Arcadium Data Scrapers
Home / Actors / Booking.com Reviews Scraper

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

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

FieldWhat it holds
reviewIdBooking's own ID, prefixed Booking___. Stable between runs, so weekly exports can be deduplicated.
dateReview date, ISO format.
titleThe review headline.
pros, consWhat the guest liked and disliked. text holds both joined.
ratingOverallScore on a 0 to 5 scale (Booking's 1 to 10 score divided by 2). The original is in extras.score10.
languageReview language, empty when Booking could not tell.
helpfulVotesHow many readers marked the review as helpful.
vendorResponseThe hotel's reply, with the greeting name removed.
extrasTraveler type, room type, check-in and check-out dates, nights, photo count.
countryReviewer country as a two-letter code. On by default; switch off with includeReviewerCountry: false.
entityId, productName, productUrl, productWhich 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 1,000FreeBronzeSilverGoldPlatinumDiamond
Review (main)$1.80$1.71$1.35$0.81$0.81$0.81

Use cases

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

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.

Related actors

Agoda and Trip.com Reviews Scraper

Agoda and Trip.com hotel reviews for hotel links or IDs: score, original text, English translation, traveler type, hotel reply; $5.40 per 1,000 Agoda reviews.

$5.40 per 1,000 Agoda reviews on the Free plan, down to $2.70 on higher plans

Capterra Reviews Scraper

Capterra reviews for product URLs: rating, pros, cons, text, reviewer role, industry and company size, incentivized flag; $1.79 per 1,000 reviews.

$1.79 per 1,000 reviews on the Free plan, down to $1.16 on higher plans

Google Hotel Reviews Scraper

Google hotel reviews for hotel links or names: rating, text, translation, date, trip type, room/service/location scores, owner reply; $0.54 per 1,000 reviews.

$0.54 per 1,000 reviews on the Free plan, down to $0.27 on higher plans

Google Hotels Scraper

Google Hotels prices for a city or hotel and your dates, $4.49 per 1,000 hotels; zerobreak/google-hotels-scraper input works as is.

$4.49 per 1,000 hotel rows on the Free plan, down to $2.69 on higher plans

Hotel Reviews Scraper

Hotel reviews from Tripadvisor, Booking.com, Google Hotels, Agoda and Trip.com in one dataset, ratings on one 1-5 scale; $4.50 per 1,000 reviews.

$4.50 per 1,000 reviews on the Free plan, down to $0.80 on higher plans

Review Monitor

New 1-2★ reviews, rating drift, owner-reply rate and review velocity per watched business, app or SaaS product since your last run; $12 per 1,000 checks.

$12.00 per 1,000 entities checked