Booking.com Reviews Scraper — Score, Text, Guest Name

Get the guest reviews of any Booking.com hotel or stay as a clean table: score, review text, guest name and stay date, plus a signal that flags sudden spikes of reviews. Paste hotel links, choose how many recent reviews per hotel (from 22 October 2026), export to Excel, CSV or JSON. No login.

Price: $3 per 1,000 reviews from 22 October 2026 (see the Pricing tab for today's price). The first 10 results of every run are free.

The form is prefilled: press Start to see real rows in seconds.

In short: what you give, what you get, what it costs

You give	Booking.com hotel or stay links
We do	Read each property's most recent guest reviews
You get	One row per review: score, title, liked and disliked text, traveler type and country, room, nights, stay and review dates, language and the property's reply
It costs	$3 per 1,000 reviews, $1 from 21 November 2026, no start fee. Optional scheduled monitoring: +$0.18 per check, $0.008 from 21 November (one-off runs never pay it). Apify also bills the supplier Actor voyager/booking-reviews-scraper that this robot runs for you, at its own price (about $2 per 1,000 results). The first 10 results of every run are free of this robot's fee.
It does not	Sign in to Booking.com or give room prices

A real result row is shown further down this page.

Free tier — 10 results free on every run

The free results waive this Actor's own fee; the source Actor (voyager/booking-reviews-scraper) still bills its own price for every row it returns.

The first 10 results of every run are free, on every run you ever make — not a one-off trial. Run it on your own subjects and see the real output before you are billed for a single result.

One guard: the free allowance never covers more than half of a run, so a run returning 6 results gets 3 free. That keeps the offer sustainable.

What it does

Run it once and get the full, current data as clean rows you can export to JSON, CSV or Excel, or pull through the API. Need only fresh data? Turn on monitorEnabled and schedule it: every later run returns only what is new or changed since the previous one, so you never re-download or re-pay for the same rows.

Compared with solidcode/booking-reviews-scraper

Read on the Store on 2026-10-23 (Booking.com Reviews Scraper). Where it does better, this section says so.

• Data source: this Actor runs voyager/booking-reviews-scraper for you, then cleans and checks every row.
• Only here (fields its Store page does not list): change_type (new or changed since your last scheduled run); actionable (needs a reply or action); severity (how serious a complaint is); why_it_matters (one-line reading of the row).
• This Actor's fee is free on the first results of every run, and a hard cost cap (maxTotalChargeUsd) limits it.
• Price: about $5 per 1,000 in total here ($3 for this Actor + $2 for voyager/booking-reviews-scraper), $1.3 at solidcode/booking-reviews-scraper.

Why this scraper

1. Try before you pay. The first 10 results of every run are free, on every run.
2. Pay only for data delivered. Failed sources and failed inputs are never billed.
3. Hard cost cap. Set maxTotalChargeUsd and a run can never cost more than you allow.
4. Only-new mode. With monitorEnabled on a schedule, you get just the new or changed rows, plus a spike signal when volume suddenly jumps.
5. Clean, normalized rows with the same field names every run, plus a RUN_SUMMARY.json — ready for spreadsheets, databases, n8n/Make/Zapier and AI agents (MCP).

Example input

{
  "hotelUrls": [
    "https://www.booking.com/hotel/us/new-york-hilton-midtown.html"
  ],
  "maxTotalChargeUsd": 1.0
}

This returns the full current data right away. To receive only what is new on a schedule, add "monitorEnabled": true: the first monitored run stores a free baseline, later runs return only new or changed rows. Pin a monitorId to keep separate targets from sharing state.

Output

Each row is one hotel review. A real row from a run on Apify (long texts are cut here and people's names hidden; your dataset has them in full):

A real row from this Actor's latest run on Apify (2026-10-24; long texts are cut and people's names hidden here, your dataset has them in full):

{
  "review_id": "2ef684194b63fd68",
  "subject_id": "https://www.booking.com/hotel/us/new-york-hilton-midtown.html",
  "author": "(hidden here)",
  "rating": 9,
  "published_at": "2024-02-24T14:07:36.000Z",
  "likedText": "Good location close to Times Square and the park. Easy to get to and visit tourist attractions. The rooms were very clean and spacious. T...",
  "dislikedText": "No in room coffee maker. The prices for laundry and food and drinks is a little excessive but other stores are around.",
  "reviewTitle": "Another great stay at the Midtown Hilton.",
  "travelerType": "Family",
  "userLocation": "(hidden here)",
  "userName": "(hidden here)",
  "userAvatar": "(hidden here)",
  "propertyResponse": "Dear Andrew,\nThank you for your positive words about your recent stay at New York Hilton Midtown, highlighting our convenient location, c...",
  "checkInDate": "2024-02-16",
  "checkOutDate": "2024-02-20",
  "reviewDate": "2024-02-24T14:07:36.000Z",
  "images": [
    "https://q-xx.bstatic.com/xdata/images/xphoto/max1280x900/314069960.jpg?k=52d2e45ce266fc8a0647974a2145c2fbf0b84d67e9c0e877775d8a535557d18c&o="
  ],
  "id": "2ef684194b63fd68",
  "roomInfo": "City Room Two Double Beds",
  "numberOfNights": 4,
  "reviewLanguage": "xu",
  "stayRoomId": 5589024,
  "helpfulVotes": 0,
  "totalCategoryReviews": 1542,
  "hotelId": 55890,
  "reviewsScoreFilter": "ALL",
  "reviewPage": 1,
  "startUrl": "https://www.booking.com/hotel/us/new-york-hilton-midtown.html",
  "hotelRating": 7.2,
  "hotelReviews": 1542,
  "record_id": "2ef684194b63fd68",
  "change_type": "new",
  "actionable": false,
  "topic": "other",
  "severity": "minor",
  "why_it_matters": "New positive review — no action needed."
}

