Travel & Hospitality · Review sentiment analytics
A one-star trend hides in your inbox for six weeks before it hits your score
Banao builds review sentiment pipelines that pull guest feedback from OTAs, Google, and internal surveys into a single operational view — themes by property, by department, and by week — so the GM sees a housekeeping pattern before it lands in your aggregate rating.
The system does not surface a sentiment score. It surfaces the complaint cluster: third-floor rooms smell, check-in wait exceeds 15 minutes on Friday arrivals, breakfast station runs out by 9 AM on weekends. Operations act on themes, not averages.
The first call is free · 45 minutes · no obligation
What we build
What the sentiment pipeline delivers
Sentiment analytics is not a dashboard. It is the ingestion, the topic modelling, the routing logic, and the weekly brief that operations actually reads — we build all four.
Multi-source review ingestion
Reviews pulled from Google, TripAdvisor, Booking.com, Expedia, and internal guest-survey tools into a single normalised store — no manual export, no tab-switching.
Department-level topic clustering
NLP clusters complaints and praise by operational area — housekeeping, front desk, F&B, maintenance, noise — so themes surface by department, not just by overall rating.
Property and period comparison
Side-by-side trend lines across properties and time periods, so a regional GM sees whether a check-in complaint is one property or a chain-wide pattern.
Weekly operational brief
A concise digest routed to the GM and relevant department heads each week: top three recurring complaints, any new spike, movement from last week. Designed to be read in under five minutes.
Response draft generation
Draft OTA response text generated per review, grounded in the property's standard voice and the complaint category — reviewed and posted by the team, not auto-published.
Alert on sudden sentiment drop
When a new complaint cluster exceeds a threshold in a 7-day window, an alert fires before the aggregate rating shifts. Early warning, not post-mortem.
Dogfooding
We operate on our own AI — yours runs the same standard
Banao's own 300-person operation runs on the same AI systems we deploy for clients. InterviewGod screens our hiring; Vikaas runs our demand generation. Every product we hand over has already survived internal use — edge cases, staff override, and all.
A review analytics pipeline that handles an operation this varied is already battle-tested before it reaches your property group. We do not brief clients on AI from a vendor brochure.
Screens every Banao engineering hire before a recruiter opens the shortlist.
Runs Banao's own demand-gen pipeline — the same NLP pattern applied to operational feedback.
The honest version
When review sentiment analytics is not the right starting point
We will tell you before you build it if the conditions are not right:
- Low review volume: below roughly 50 reviews a month per property, topic clustering produces too few examples per theme to be reliable. A manual weekly read is faster and cheaper.
- Single-property with an active GM reading every review: if the GM already reads each one, a pipeline adds process without adding information. We build for teams who cannot read every one.
- Operational issues already known internally: if the same complaint has been raised in team meetings for months, the pipeline will confirm it — but the fix is operational, not analytical. We will say so.
How we start
How we start — confirm the signal before the build
We do not scope a sentiment pipeline off a feature list. We look at your actual review data first.
- 01
AI Discovery Sprint
2 weeks · fixed price
We ingest a sample of your existing reviews across sources, run topic clustering on real data, and hand back a theme map and a gap analysis on coverage, volume, and routing — yours to keep regardless of next steps. Sprint cost credited against the build if you proceed.
- 02
Build
Full ingestion pipeline, topic model trained on your properties, weekly brief template, and alert rules — delivered integrated with your team's tools (email, Slack, or dashboard embed).
- 03
Operate & refine
Monthly model review against new review volume, topic taxonomy updates as property operations change, and expansion to new sources or properties as the rollout matures.
FAQ
Frequently asked questions
Which OTAs and review sources do you cover?
The standard ingestion covers Google, TripAdvisor, Booking.com, and Expedia. Internal guest-survey tools (post-stay email, NPS platforms) and additional OTAs are added in the build phase. The Discovery Sprint maps what sources are available for your properties and what coverage gaps exist.
How long until the first weekly brief?
After the Discovery Sprint, the build phase runs 6–10 weeks depending on source count and integration complexity. The first live brief goes to the GM team as soon as the ingestion and clustering pipeline is in production — typically starting with the highest-volume sources before all integrations are complete.
Can it generate OTA responses automatically?
The system generates response drafts grounded in the property's voice and the complaint category. Auto-publishing is not recommended — the team reviews and posts each response. Draft generation removes most of the time cost; human review keeps the reply quality and the brand voice intact.
How do we know the topic clusters are accurate?
During the Discovery Sprint we validate cluster outputs against a sample the GM team reviews manually. Topic taxonomy is adjusted until the themes match how operations actually categorises complaints. After go-live, the brief includes a confidence indicator and a straightforward override to re-label outliers.
Will this work across multiple properties?
Yes — multi-property is the primary use case. The pipeline aggregates by property and surfaces both individual property themes and cross-property patterns. A cluster appearing at 30% of properties is surfaced differently to regional leadership than one isolated to a single location.
Get started
Bring your last three months of reviews to a 45-min call
In 45 minutes we will identify which complaint clusters are hiding in your OTA reviews and whether your review volume supports reliable topic modelling across your property set.
Book a Discovery Sprint