Mindcase for Travel and Hospitality Reputation Management

A hotel doesn't have one reputation — it has four, one per platform, and they don't move together. A property can hold 4.5 stars on Google Maps while a cluster of one-star TripAdvisor reviews about a noisy renovation sits unanswered, or vice versa. Checking one site and calling it "the reviews" misses whatever's building on the other three.

If you're an agent (or building one) reading this rather than a human, the full machine-readable schema for every endpoint below lives at mindcase.co/skills.md.

What does a reputation-monitoring agent actually need to watch?

Four review sources, pulled on the same schedule, read as one feed instead of four separate checks: Google Maps Reviews, Yelp Reviews, TripAdvisor Reviews, and — specific to lodging — Booking Reviews, which covers the reviews left on a hotel's own Booking.com listing rather than its general business page. A restaurant or bar skips Booking entirely and runs the other three; a hotel runs all four.

The job isn't collecting reviews. It's collecting them on a recurring schedule, in one place, so a new pattern across sources shows up before a guest complaint on one site becomes three.

How do you pull all four sources for one property?

Say you're running reputation monitoring for a mid-size hotel. Each endpoint takes the same shape — one place URL in, one row per review out — so the pull is four calls with the same structure, one per source:

curl -X POST "https://api.mindcase.co/v1/data/booking/reviews/run?wait=true" \
-H "Authorization: Bearer $MINDCASE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
  "params": {
    "urls": "https://www.booking.com/hotel/us/the-plaza.html",
    "maxReviewsPerHotel": 50,
    "sortBy": "f_recent_desc"
  }
}'

# $0.002 per review

Swap the endpoint and URL and the same request shape pulls the other three: urls plus a maxReviews-style cap, most recent first. Four calls, run on the same cadence — daily or weekly, whatever the property's review volume justifies — land four rows-per-review datasets an agent can merge into one timeline by postedDate.

How do you turn four feeds into one reputation signal?

By reading past the star rating into the fields each endpoint already returns. Booking Reviews' liked/disliked pair separates what a guest praised from what they didn't in the same review — useful for tagging a complaint by theme (noise, cleanliness, check-in wait) without re-parsing free text. Google Maps Reviews' ownerResponse and ownerResponseDate show whether the property is actually replying, and how fast. TripAdvisor Reviews' tripType and travelDate let an agent separate a business traveler's one-night complaint from a family's week-long stay. None of these fields exist on all four sources — that's the reason to pull all four instead of picking the biggest one.

The pattern worth flagging isn't a single bad review. It's the same complaint — a renovation, a staff turnover, a maintenance issue — showing up across two or more of the four sources in the same week. That's a signal a general manager should see before the count climbs, not a monthly summary they read after it already has.

There's also a source-specific tell worth watching on its own: a gap between a property's Booking.com rating and its TripAdvisor rating for the same stretch of dates. Booking's reviewer pool is limited to guests who booked through the platform; TripAdvisor's is open to anyone who claims to have stayed. A wide, sustained gap between the two — not a one-off outlier review — is often the first sign that something changed in how the property is actually running, before it shows up as a drop in the aggregate star rating on any single site.

What does each source add that the others don't?

The fields and the cost per row differ enough to matter for how an agent weighs a result. Google Maps Reviews returns 31 fields per row — the widest of the four — and bundles the business's own aggregate rating and category alongside each review, at $0.00025 per review. Yelp Reviews returns 16 fields, including public owner replies and reaction counts, also at $0.00025. TripAdvisor Reviews returns 20 fields with trip-type and travel-date context specific to travel planning, at $0.002 per review. Booking Reviews returns 18 fields — including room, checkIn, and checkOut dates tied to the actual stay — also at $0.002 per review, since it's pulling from the same booking platform the guest stayed through.

A 50-review pull across all four sources — 200 reviews total — costs $0.0125 on Google and Yelp combined for 100 reviews, plus $0.20 on TripAdvisor and Booking combined for the other 100: $0.2125 for the full picture on one property, once.

What can't you get from Mindcase?

Two cases.

A source a guest didn't use has nothing to return. A hotel with no TripAdvisor reviews yet returns nothing from that endpoint — the same is true for a manual check of the TripAdvisor page itself. Coverage across all four sources depends on where guests actually leave reviews, not on what the API can pull.

Sentiment scoring isn't part of the response. Each endpoint returns the review text and its structured fields — rating, dates, reviewer details — not a computed sentiment label. Turning liked/disliked pairs or free review text into a theme count or a trend line is work the receiving agent does after the pull, the same way it would with data from any of these four sources on its own.

Which endpoint should you use for which property?

FAQ