Sentiment Monitoring
When to Use
- Founder wants to track what customers and the public are saying about their product
- Founder wants to catch bad reviews early and respond before they spread
- Founder wants to understand community sentiment trends over time
- Founder wants to monitor specific review platforms for new reviews
This is different from review-mining (mining competitor reviews for pain points). This skill monitors your OWN product's reputation.
Context Required
- Product name and any common misspellings or abbreviations
- Platforms to monitor — the founder must provide the list of places to watch. Common options:
- Product Hunt (product page reviews and comments)
- Google Maps / Google Business reviews
- G2, Capterra, TrustRadius
- Trustpilot
- App Store / Play Store
- Reddit mentions
- Twitter/X mentions
- Hacker News mentions
- Industry-specific forums
- Monitoring frequency (daily for post-launch, weekly for steady state)
- Response policy — does the founder want draft responses for negative reviews?
- Escalation threshold — what severity warrants immediate attention?
Workflow
- Set up the monitoring list — the founder provides which platforms to watch. For each platform, note:
- Direct URL to the product's review/listing page
- Current rating and review count (baseline)
- How to check for new reviews (RSS, manual, API, or alert tool)
- Define the severity scale — categorize incoming sentiment:
- Critical (respond within 24h): public accusations of data loss, security issues, billing fraud, or legal threats. 1-star reviews with detailed complaints that could go viral.
- Negative (respond within 48h): legitimate complaints about bugs, missing features, poor support, or pricing frustration. 1-2 star reviews.
- Mixed (respond within 1 week): 3-star reviews with constructive feedback. "Good product but..."
- Positive (acknowledge): 4-5 star reviews. Thank the reviewer, ask for referrals.
- Scan platforms — check each platform on the founder's list for new reviews, mentions, or discussions since the last scan.
- Analyze each finding — for every new review or mention:
- Platform and date
- Sentiment: positive / mixed / negative / critical
- Core issue: what specifically is the person saying (quote verbatim)
- Validity: is this a legitimate product issue, user error, or bad-faith review?
- Impact: how visible is this? (high-traffic platform, many upvotes, or buried)
- Pattern: does this match other recent complaints? (signals a systemic issue)
- Draft responses — for negative and critical reviews, draft a response that:
- Acknowledges the issue without being defensive
- Shows the complaint was heard and understood
- Offers a specific next step (DM, email, fix timeline)
- Is written in the founder's voice, not corporate PR speak
- Flag patterns — if 3+ reviews mention the same issue, escalate it as a product issue, not just a review problem.
- Generate the sentiment report — summary of findings with trends.
Output Format
markdown## Sentiment Report — [Date Range] ### Overview - **Reviews scanned:** [count across all platforms] - **New since last scan:** [count] - **Sentiment breakdown:** [X positive, Y mixed, Z negative, W critical] - **Average rating trend:** [up/down/stable vs. last period] ### Critical & Negative Items (action required) **[Platform] — [Star Rating] — [Date]** > "[Verbatim quote or summary]" - **Core issue:** [what they're actually complaining about] - **Validity:** [Legitimate / User error / Bad faith] - **Pattern:** [First mention / Recurring — also seen on X, Y] - **Suggested response:** > [Draft response in founder's voice] ### Emerging Patterns | Issue | Mentions This Period | Platforms | First Seen | Trend | |-------|---------------------|-----------|------------|-------| | [Issue] | [count] | [platforms] | [date] | [new / growing / stable] | ### Positive Highlights - [Platform]: "[positive quote]" — consider using as testimonial - [Platform]: "[positive quote]" — share on social ### Recommended Actions - [ ] Respond to [N] critical/negative reviews (drafts above) - [ ] Investigate [issue] — mentioned [N] times across [platforms] - [ ] Request reviews from happy customers to offset [negative trend]
Frameworks & Best Practices
Response principles for negative reviews:
- Speed matters — respond within 24-48 hours. Unanswered negative reviews signal "they don't care."
- Acknowledge, don't argue — "I hear you" beats "Actually, you're wrong" every time
- Take it offline — "I'd love to look into this — can you email me at founder@company.com?" moves the conversation out of public view
- Be the founder — sign with your name and title. "— Alex, CEO" hits differently than a generic support reply
- Fix the issue, then update — come back to the review after fixing the problem: "We shipped a fix for this last week"
Platform-specific notes:
| Platform | Review visibility | Response capability | Notes |
|---|---|---|---|
| Product Hunt | High (launch day) | Comments only | Critical during and after launch. Engage in comments actively. |
| Google Maps | High (local SEO) | Owner response | Directly affects local search ranking. Respond to everything. |
| G2 | High (B2B buyers) | Vendor response | Enterprise buyers read these. Detailed responses matter. |
| Trustpilot | High (consumer) | Business response | Invite happy customers to balance. TrustScore affects visibility. |
| App Store | High (affects downloads) | Developer response | Apple limits response frequency. Be concise. |
| Variable | Comment as user | Don't astroturf. Be transparent about who you are. |
When negative reviews are actually gifts:
- Specific, actionable complaints point to real product gaps — treat them as free user research
- A pattern of "love the product but X is broken" means you have product-market fit with a fixable issue
- No negative reviews at all usually means no one is using the product
Common mistakes:
- Monitoring without responding (worse than not monitoring)
- Getting defensive or arguing publicly with reviewers
- Only monitoring one platform (customers complain wherever they are, not where you're watching)
- Treating all negative reviews equally (a billing fraud accusation ≠ a UI complaint)
- Not feeding review insights back into the product roadmap
Related Skills
review-mining— for mining COMPETITOR reviews (this skill monitors YOUR reviews)feedback-synthesis— for synthesizing feedback patterns into product decisionschurn-analysis— negative reviews often correlate with churn signalscommunity-discovery— to find communities where people discuss your product
Examples
Prompt: "Set up monitoring for our reviews. We're on Product Hunt, G2, Trustpilot, and the App Store."
Good output includes: Monitoring checklist for all 4 platforms with current baselines, severity scale customized to the product, and a template for the weekly sentiment report.
Prompt: "We got 3 bad reviews on G2 this week. Help me respond."
Good output includes: Analysis of each review (core issue, validity, pattern detection), draft responses in the founder's voice, and a flag if the issues point to a systemic product problem.
