voice-of-customer-miner

name	voice-of-customer-miner
argument-hint	[whose customer voice, and the decision it informs]
description	Mine public reviews, app stores, and forums for unmet needs, competitor weaknesses, and switching triggers — with quoted evidence. Use when you want customer voice without waiting on interviews.
intent	Mine public customer voice for unmet needs, competitor weaknesses, and switching triggers, with real quoted verbatims and labeled inference. Bridges competitive intelligence and discovery: outputs feed JTBD canvases, opportunity solution trees, and battle cards — as hypotheses to validate, not verdicts.
type	workflow
theme	market-intelligence
best_for	["Finding what users actually complain about and wish for — yours and competitors' — from the public record","Arming battle cards with competitor weaknesses in customers' own words","Seeding discovery interviews and opportunity trees with evidence-backed hypotheses"]
scenarios	["Mine the reviews of our top two competitors — what are their customers angriest about?","Before the interview cycle starts, what does the public web say our segment's unmet needs are?"]
estimated_time	20-35 min per run

Voice-of-Customer Miner

Purpose

Mine public customer voice — review sites, app stores, Reddit and practitioner forums, community boards — for unmet needs, competitor weaknesses, and switching triggers: search plan → source sweep → verbatim capture → need themes → so what → next-step options. This bridges competitive intelligence and discovery: it delivers customers' exact words without waiting on an interview cycle. But public voice skews toward the angry and the vocal, so every theme it surfaces is a hypothesis to validate, never a verdict — the output's last stop is always a real conversation.

Input

Works best with: the product(s) or competitor(s) to mine — yours, a rival's, or a set — and the decision this should inform. Also useful: a theme to focus on (onboarding, pricing, reliability) if you have one; otherwise the sweep runs open.

Input supplied inline with the invocation — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it against the question budget; don't re-ask.

Arriving empty-handed? That works too. The skill opens with at most 3 questions (whose voice, what decision, theme or open sweep) and proceeds on labeled assumptions if they go unanswered.

Example invocation: Mine voice-of-customer for [Competitor A] and [Competitor B], focus on onboarding — informs whether our Q1 bet is a migration tool.

Key Concepts

• Governing protocol: honors the autonomous-investigation contract — question budget of 3, search-plan gate, Fact/Inference/Assumption labels, Just Enough Mode, stable schema, 4-option Final Step. Discipline: OSINT's review-and-community layer (see intelligence-collection-disciplines).
• Theme by need, not by feature. "Exports are broken" is a feature complaint; "I can't get my data where my team works" is the underlying need. Theming by need is the same solution-free discipline as JTBD and painstorming — and it's what makes themes portable into discovery.
• Verbatims are the product. Short, real, quoted customer language with URLs. Verbatims teach persona language: the exact words customers use become interview probes and positioning copy. Never fabricate quotes, ratings, review counts, or reviewer roles.
• Every source has a known skew. Reviewers skew negative; vendor communities skew loyal; app stores over-represent update anger. Note the bias per source — public voice is evidence with a known skew, not ground truth.