Review Mining for Positioning
Mine the reviews of your category — what buyers praise, what they complain about, why they switch — and turn it into positioning that uses their words.
Product Marketing - Positioning
Positioning in the market's own words — mined from category reviews
3
Message pillars
Buyer voice, not jargon
Competitors' #1 complaint: surprise
bills. That's a pillar we can own.
Competitors' #1 complaint: surprise
bills. That's a pillar we can own.
| Pattern | Buyer voice |
|---|---|
| Top complaint | 'Bill surprised us' |
| Top praise | 'Powerful once set up' |
| Switch trigger | 'Got too expensive' |
Why it lands
Internal positioning decks use internal words. Buyers say 'the bill surprised us' and 'it got too expensive at scale.' Mining the reviews lets you position in the exact language the market already uses to describe the pain.
Overview
Mine TrustRadius reviews across a product category to surface what buyers consistently praise, complain about, and switch for — then translate those buyer-voice patterns into positioning angles and message pillars that use the market's own language.
Use cases
Position in the buyer's words
The most persuasive positioning uses the exact phrases buyers use. Review mining hands PMM those phrases — and the complaints competitors consistently earn become your white space.
Message pillars with evidence behind them
Each pillar traces to a recurring review theme, so when sales asks 'why this message?' the answer is the market's own voice, not a brainstorm.
View workflow prompt
# Review Mining for Positioning
## Parameters
- `{{category}}` *(required)* — The product category to mine. Example: `observability`
- `{{our_product}}` *(required)* — Our product, for positioning the angles. Example: `unified observability platform`
- `{{key_competitors}}` *(optional)* — Competitors whose reviews to weight. Example: `Datadog, New Relic`
## Purpose
Mine reviews across the {{category}} (weighting {{key_competitors}}) to extract the buyer-voice patterns — praise, complaints, switch triggers — and turn them into positioning angles and message pillars for {{our_product}} that speak the market's language.
## Process
Run the tools immediately and produce the full output — do not pause to summarize the reference skills. Bound to ~6 tool calls.
1. **Scope the category** — `get_product_category` + `get_vendor_information` to identify the products whose reviews define the category. One pass each.
2. **Mine reviews** — `get_product_reviews` for {{key_competitors}} (and one or two more category leaders); cluster into Praise, Complaints, and Switch Triggers.
3. **Find the white space** — identify the complaints competitors consistently get that {{our_product}} could own.
4. **Build pillars** — translate the white space into 2-3 message pillars using buyer language from the reviews (per pvp-composition).
5. **Angles** — draft a positioning angle per pillar, kept human and specific.
## Output Format
Markdown with:
- `# Review-Mined Positioning — {{category}}`
- `## Buyer Voice` (Praise / Complaints / Switch Triggers, cited)
- `## White Space` (complaints competitors own that we can take)
- `## Message Pillars` (2-3, in buyer language)
- `## Positioning Angles` (one per pillar)
- `## Citations`
## Quality Checklist
- Buyer-voice patterns cite `get_product_reviews`
- Message pillars use language drawn from real reviews, not internal jargon
- White space is a complaint competitors consistently get, not a guess
- Angles are specific and human