying numbers between tabs." — G2 2-star review, Feb 2026 Implication: Lead homepage messaging with time reclaimed from manual work, in their words.

FAQ

How do I do customer research if I have no interviews yet?

Use digital watering hole research — go where customers already talk unfiltered. Read 1-3 star reviews and competitor 4-star reviews on G2 and Capterra, mine role-specific subreddits, Hacker News, and niche communities, and capture verbatim quotes with source, sentiment, and theme tags. For early-stage products with no first-party reviews, walk outward through proxy sources (your differentiator, competitor reviews, comparable products) and tag every persona as provisional until real data arrives.

Why should I read competitors' 4-star reviews specifically?

4-star reviews are where satisfied customers bury their real complaints — they like the product enough to keep using it but still name what frustrates them. Those buried gripes are your clearest product and positioning opportunities. 1-star reviews skew toward outliers and edge cases; 4-star reviews reveal what mainstream buyers wish were better.

How much data do I need before building a persona?

At least 5-10 independent data points from a consistent segment — interviews, reviews, or community posts. Below that, you're inventing, not researching. Don't average across segments (a persona for everyone represents no one), leave fields blank rather than filling in details you don't have, and revisit personas quarterly as your market and product evolve.

Build a tool for this workflow?

Marketers run this skill mid-task — the exact moment your tool matters. Partner tiers put your tool inside the skill their agent runs.

See partner tiers