kestrel actors › Hotel & flight prices

Hotel Rate Parity Checker — OTA Price Comparison

Hotel rate parity checker built on Google Hotels prices: for each property and stay you name, one row with every booking source Google lists side by side — Booking.com, Expedia, Hotels.com, Agoda, Trip.com, Vio.com, the property's official site — and the parity math already done: the cheapest and dearest source, the spread in percent, the direct rate, and which OTAs undercut it and by how much. It is an OTA price comparison and rate shopping tool for revenue managers, channel managers and owners, priced per row instead of per seat. Put it on a schedule and it becomes rate parity monitoring with a history you own. No API key, no login, no browser: it reads the same public comparison any traveller sees, through Apify's proxies, and returns clean JSON.

Run Hotel Rate Parity Checker on Apify →

Hotel rate parity pricing: what one row costs

Pay per event: one parity event per delivered parity row, at the price on this page's pricing tab. A comp set of ten properties checked over seven check-in dates is 70 rows; the same run with minSpreadPct set delivers — and bills — only the breaches. Properties with no rates for the stay, names that do not resolve, a property listed twice, rows removed by the filter, rows the spending limit refused and status rows are all free, and a property and stay is billed once per run. Apify's platform usage for such a run is a fraction of a cent: name lookups take one search each, every property and stay takes one offers call.

Compared with the parent Google Hotels Prices Scraper, which bills one row per source, a parity row is one event for the whole comparison — usually cheaper per property, and already in the shape a rate shopper wants.

Hotel rate parity input reference

Every field of Hotel Rate Parity — input, straight from the actor's input schema.

Example input

{ "hotels": ["https://www.google.com/travel/hotels/entity/ChkIhLCQwvjO2IYWGg0vZy8xMXE0bTZieDkyEAE", "ChkIg-b2ismUj7M1Gg0vZy8xMWg3MThreGg1EAE"], "checkIn": "30 days", "nights": 1, "adults": 2, "currency": "USD" }

{ "hotelNames": ["Hyatt Regency Lisbon", "Altis Grand Hotel Lisbon", "Brown's Avenue Hotel Lisbon"], "checkIn": "14 days", "nights": 2, "sweepDays": 6, "minSpreadPct": 5, "currency": "EUR", "country": "pt" }

Hotel rate parity output fields

Two row types share one dataset: parity (one property and stay with every booking source side by side and the parity math; charged) and status (per property and stay; never charged).

Dataset views in the Apify Console: Rate parity, Undercut check, Run status.

Example row from a real run

Taken from the actor's README — this is the shape your dataset holds.

{ "type": "parity", "query": "https://www.google.com/travel/hotels/entity/ChkIhLCQwvjO2IYWGg0vZy8xMXE0bTZieDkyEAE", "hotel_name": "Brown's | Avenue Hotel", "entity_id": "ChkIhLCQwvjO2IYWGg0vZy8xMXE0bTZieDkyEAE", "hotel_id": null, "hotel_url": "https://www.google.com/travel/hotels/entity/ChkIhLCQwvjO2IYWGg0vZy8xMXE0bTZieDkyEAE", "stars": null, "rating": null, "reviews": null,
  "check_in": "2026-09-27", "check_out": "2026-09-29", "nights": 2, "adults": 2, "children": 0, "currency": "USD",
  "sources": [
    { "source": "Vio.com", "source_id": 2017, "official": false, "price_nightly": 377.39, "price_total": 754.78, "free_cancellation": null, "url": "https://www.vio.com/…" },
    { "source": "Brown's Avenue", "source_id": 12058, "official": true, "price_nightly": 488.46, "price_total": 976.92, "free_cancellation": null, "url": "https://be.synxis.com/?hotel=…&arrive=2026-09-27&depart=2026-09-29" },
    { "source": "Booking.com", "source_id": 184, "official": false, "price_nightly": 563.3, "price_total": 1126.61, "free_cancellation": null, "url": "https://www.booking.com/hotel/pt/browns-avenue.html?checkin=2026-09-27&checkout=2026-09-29" },
    { "source": "Expedia.com", "source_id": 232, "official": false, "price_nightly": 573.94, "price_total": 1147.88, "free_cancellation": null, "url": "https://www.expedia.com/…" }
  ],
  "n_sources": 4, "min_source": "Vio.com", "min_price": 377.39, "max_source": "Expedia.com", "max_price": 573.94, "spread_pct": 52.1, "median_price": 525.88,
  "official_source": "Brown's Avenue", "official_price": 488.46, "official_is_cheapest": false, "undercut_by": ["Vio.com"], "undercut_pct": 22.7,
  "fetched_at": "2026-08-29T06:15:42+00:00" }

{ "type": "status", "query": "Brown's Avenue Hotel Lisbon", "hotel_name": "Brown's | Avenue Hotel", "entity_id": "ChkIhLCQwvjO2IYWGg0vZy8xMXE0bTZieDkyEAE", "check_in": "2026-09-27", "check_out": "2026-09-29", "status": "ok", "n_sources": 4, "spread_pct": 52.1, "filtered": false, "error": null, "fetched_at": "2026-08-29T06:15:42+00:00" }

