Airbnb Reviews Scraper

Extract Airbnb guest reviews at scale. Scrape full review text, ratings, category scores (cleanliness, accuracy, communication, location, check-in, value), reviewer details, stay duration, host info, and complete listing metadata for any property.

Features

• Scrape reviews by listing URL or location search
• Extract full review text with date and rating
• Reviewer name, location, and stay duration
• 6 Airbnb category ratings: Cleanliness, Accuracy, Communication, Location, Check-in, Value
• Listing metadata: title, type, host, superhost status, price, amenities
• Sort by most recent or most relevant
• Multi-language support (auto-translation)
• Multiple extraction strategies: NEXT_DATA, deferred-state JSON, API endpoints, DOM parsing
• Automatic pagination — scrape hundreds or thousands of reviews
• Anti-detection with rotating user agents and realistic headers
• Deduplication — no duplicate reviews in output
• Clean, structured JSON output

Input

Field	Type	Default	Description
listingUrls	array	[]	Airbnb listing URLs to scrape reviews from
searchQuery	string	""	Search by location (e.g., "Paris, France")
maxReviews	number	500	Max reviews per listing (0 = unlimited)
sortBy	string	"recent"	Sort: "recent" or "relevant"
language	string	"en"	Review language (ISO 639-1 code)
maxListingsFromSearch	number	10	Max listings to discover from search
includeListingDetails	boolean	true	Include listing metadata with each review
includeCategoryRatings	boolean	true	Include 6 category rating scores
proxyConfiguration	object	Apify Residential	Proxy settings (residential recommended)

Output — Individual Review

{
  "listingTitle": "Stunning Eiffel Tower View Apartment",
  "listingId": "12345678",
  "listingUrl": "https://www.airbnb.com/rooms/12345678",
  "reviewId": "r-987654321",
  "reviewText": "Amazing apartment with breathtaking views of the Eiffel Tower. The host was incredibly responsive and the location is perfect for exploring Paris. Everything was spotlessly clean and exactly as described in the listing. Would absolutely come back!",
  "rating": 5,
  "reviewDate": "2026-01-15",
  "reviewDateRaw": "January 2026",
  "reviewerName": "Sarah",
  "reviewerLocation": "New York, United States",
  "reviewerProfileUrl": "https://www.airbnb.com/users/show/11223344",
  "reviewerAvatar": "https://a0.muscache.com/im/pictures/user/...",
  "stayDuration": "5 nights",
  "stayType": "Leisure",
  "response": "Thank you Sarah! So glad you enjoyed the view. You're welcome back anytime!",
  "responseDate": "2026-01-16",
  "language": "en",
  "translatedFrom": null,
  "overallRating": 4.95,
  "totalReviews": 347,
  "categoryRatings": {
    "cleanliness": 4.9,
    "accuracy": 5.0,
    "communication": 5.0,
    "location": 5.0,
    "checkIn": 4.9,
    "value": 4.8
  },
  "listingDetails": {
    "propertyType": "Entire apartment",
    "location": "Paris, Ile-de-France, France",
    "hostName": "Jean-Pierre",
    "superhost": true,
    "pricePerNight": 185,
    "currency": "USD",
    "bedrooms": 2,
    "bathrooms": 1,
    "maxGuests": 4,
    "amenities": ["Wifi", "Kitchen", "Washer", "Air conditioning", "Elevator"]
  },
  "scrapedAt": "2026-03-02T12:00:00.000Z"
}

Use Cases

• Property Management: Monitor guest satisfaction, identify recurring complaints, track improvement over time
• Investment Analysis: Evaluate properties before purchasing — review sentiment reveals true guest experience
• Competitor Research: Analyze competitor listings in your market — understand their strengths and weaknesses
• Market Research: Discover what guests value most in specific locations and property types
• Pricing Strategy: Correlate review scores with pricing to find optimal price points
• Quality Benchmarking: Compare category scores across your portfolio vs. market averages
• Guest Experience Design: Extract actionable insights from guest feedback to improve amenities and services
• Due Diligence: Validate Airbnb income claims with actual review volume and sentiment data
• Content Analysis: Mine real guest language for listing copywriting and marketing
• Trend Detection: Spot emerging issues (noise, cleanliness, safety) before they impact ratings

Pricing

Pay per review scraped — you only pay for successfully extracted reviews. See the Pricing tab for current rates.

Tips

• Start small: Test with 1-2 listings and 50 reviews before running large batches
• Use proxies: Residential proxies significantly improve reliability
• Sort by recent: Best for monitoring and trend analysis
• Sort by relevant: Best for overall sentiment understanding
• Category ratings: Available at listing level — great for benchmarking across properties
• Language: Set to your preferred language — Airbnb auto-translates reviews

Legal

This actor is intended for legitimate research purposes including property management, market analysis, and academic research. Always comply with Airbnb's Terms of Service and applicable data protection regulations. Do not use scraped data for harassment, discrimination, or any unlawful purpose.

Integration — Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("sovereigntaylor/airbnb-reviews-scraper").call(run_input={
    "searchTerm": "airbnb reviews",
    "maxResults": 50
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item.get('title', item.get('name', 'N/A'))}")

Integration — JavaScript

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('sovereigntaylor/airbnb-reviews-scraper').call({
    searchTerm: 'airbnb reviews',
    maxResults: 50
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(item => console.log(item.title || item.name || 'N/A'));