Review MonitoringAutomation
Every new review from every platform in one feed, sorted by urgency, with a drafted reply ready for a person to approve.
Review Monitoring Automation: what the work involves
Reviews appear on Google, Facebook, app stores, marketplaces and delivery apps, and each has its own login and notification habits. A one-star review about a missed delivery can sit unanswered for weeks, while the business assumes no news is good news. Replying well takes time that busy owners rarely have, so responses are late, copy-pasted or absent.
We pull reviews through official APIs and approved export routes into one database and deduplicate them. A classifier tags each review by topic, such as service, price or cleanliness, and urgency. A language model drafts a reply in your tone that mentions the specific point raised and, for complaints, proposes a next step. Replies are never invented offers: they use a policy sheet you maintain. A manager approves or edits in a queue and the response is posted back where the platform allows it. Alerts go to the right branch lead, and a monthly report summarises themes, with representative quotes rather than averages alone.
Core features
Single review inbox
Reviews from Google, Facebook, app stores and marketplaces arrive in one list with source and branch noted.
Topic and urgency tagging
Each review is tagged for what it concerns and how pressing it is, so serious complaints rise to the top.
Drafted replies in your tone
The reply refers to the actual issue and follows your policy sheet, leaving the manager to edit and approve.
Branch-level alerts
Negative reviews go straight to the responsible branch lead in chat, not to a generic inbox nobody checks.
Reply posting where allowed
Approved replies are posted through platform APIs, or prepared for one-click copy where posting is restricted.
Monthly theme report
A summary shows recurring praise and complaints with real quotes, by branch and period.
What we get right before launch
Platform access rules
Not every platform offers a review API, and scraping can breach terms. We use official access where it exists and clearly mark sources that need manual handling.
Replies that make promises
An auto-drafted apology that offers a refund can create obligations. Drafts only use approved remedies, and complaint replies always wait for human approval.
Fake or incentivised reviews
Detecting fakes is unreliable. We flag unusual patterns for a person to look at, and do not auto-report or ignore reviews on the model's guess alone.
Tools and technology
- Google Business Profile API
- OpenAI
- Python
- Node.js
- n8n
- PostgreSQL
- Slack API
- Twilio
Common questions, answered
Can it reply to reviews automatically?
It can post replies, but we recommend approval for anything negative. Positive thank-you replies can be automated if you wish. Public replies represent your brand, so a person should own the sensitive ones.
Which platforms can you connect?
Google Business Profile, Facebook pages and app stores have usable routes. Others depend on their terms and APIs. We confirm what is possible per platform during scoping rather than assume.
Does it handle Urdu or Roman Urdu reviews?
Yes, with the usual caveat that casual Roman Urdu is harder. Replies can be drafted in the reviewer's language, and uncertain cases are shown to your staff before sending.
Can it help us win back unhappy customers?
It can surface the complaint fast and draft a considerate reply, which helps. Whether the customer returns depends on how your team resolves the problem, which no tool can do for you.
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Ready to start your Review Monitoring Automation project?
Tell us what you need and we will come back with a clear scope, timeline and the questions worth answering before any build starts.