Hotel rate parity in Python, JavaScript and curl

Python

from apify_client import ApifyClient
client = ApifyClient("<TOKEN>")
run = client.actor("kestrel/hotel-rate-parity").call(run_input={
    "hotelNames": ["Hyatt Regency Lisbon", "Altis Grand Hotel Lisbon"], "checkIn": "30 days", "nights": 2, "sweepDays": 6, "currency": "EUR", "country": "pt"})
rows = [r for r in client.dataset(run["defaultDatasetId"]).iterate_items() if r["type"] == "parity"]
for r in sorted(rows, key=lambda r: -(r["undercut_pct"] or 0)):
    if r["undercut_by"]: print(r["hotel_name"], r["check_in"], f'{r["undercut_pct"]}% under direct via {r["undercut_by"][0]} ({r["min_price"]} vs {r["official_price"]} {r["currency"]})')

JavaScript (Node)

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: '<TOKEN>' });
const run = await client.actor('kestrel/hotel-rate-parity').call({ hotels: ['ChkIhLCQwvjO2IYWGg0vZy8xMXE0bTZieDkyEAE'], checkIn: '30 days', nights: 1, minSpreadPct: 5 });
const { items } = await client.dataset(run.defaultDatasetId).listItems();
const lines = items.filter(r => r.type === 'parity' && r.undercut_by.length).map(r => `${r.hotel_name} ${r.check_in}: ${r.min_source} ${r.min_price} vs direct ${r.official_price} (${r.undercut_pct}%)`);
console.log(lines.join('\n') || 'in parity');

curl

curl -X POST "https://api.apify.com/v2/acts/kestrel~hotel-rate-parity/run-sync-get-dataset-items?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"hotels": ["ChkIg-b2ismUj7M1Gg0vZy8xMWg3MThreGg1EAE"], "checkIn": "30 days", "nights": 1, "currency": "USD"}'

The same three calls are runnable files in the examples repository: examples/hotel-rate-parity.py|.js|.sh.

Limits and honest notes

FAQ

Does it need a Google Hotels API key or a Google account?

No. There is no public API for reading Google Hotels prices; the actor reads the public results through Apify's proxies. No login, cookies or API key.

What is rate parity, in the terms this actor uses?

Rate parity means the same room sells for the same price on every channel, including your own site. The row measures it two ways: spread_pct is the gap between the cheapest and dearest source across the market, and undercut_pct is how far the cheapest channel beats your direct rate. A rate parity check is a scan of undercut_by; a hotel rate audit is that column over time, and official_price is your direct booking rate as Google shows it. Google Hotels rate parity, in short, is what a guest comparing channels on Google actually sees.

Can it run a rate parity check for my whole comp set every morning?

Yes: list the properties in hotels (or hotelNames for the first run), use a relative checkIn, add sweepDays for the booking window, and schedule the actor in Apify Console. Every run appends dated rows; minSpreadPct keeps the feed to breaches.

Why is the OTA cheaper than my official site?

Usually a wholesale or bed-bank rate resold on a metasearch-facing OTA, a member price shown to everyone by a listing site, or a stale rate on a channel you stopped updating. The sources array names the exact source and gives its booking link, so the trail starts from the row.

Which booking sites are compared?

Every source Google Hotels lists for that property and market — the big OTAs, metasearch resellers and regional sites — plus the official site when Google identifies one. Names and source_ids come straight from Google.

Does the price include taxes and fees?

It is the nightly and total figure Google Hotels shows for your market. Some markets display all-in prices, others add taxes later; set country to the market you sell in so every source follows the same rule.

How is this different from the Google Hotels Prices Scraper?

Same data, different shape. The parent returns one row per source (and can go to room level); this one returns one row per property and stay with the comparison and the parity math done, filters on spread before billing, and accepts names. Use the parent when you need every source as its own row or room-level offers.

Is there a free tier?

Yes: Apify's free plan covers small runs, and a run that delivers no parity rows costs nothing.

Last verified working: 2026-08-29.

How to use Hotel Rate Parity Checker

• How to Scrape Google Hotels Prices with Python — Google Hotels prices for exact dates, every OTA per property, in one call. Plus the silent failure mode: Google never says it did not find your place.
• How to Check Hotel Rate Parity Across OTAs — Find out when an OTA undercuts your direct rate: one row per property per date with every source compared, the spread and who is cheapest.
• Pay Per Event vs Per Result: Scraper Pricing — How scraper pricing models differ, why the per-row price is not the cost, and the four questions that decide what a scraping job actually bills you.
• How to Schedule a Scraper So It Never Goes Stale — Hard-coded dates rot the day after you set them. Relative date inputs keep a scheduled scraper meaning the same thing every morning — here is the grammar.

Ready-made runs you can open and start

Each one is a saved input on the Apify Store — open it, press Start, and it runs with the fields already filled in. All 163 across the suite.

Related scrapers

• Google Hotels Prices Scraper — need every source as its own row, room-level offers, or a whole city search? That is the parent of this actor.
• Agoda Reviews Scraper — Agoda guest reviews with separate positives and negatives.
• Airbnb Reviews Scraper — every guest review of an Airbnb listing, with translations.
• Airbnb Scraper — Airbnb prices, availability calendars and occupancy.
• Google Flights Scraper — airfare for a route and date, with a cheapest-day sweep.

Run Hotel Rate Parity Checker

The actor lives on the Apify Store, where the pricing tab carries the live per-row price and the input form has every field above: apify.com/kestrel/hotel-rate-parity