Field	What it holds
rating	guest score out of 10
reviewTitle	review headline
likedText	what the guest liked
dislikedText	what the guest disliked
travelerType	couple, family, solo, business...
userLocation	guest's country
roomInfo	room booked
numberOfNights	length of stay
checkInDate	check-in date
reviewDate	review date
reviewLanguage	review language
propertyResponse	the hotel's reply
hotelRating	hotel's overall score
topic	what the review is about
why_it_matters	one-line reading for a hotel manager

Each row also keeps the other fields the source returns, so you get everything above and more. In the Output tab, the Overview table shows these columns, readable without any code; export them as CSV, Excel, JSON or HTML.

How you're charged

• Source Actor charge: this Actor runs voyager/booking-reviews-scraper inside your run, and Apify bills that run to your account at voyager/booking-reviews-scraper's own price (about $2 per 1,000 results, read on 2026-10-23), on top of this Actor's price. Each call to it is capped at $0.50.
• Reviews per place — from 22 October 2026 you choose how many recent reviews to read per link with maxReviewsPerPlace, up to 1,000 (until then, and with monitoring on, 50 are read).
• Review — from 22 October 2026: $0.003 per review ($3 per 1,000), the same on every plan, billed for each review delivered to your dataset. With monitoring on, only reviews that are new since the last check are delivered and billed.
• Monitoring check ($0.18) — only when you turn on scheduled monitoring (monitorEnabled), once per target per run, and only when the source responded. One-off runs never pay it: you pay only per result.
• One-off runs pay only per result. The monitoring check applies only to scheduled monitoring; every upstream call is capped, so a run can never cost more than you allow.

How to use it in 3 steps

1. Click Try for free and fill in Booking.com property URLs (hotelUrls).
2. Optional: adjust the other fields; every one has a description and a sensible default.
3. Click Start and download the results as JSON, CSV or Excel, or read them from the API.

Use cases

• Hotel reputation: follow what guests say about your property and your competitors.
• Spot fake-review spikes with the velocity signal before they hurt your score.
• Travel research: compare scores and recurring complaints across hotels in a city.

Use it from code (API)

Every Apify Actor is an API. Start a run and read the results with one call.

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("om_kh/booking-com-reviews-scraper").call(run_input={"hotelUrls": ["https://www.booking.com/hotel/us/new-york-hilton-midtown.html"]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('om_kh/booking-com-reviews-scraper').call({
    "hotelUrls": [
        "https://www.booking.com/hotel/us/new-york-hilton-midtown.html"
    ]
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

One HTTP call (cURL) — runs the Actor and returns the dataset in the same response:

curl -X POST "https://api.apify.com/v2/acts/om_kh~booking-com-reviews-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"hotelUrls": ["https://www.booking.com/hotel/us/new-york-hilton-midtown.html"]}'

Integrations: n8n, Make, Zapier, Google Sheets

• n8n — the official Apify node, operation Run Actor and get dataset, Actor om_kh/booking-com-reviews-scraper.
• Make — Apify › Run an Actor, then Apify › Get Dataset Items.
• Zapier — Apify › Run Actor; map the dataset items into your next step.
• Google Sheets, webhooks, Slack — add an integration from the Integrations tab of this Actor.
• Schedules — run it every hour or day from Schedules in Apify Console.

Use it from an AI agent (MCP and x402)

Connect Claude Desktop, Cursor, VS Code or any MCP client to Apify's MCP server at https://mcp.apify.com and add this Actor, om_kh/booking-com-reviews-scraper, as a tool — the agent passes the same JSON as the run input and gets the dataset back.

AI agents that pay with x402 can run it too, without an Apify account: the Actor charges only per result delivered, so an agent pays exactly for what it gets.

FAQ

Is it legal to scrape Booking.com? This Actor collects only publicly available Booking.com data and never logs in. You are responsible for how you use it; check Booking.com's terms and your local law (GDPR, CCPA) if you store personal data, and ask a lawyer if unsure.

Do I need an account, cookies or an API key? No. You only need an Apify account to run it.

What data do I get? Guest reviews with score, positive and negative text and date. Download it as JSON, CSV, Excel, HTML or XML, or read it from the API.

Am I charged when something fails? No. An input that fails is listed with its reason in the run summary and is never charged.

Can I run it on a schedule? Yes. Create a schedule in Apify Console (hourly, daily, weekly) and connect webhooks, Google Sheets, Slack, n8n, Make or Zapier.

Can I use it from Python, JavaScript or an AI agent? Yes: see the code samples above, or connect AI agents through MCP with the booking_new_reviews tool.

All input fields

The main fields are described above; these are the others the form accepts:

• currentReviews (Bring your own reviews (optional)) — Skip the chained fetch and pass review data directly, e.g. from your own export.
• previousReviews (Previous reviews (non-monitor mode)) — Reviews from the prior run; used to identify new feedback when not using persistent monitor mode.

Your feedback

Did this Actor save you time? A short review on the Reviews tab helps other people find it, and every review is read. Something missing or broken? Open an issue on the Issues tab: it is answered and fixed fast.

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