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voice-of-customer-miner · product-manager-skills · Flowy
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.
One skill from product-manager-skills .
$ npx -y skills add deanpeters/Product-Manager-Skills --skill voice-of-customer-miner --agent claude-codeInstalls just this skill. Get the whole plugin for auto-invocation.
⚡ How it fires
How this skill gets triggered: by you, by Claude, or both.
Fires itself Claude auto-loads it when your prompt matches the work. You can call it Invoke it directly when you want it. Slash command /voice-of-customer-miner👁️ Context preview
The summary Claude sees to decide when to auto-load this skill.
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. </> SKILL.md
voice-of-customer-miner.SKILL.md
---
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
Flowy AI Flows that just work. Hand-picked Claude Code plugins that fire the right skill as you prompt.
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`](../autonomous-investigation/SKILL.md)
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`](../intelligence-collection-disciplines/SKILL.md)).
- **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.
- **Honest frequency.** *Recurring across sources* ≠ *concentrated in one thread* ≠ *isolated but
vivid*. Say which; one articulate ranter is not a theme.
- **When NOT to use:** no meaningful public footprint (early-stage, niche enterprise) → run
[`discovery-interview-prep`](../discovery-interview-prep/SKILL.md) instead; you need *your* users'
voice on a private area → mine your own tickets and research; statistical confidence required →
this is qualitative theming.
## Application
1. **Credit inline context**, then ask only the unanswered questions (max 3):
1. Whose customer voice — yours, a competitor's, or a set?
2. What decision should this inform?
3. Any specific theme to focus on, or open sweep?
2. **Show the 3-bullet search plan** — which voice sources you'll sweep, how you'll select
representative verbatims, how observation will be separated from interpretation. Continue unless
revised.
3. **Sweep mixed voice sources** — review sites (G2, Capterra, TrustRadius), app stores, Reddit and
practitioner forums, community boards, social threads — capturing short real quotes with URLs and
noting each source's bias.
4. **Emit the schema below exactly.**
### Output schema (do not reorder)
~~~markdown
# Voice-of-Customer Snapshot
## 1. Scope
**Products mined:** | **Decision supported:** | **Sources swept:** | **As-of date:**
## 2. Need Themes
For each of the top 3-5 themes:
### Theme: [Underlying need, solution-free, 4 to 8 words]
- **Frequency:** [recurring across sources / concentrated / isolated]
- **Verbatim:** "[short real quote]" — [source, URL]
- **Verbatim:** "[short real quote]" — [source, URL]
- **Who says it:** [role/segment, if evident — labeled]
- **Reading:** [Inference — what this suggests]
## 3. Competitor Weak Points
- **[Competitor]:** [weakness in customers' words; frequency; URL]
- [Max 5, strongest evidence only]
## 4. Switching Triggers
- [What pushes customers off a product; what pulls them; labeled, cited]
## 5. So What?
- **3** opportunity hypotheses (phrased as problems, not features)
- **2** battle-card-ready weaknesses (with evidence quality noted)
- **3** assumptions to validate in real interviews
Each bullet: label, confidence, URL where relevant.
~~~
A copy/paste fill-in version of this schema, with quality checks, lives in [`template.md`](template.md).
### Final Step (offer exactly 4 options)
1. Generate discovery interview questions from the top theme ([`discovery-interview-prep`](../discovery-interview-prep/SKILL.md))
2. Feed the weaknesses into a competitive battle card ([`battle-card-builder`](../battle-card-builder/SKILL.md))
3. Build an opportunity solution tree from the top hypothesis ([`opportunity-solution-tree`](../opportunity-solution-tree/SKILL.md))
4. Re-run scoped to one theme in Verbose Mode
Accept `1`, `2`, `3`, `4`, `1 and 2`, `Verbose Mode`, or a custom path.
## Examples
**A theme done right (fictional product, illustrative verbatims):**
> ### Theme: getting historical data out at contract end
> - **Frequency:** recurring — 9 reviews across two sites plus a forum thread, past 6 months
> - **Verbatim:** "export took three support tickets and still dropped custom fields" — [G2-style review, URL]
> - **Verbatim:** "we stayed a year longer than we wanted because leaving meant losing our audit trail" — [forum thread, URL]
> - **Who says it:** ops managers at 50-200-person firms — **Inference** (reviewer titles where shown)
> - **Reading:** exit friction is functioning as involuntary retention — **Inference**; a rival with
> effortless migration turns this from their moat into their churn event.
Notice the theme name contains no feature ("export tool") — it names the need, so discovery can
explore solutions the reviews never imagined.
See [`examples/sample.md`](examples/sample.md) for a complete worked mining run (fictional
FSM-software market) where frequency honesty caps a vivid theme at low confidence and each
source's bias becomes a reading instruction. [`examples/sample-industrial.md`](examples/sample-industrial.md)
shows the thin-voice case — what honest mining looks like when the market barely posts reviews.
## Common Pitfalls
- **Feature-name theming.** Clustering by the feature customers blame instead of the need underneath
hands your roadmap to the loudest UI complaint.
- **Verbatim laundering.** Paraphrasing a review and quoting it. If it has quote marks, it must be a
real excerpt at a real URL — this domain's do-not-invent list exists because fabricated customer
quotes are both tempting and toxic.
- **Rant amplification.** One vivid one-star review presented as a theme. Frequency honesty is the
discipline: recurring, concentrated, or isolated — say which.
- **Skew blindness.** Reading review sites as a census. The angry and the vocal are over-sampled;
the satisfied-and-silent majority never posts. Bias notes per source are mandatory.
- **Skipping the validation handoff.** Shipping themes straight into the roadmap. The output's
"assumptions to validate in real interviews" section is the bridge to discovery — use it.
## References
- [`autonomous-investigation`](../autonomous-investigation/SKILL.md) (Workflow) — the governing protocol
- [`intelligence-collection-disciplines`](../intelligence-collection-disciplines/SKILL.md) (Component) — OSINT review-mining sources and bias tradecraft
- [`jobs-to-be-done`](../jobs-to-be-done/SKILL.md) (Component) — the solution-free framing themes should land in
- [`discovery-interview-prep`](../discovery-interview-prep/SKILL.md) (Interactive) — where the validation happens
- [`opportunity-solution-tree`](../opportunity-solution-tree/SKILL.md) (Interactive) — structures the opportunity hypotheses
- [`battle-card-builder`](../battle-card-builder/SKILL.md) (Workflow) — consumes the weak points
- Adapted from `market-intelligence/voice-of-customer-miner-prompt.md` in the
`https://github.com/deanpeters/product-manager-prompts` repo.
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