Booking.com Reviews Scraper
Give it Booking.com hotel URLs and it returns one JSON row per guest review: score (1-10 and on a 0-5 scale), what the guest liked and disliked as separate fields, title, date, language, traveler type, room type, nights, reviewer country and the hotel's reply. $1.80 per 1,000 reviews on the free plan, less on paid plans; you pay only for rows you get.
$1.80 per 1,000 reviews on the Free plan, down to $0.81 on higher plans
Why this actor
- Liked and disliked text arrive split, so aspect-level analysis needs no guessing.
- Filters by traveler type, score band and season, with one charge per review even when it matches several passes.
- Only new reviews and a free coverage row per hotel (stated vs delivered), plus a free
errorrow with acodefor an input that failed.
Drop-in input
Easy switch. Input names of the other popular Booking reviews actor (sortReviewsBy, cutoffDate, reviewScores, maxReviewsPerHotel) are accepted.
As stated in the actor’s README. The full list of accepted input names is on the Store page.
What you get
| Field | What it holds |
|---|---|
reviewId | Booking's own ID, prefixed Booking___. Stable between runs, so weekly exports can be deduplicated. |
date | Review date, ISO format. |
title | The review headline. |
pros, cons | What the guest liked and disliked. text holds both joined. |
ratingOverall | Score on a 0 to 5 scale (Booking's 1 to 10 score divided by 2). The original is in extras.score10. |
language | Review language, empty when Booking could not tell. |
helpfulVotes | How many readers marked the review as helpful. |
vendorResponse | The hotel's reply, with the greeting name removed. |
extras | Traveler type, room type, check-in and check-out dates, nights, photo count. |
country | Reviewer country as a two-letter code. On by default; switch off with includeReviewerCountry: false. |
entityId, productName, productUrl, product | Which hotel the review belongs to. |
Sample row (from the README example; long text shortened, lists cut to two items):
{
"platform": "booking",
"reviewId": "Booking___c6397d1e2a854aa3",
"date": "2026-09-30",
"title": "Perfect stay",
"pros": "Staff went out of their way for us.",
"cons": null,
"ratingOverall": 5,
"language": "en",
"vendorResponse": "Dear [name],\nThank you for staying with us...",
"extras": {
"score10": 10,
"travelerType": "COUPLES",
"roomType": "Superior King",
"nights": 3
},
"entityId": "280149",
"productName": "The Savoy"
}
Price
Live Apify price on 2026-10-31, per 1,000 rows, by Apify plan. You pay only for rows delivered; error and summary rows marked free in the README cost nothing. Plus $0.001 per GB of memory when a run starts.
| Per 1,000 | Free | Bronze | Silver | Gold | Platinum | Diamond |
|---|---|---|---|---|---|---|
| Review (main) | $1.80 | $1.71 | $1.35 | $0.81 | $0.81 | $0.81 |
Use cases
- Reputation monitoring: pull the newest reviews every week with
onlyNewReviewsand watch what changes. - Competitor benchmarking: compare category scores (location, staff, value) across hotels in one city with the summary row.
- Complaint mining: filter to poor and very poor scores and read the
conscolumn. - Model training: aspect-level sentiment from the native liked and disliked split.
Run it from code or an AI agent
Actor ID arcadium/booking-reviews. Set APIFY_TOKEN to your Apify API token. The input below is the actor’s prefilled example; see the guide for every field.
