Customer Research

---
name: Customer Research
description: Use when the user wants to conduct, analyze, or synthesize customer research — interviews, surveys, support tickets, reviews, or personas built from real data.
category: Strategy
version: 2.0.0
tools: []
---

# Customer Research

Uncover what customers actually think, feel, say, and struggle with — so positioning, product, and copy are grounded in reality rather than assumption.

## Before Starting
Search the Knowledge Base for existing product-marketing context first, and use it to skip questions already answered.

## Two Modes
**Mode 1: Analyze existing assets** — raw research material already exists (transcripts, surveys, reviews, tickets); the job is extracting signal. **Mode 2: Go find research** — gather intel from online sources (Reddit, G2, forums, communities, review sites); the job is knowing where to look and what to extract. Most engagements combine both — establish which applies before proceeding.

## Mode 1: Analyzing Existing Assets

**Asset types and what to mine:**
- *Interview/sales call transcripts* — pains, triggers, desired outcomes, exact language, objections, alternatives considered; specifically the moment they decided to look for a solution and what they tried before.
- *Surveys* — segment by tier/use case/tenure before concluding anything; flag where open-ended answers contradict multiple-choice answers; find the 20% of responses carrying the most signal.
- *Support conversations* — recurring complaints, confusion points, feature requests, "I wish it could…" language; categorize tickets before analyzing (bugs vs. confusion vs. missing features vs. expectation mismatch).
- *Win/loss and churn notes* — for wins, what tipped the decision and what nearly lost it; for losses/churn, was it price, features, fit, or timing; segment by reason rather than averaging across causes.
- *NPS* — passives and detractors carry more improvement signal than promoters; pair every score with its verbatim (a 9 with a specific complaint beats a bare 10).

**Extraction framework** — for each asset, pull: (1) Jobs to Be Done — functional, emotional, and social job; (2) pain points, prioritizing unprompted ones stated with emotional language; (3) trigger events (team growth, new hire, missed target, embarrassing incident, a competitor's move); (4) desired outcomes, captured as exact quotes not paraphrases; (5) language and vocabulary verbatim — "we were drowning in spreadsheets" beats "manual process inefficiency" for copy; (6) alternatives considered, including doing nothing or building in-house.

**Synthesis** — cluster by theme across assets; score by frequency × intensity; segment by company size/role/use case/tenure to see if patterns differ; pull 5-10 "money quotes" per theme; flag contradictions between what customers say and do.

**Quality guardrails** — label every insight's confidence: **High** (3+ independent sources, unprompted, consistent across segments), **Medium** (2 sources, or prompted, or one segment only), **Low** (single source, possible outlier). Weight sources from the last 12 months more heavily — a 3-year-old transcript may reflect a different product and buyer. Watch for sample bias: online reviewers skew toward power users and strong opinions, support tickets skew toward problems not value, Reddit skews technical/skeptical. Don't build personas or messaging conclusions from fewer than 5 independent data points per segment.

## Mode 2: Digital Watering-Hole Research
Online communities carry unfiltered language about the problem space. Match source to ICP: **B2B SaaS/technical** — Reddit (role subs), G2/Capterra, Hacker News, LinkedIn, Indie Hackers, SparkToro. **SMB/founders** — r/entrepreneur, r/smallbusiness, Indie Hackers, Product Hunt, Facebook Groups, SparkToro. **Developer/DevOps** — r/devops, r/programming, Hacker News, Stack Overflow, Discord. **B2C/consumer** — app store reviews (1-3 star), Reddit hobby subs, YouTube/TikTok/Instagram comments. **Enterprise** — LinkedIn, analyst reports, G2 Enterprise filter, job postings, SparkToro.

Quick routing: have a category → start with G2/Capterra reviews (own + competitors); need to know where the audience spends time → SparkToro; need raw language → Reddit/YouTube comments; need trigger events → LinkedIn posts, job postings, HN "Ask HN"; need competitive intel → competitor 4-star G2 reviews, Product Hunt discussion, SparkToro competitor audience analysis.

For every piece of content found, capture: source (platform, thread URL, date), verbatim quote (never paraphrased), context (what prompted it), sentiment, theme tag (pain/trigger/outcome/alternative/language), and any profile signals (role, company size, industry). Synthesize into a per-theme block: summary, frequency (X of Y sources), intensity, 2+ representative quotes with source/date, and implications for messaging/product/positioning.

## Persona Generation
Build personas from research only — never invent one with fewer than 5-10 data points from a consistent segment. Structure: profile (title range, company size, industry if narrow, reporting line, team size); primary Job to Be Done in one sentence; trigger events; top 3 pains in their words; desired outcomes and how they measure success; objections/fears; alternatives considered; key vocabulary (verbatim phrases); how to reach them (channels, content consumed, trusted communities). Anti-patterns: don't name personas cutely unless the team finds it genuinely useful; don't average across segments (a persona representing everyone represents no one); don't fill in details without data — leave them blank; revisit quarterly as the market and product evolve.

## Deliverable Formats
Offer, per the user's need: a research synthesis report (themes, quotes, patterns, implications); a VOC quote bank organized by theme for copy use; a persona document (1-3 personas); a jobs-to-be-done map by segment; a competitive intelligence summary of what customers say about competitors vs. the product; or a research gap analysis. Ask which deliverable(s) are needed before generating output.

## Questions to Ask
Lead with #1 and #2, then follow up as needed rather than asking all five at once: (1) What's the goal — messaging, personas, product gaps, churn? (2) What already exists — transcripts, surveys, tickets, reviews, nothing? (3) Who's the target segment? (4) What's the product, if not already in context? (5) What deliverable is wanted?

## Related Skills
copywriting (copy informed by research), cro (optimizing with VOC insights), competitors (comparison pages), churn-prevention (churn-research-driven strategy), ads (research-informed targeting), cold-email (pain/trigger-informed outreach), content-strategy (topics from research).