Review Response Queue
Import reviews from any platform, auto-classify sentiment and urgency, draft an on-brand reply for a manager to approve or edit, and route serious negatives for escalation - so every review gets a timely, human-approved response.
A private, team-only queue where imported reviews are classified, AI-drafted replies wait for a manager's approval, escalations are logged, and you can export a clean response-tracking CSV.
Before you start
- A free Supabase account
- A free Vercel account
- A free Resend account (for notifications)
- A reviews export (CSV) from your review platforms - or a Google Sheet you can download as CSV
The problem this kills
Reviews come in across Google, Yelp, Trustpilot, app stores, your booking platform - and they pile up faster than anyone can answer. The five-star ones get ignored. The angry one-star post sits unanswered for a week while it climbs to the top of your listing. Replies get written from scratch every time, in slightly different voices, and nobody can say for sure which reviews already got a response.
Meanwhile the genuinely dangerous reviews - the ones alleging fraud, safety problems, or legal threats - get the same treatment as "the parking was tight," because there's no system that tells the difference.
You don't need a six-figure reputation platform to fix this. You need a queue that reads every review, flags the urgent and the legally sensitive ones, drafts a reply in your brand voice, and then makes a human approve it before anything is marked ready to post.
What you'll build
A small private web app for your marketing/reputation team:
- Import reviews from any platform by uploading a CSV export (platform, rating, text, date, reviewer). No API needed.
- Auto-classify each review for sentiment (positive / neutral / negative) and urgency, and flag anything that looks policy-violating or legally sensitive.
- Draft an on-brand reply for each review using your own templates and tone.
- Human approval gate: a manager reviews each drafted reply, edits it, and approves it - only then is it marked "ready to post." Nothing is ever auto-posted.
- Escalation routing: serious negatives are routed to the right person and logged, with an email alert via Resend.
- Response-tracking CSV export in the exact columns your team or platform expects.
What's inside the Implementation Plan
The plan is a single file you paste into Claude Code (a free AI coding tool). It walks the AI through building the whole thing, step by step, with a ready-to-copy prompt at the end of each step.
The best part: the plan opens by interviewing you about your business - which review platforms you use, how your export columns are named, your real rating scale, your reply templates and brand voice, your escalation rules, and the messy edge cases (fake reviews, competitor spam, reviews in other languages). It then reflects a short tailored spec back to you and waits for your thumbs-up before building anything. You get a tool shaped around how you actually work - not a generic template.
The governance it includes (this is the point)
- Login so only your team can open the queue.
- Row-level security so each organization only ever sees its own reviews and replies.
- A complete audit trail - who imported, who edited, who approved, and exactly when.
- A hard human-in-the-loop approval gate - the AI drafts, a person reviews and approves, and only then is a reply marked ready to post. Nothing reaches your listings automatically.
- Duplicate guards - a dedupe key of platform + review ID means the same review can never be queued twice.
Who it's for
Marketing and reputation-ops managers who handle reviews across multiple platforms and want timely, consistent, on-brand responses without letting an AI loose on their public listings. If you can fill in a spreadsheet, you can build and run this.
You've got this - paste the first prompt and let the interview tailor the rest.