curl
curl -X POST "https://api.apify.com/v2/acts/arcadium~booking-reviews/run-sync-get-dataset-items" \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"startUrls":[{"url":"https://www.booking.com/hotel/gb/the-savoy.html"}],"maxReviewsPerHotel":20,"sort":"NEWEST_FIRST"}'JavaScript
// npm install apify-client
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('arcadium/booking-reviews').call({
"startUrls": [
{
"url": "https://www.booking.com/hotel/gb/the-savoy.html"
}
],
"maxReviewsPerHotel": 20,
"sort": "NEWEST_FIRST"
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);Python
# pip install apify-client
import os
from apify_client import ApifyClient
client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/booking-reviews").call(run_input={
"startUrls": [{
"url": "https://www.booking.com/hotel/gb/the-savoy.html",
}],
"maxReviewsPerHotel": 20,
"sort": "NEWEST_FIRST",
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)MCP
{
"mcpServers": {
"apify": {
"url": "https://mcp.apify.com/?tools=arcadium/booking-reviews",
"headers": {
"Authorization": "Bearer <APIFY_TOKEN>"
}
}
}
}LangChain
# pip install langchain-apify (reads APIFY_API_TOKEN from the environment)
from langchain_apify import ApifyActorsTool
tool = ApifyActorsTool("arcadium/booking-reviews")
rows = tool.invoke({"run_input": {
"startUrls": [{
"url": "https://www.booking.com/hotel/gb/the-savoy.html",
}],
"maxReviewsPerHotel": 20,
"sort": "NEWEST_FIRST",
}})
# or give `tool` to an agent: create_react_agent(llm, [tool])LlamaIndex
# pip install llama-index-readers-apify
import os
from llama_index.core import Document, VectorStoreIndex
from llama_index.readers.apify import ApifyActor
reader = ApifyActor(os.environ["APIFY_TOKEN"])
documents = reader.load_data(
actor_id="arcadium/booking-reviews",
run_input={
"startUrls": [{
"url": "https://www.booking.com/hotel/gb/the-savoy.html",
}],
"maxReviewsPerHotel": 20,
"sort": "NEWEST_FIRST",
},
dataset_mapping_function=lambda item: Document(text=str(item.get("text") or ""), metadata={"url": item.get("url")}),
)
index = VectorStoreIndex.from_documents(documents)CrewAI
# pip install crewai crewai-tools langchain-apify (reads APIFY_API_TOKEN from the environment)
from crewai import Agent
from crewai_tools import ApifyActorsTool
tool = ApifyActorsTool(actor_name="arcadium/booking-reviews")
researcher = Agent(
role="Research analyst",
goal="Answer with data collected by the tool",
backstory="Uses public web data.",
tools=[tool],
)n8n
{
"nodes": [
{
"name": "Run arcadium/booking-reviews",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
0,
0
],
"parameters": {
"method": "POST",
"url": "https://api.apify.com/v2/acts/arcadium~booking-reviews/run-sync-get-dataset-items",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "{\"startUrls\":[{\"url\":\"https://www.booking.com/hotel/gb/the-savoy.html\"}],\"maxReviewsPerHotel\":20,\"sort\":\"NEWEST_FIRST\"}",
"options": {
"timeout": 300000
}
}
}
],
"connections": {}
}Google Sheets
// Extensions > Apps Script. Store your token once: Project Settings > Script properties > APIFY_TOKEN.
function importLastRun() {
const token = PropertiesService.getScriptProperties().getProperty('APIFY_TOKEN');
const url = 'https://api.apify.com/v2/acts/arcadium~booking-reviews/runs/last/dataset/items?status=SUCCEEDED&clean=true&format=json';
const res = UrlFetchApp.fetch(url, { headers: { Authorization: 'Bearer ' + token } });
const rows = JSON.parse(res.getContentText());
if (!rows.length) return;
const keys = Object.keys(rows[0]);
const values = rows.map((r) => keys.map((k) => (typeof r[k] === 'object' ? JSON.stringify(r[k]) : r[k])));
const sheet = SpreadsheetApp.getActiveSheet();
sheet.clearContents();
sheet.getRange(1, 1, 1, keys.length).setValues([keys]);
sheet.getRange(2, 1, values.length, keys.length).setValues(values);
}Limitations
- Public reviews only. Nothing behind a login.
- Booking only shows roughly the last three years of reviews, so "all reviews" means that window.
- Review language is empty for a small share of reviews where Booking does not know it.
- Searching by hotel name is not supported yet. Paste the hotel page URL or the hotel ID.
dateFromworks with every sort order, but only newest first can stop early; other orders read all matching pages and filter.- Hotel IDs without a URL give rows without a hotel name; Booking only reports the name through the hotel page.
- Booking publishes category scores (cleanliness, location and so on) per hotel, not per review, so they are in the optional summary row only.
- City averages in the summary row are only available when the hotel is given as a URL.
FAQ
How fresh is the data? It is read when you run the actor, so it matches what the site shows at that moment.
Can I get only new reviews since my last run? Yes. Turn on onlyNewReviews and keep the same stateKey. The state is stored per hotel. Use another stateKey to start a separate series.
A hotel returned no reviews. Why? Check that the URL opens a hotel page in your browser. Unknown hotels and hotels without reviews return an error row, which is not charged.
Something looks wrong in the output. Who do I tell? Open an issue on the actor page with the run link. We read them all.
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