Every event that will move hotel demand in a city, with roomnights, pressure and booking window.

Read every hotel listed in a district — price, rank, score, distance to the metro — and diff two days to see who entered the listing, who vanished and who moved.

Fetch a live Booking.com rate for a hotel and stay, on demand.

Inbound flight rates as a leading indicator of hotel demand.

One score built from every OTA your hotel is listed on, the sentiment split behind it, and which categories are actually moving — rendered on your own site, behind a proxy that keeps your API key private.

Rate, occupancy, comp-set price, review sentiment, rank and the city’s event calendar answer the same question at once, under one key, in one conversation.

One request returns every hotel on sale in a destination for a given night — price, score, stars, room type and cancellation — instead of asking hotel by hotel. 192 properties for 0,32 credits.

Register Barcelona as a location and read its event calendar with hotel demand attached: roomnights per day, pressure against the city's 40.000 rooms, and which ring of the city those rooms sit in.

Sold-out dates, blackout nights and demand spikes across the market — the pace signals your operators can see and you usually cannot.

Every event that will move hotel demand in a city, with roomnights, pressure and booking window.

Read every hotel listed in a district — price, rank, score, distance to the metro — and diff two days to see who entered the listing, who vanished and who moved.

Fetch a live Booking.com rate for a hotel and stay, on demand.

Inbound flight rates as a leading indicator of hotel demand.

One score built from every OTA your hotel is listed on, the sentiment split behind it, and which categories are actually moving — rendered on your own site, behind a proxy that keeps your API key private.

Rate, occupancy, comp-set price, review sentiment, rank and the city’s event calendar answer the same question at once, under one key, in one conversation.

One request returns every hotel on sale in a destination for a given night — price, score, stars, room type and cancellation — instead of asking hotel by hotel. 192 properties for 0,32 credits.

Register Barcelona as a location and read its event calendar with hotel demand attached: roomnights per day, pressure against the city's 40.000 rooms, and which ring of the city those rooms sit in.

Sold-out dates, blackout nights and demand spikes across the market — the pace signals your operators can see and you usually cannot.

The hotel is half the setup. Without the competitors attached, every rate, parity and reputation answer comes back about you alone — which is a price list, not a comparison.

Spot where your rate breaks parity across OTAs versus your direct price.

Pull a hotel's Booking.com reviews as structured JSON — no scraper to maintain.

Compare your comp set product by product — same board, same cancellation policy — instead of the cheapest-rate-per-hotel table that quietly puts your flexible rate against someone else's non-refundable.

Ask your assistant to size up a city you do not operate in yet — supply, price bands, review scores, who is winning — and get the answer as a briefing, not a spreadsheet.

Create an accommodation, a location, a location search and a flight from the dashboard — the four things every Feed and Real Time endpoint asks you to point at, and what each one is actually for.

What your competitors charge, how they rank and what their guests write — crossed in one question, so a gap surfaces the day it opens rather than in next week’s report.

Answer what you spent, why a given line cost what it cost, and what a new scenario would cost — with the step-by-step credit calculation the dashboard hides behind one icon.

Every event that will move hotel demand in a city, with roomnights, pressure and booking window.

The hotel is half the setup. Without the competitors attached, every rate, parity and reputation answer comes back about you alone — which is a price list, not a comparison.

Spot where your rate breaks parity across OTAs versus your direct price.

Pull a hotel's Booking.com reviews as structured JSON — no scraper to maintain.

Compare your comp set product by product — same board, same cancellation policy — instead of the cheapest-rate-per-hotel table that quietly puts your flexible rate against someone else's non-refundable.

Ask your assistant to size up a city you do not operate in yet — supply, price bands, review scores, who is winning — and get the answer as a briefing, not a spreadsheet.

Create an accommodation, a location, a location search and a flight from the dashboard — the four things every Feed and Real Time endpoint asks you to point at, and what each one is actually for.

What your competitors charge, how they rank and what their guests write — crossed in one question, so a gap surfaces the day it opens rather than in next week’s report.

Answer what you spent, why a given line cost what it cost, and what a new scenario would cost — with the step-by-step credit calculation the dashboard hides behind one icon.

Every event that will move hotel demand in a city, with roomnights, pressure and booking window.

The classic rate-shopping grid: your hotel against its comp set, live from Booking.com.

Your guest score, review volume and category breakdown across every OTA, against your comp set.

People book the flight before the room. Register the routes your guests arrive on and you get the fare re-priced every day — a demand signal that moves before your own pace does.

Take any hotel from Booking, add it to Veetal and pull its multi-OTA reputation — score, review count and category breakdown from Booking.com, Tripadvisor and Google — ready to read over the API.

Run a live Booking.com rate call from the dashboard playground, read the response, and copy the same request into Postman or your own code without writing a line of it yourself.

Read every review across every OTA at once and ask what the recurring themes are, which are getting worse, and which of them your score is hiding.

ADR, ranking, parity and rating for every hotel in the portfolio, on the same scale, so the outlier is obvious without opening twelve dashboards.

Live rates and availability, on demand, so your pricing reacts on the day demand shifts instead of the morning after the extraction.

The hotel is half the setup. Without the competitors attached, every rate, parity and reputation answer comes back about you alone — which is a price list, not a comparison.

The classic rate-shopping grid: your hotel against its comp set, live from Booking.com.

Your guest score, review volume and category breakdown across every OTA, against your comp set.

People book the flight before the room. Register the routes your guests arrive on and you get the fare re-priced every day — a demand signal that moves before your own pace does.

Take any hotel from Booking, add it to Veetal and pull its multi-OTA reputation — score, review count and category breakdown from Booking.com, Tripadvisor and Google — ready to read over the API.

Run a live Booking.com rate call from the dashboard playground, read the response, and copy the same request into Postman or your own code without writing a line of it yourself.

Read every review across every OTA at once and ask what the recurring themes are, which are getting worse, and which of them your score is hiding.

ADR, ranking, parity and rating for every hotel in the portfolio, on the same scale, so the outlier is obvious without opening twelve dashboards.

Live rates and availability, on demand, so your pricing reacts on the day demand shifts instead of the morning after the extraction.

The hotel is half the setup. Without the competitors attached, every rate, parity and reputation answer comes back about you alone — which is a price list, not a comparison.