Case study · Hospitality
AI-Native Reputation Command Center
Tea estate bungalows, wildlife safari lodges and hill resorts across several states, many in remote locations.
Engagement record
- Client
- Luxury hospitality group
- Industry
- Hospitality
- System
- Guest reviews · Root-cause analysis · Revenue at risk
About this write-up
This case study describes the engagement as recorded. The client is not named; figures and outcomes are as reported by the client and have not been independently audited.
The challenge
Reviews were read once a month, the same complaints kept coming back, and unhappy guests usually posted a public review before anyone at the property knew there was a problem.
Objectives
- Every review in one place
- Complaints grouped by cause
- Tasks for each department
- Catch unhappy guests mid-stay
Discovery
We built this reputation platform for a luxury hospitality group running tea estate bungalows, wildlife lodges and hill resorts. It reads reviews from Google, OTAs and in-stay WhatsApp and QR feedback in several languages, groups complaints by their real cause, routes each issue to the right department with a deadline, catches unhappy guests before they check out, and shows how much revenue each unresolved issue puts at risk.
What was built
- Every review in one place. Google, TripAdvisor, Booking.com, MakeMyTrip, Agoda and in-stay WhatsApp and QR feedback together.
- Complaints grouped by cause. Reviews about cold rooms, slow hot water or late breakfasts grouped into the one issue behind them.
- Tasks for each department. Each issue goes to housekeeping, F&B, engineering, front office or guides with a deadline.
- Catch unhappy guests mid-stay. A WhatsApp check-in during the stay alerts the manager before a guest posts a bad review.
- Revenue at risk. Shows how much booking revenue each unresolved issue is likely to cost, in rupees.
- Replies in the brand's voice. Drafts thoughtful review replies in several languages for managers to approve.
Outcomes as reported
Reported summary: −65% — recurring guest complaints.
| Figure | What it refers to |
|---|---|
| −65% | Recurring guest complaints |
| > 72% | Of in-stay issues resolved before checkout |
| < 45 min | Weekly review analysis, down from 12 hours |
Figures as reported in the engagement record; not independently audited.
