Booking.com Scraper — Hotel Listings as JSON/CSV

Scrape Booking.com search-results pages for hotels in any destination. Returns 16 fields per listing — name, URL, price, currency, review score, stars, review count, location, distance, image, plus the search context (dates, adults, rooms, destination, scraped timestamp).

No API key, no Booking.com login, no Selenium/Playwright. Uses Cheerio + Crawlee on the public search-results HTML.

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What this actor actually does (verified against src/main.js)

For every destination in your input, the actor:

1. Builds a Booking.com search URL with your check-in/out dates, adults, rooms, currency, and sort order.
2. Walks the paginated results (offsets 0, 25, 50…) until either maxResults per destination is reached or no more cards appear.
3. Parses each property card with Cheerio selectors (3-fallback chain: [data-testid="property-card"] → legacy .sr_property_block → [data-testid="property-card-container"]).
4. Applies your minPrice / maxPrice / minRating filters in-memory before pushing.
5. Writes one record per hotel to the dataset.

That's it. ~30–90 sec per destination depending on maxResults.

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Input

{
  "destinations": ["Paris", "Tokyo", "London"],
  "checkIn": "2026-06-15",
  "checkOut": "2026-06-18",
  "adults": 2,
  "rooms": 1,
  "maxResults": 50,
  "currency": "USD",
  "sortBy": "review_score",
  "minPrice": 80,
  "maxPrice": 400,
  "minRating": 8.0
}

Field	Type	Default	Notes
destinations	string[]	required	One Booking.com search per destination.
checkIn	YYYY-MM-DD	tomorrow	If empty, the actor uses tomorrow's date.
checkOut	YYYY-MM-DD	day after tomorrow	If empty, day after checkIn.
adults	int 1–10	2
rooms	int 1–10	1
maxResults	int 1–500	50	Cap per destination, not total.
currency	enum	USD	One of: USD, EUR, GBP, JPY, AUD, CAD, CHF, CNY, RUB, INR, BRL.
sortBy	enum	popularity	One of: popularity, price_asc, rating, review_score, distance.
minPrice	int / null	null	Per-night currency-units. Filter applied client-side.
maxPrice	int / null	null	Same as above.
minRating	number 0–10 / null	null	Filter on Booking review score.

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Output (one record per hotel)

{
  "name": "Hotel Le Bristol Paris",
  "url": "https://www.booking.com/hotel/fr/lebristol.html",
  "price": 1240,
  "currency": "USD",
  "rating": 9.4,
  "reviewCount": 1853,
  "stars": 5,
  "location": "8th arr., Paris",
  "distance": "1.2 km from center",
  "image": "https://cf.bstatic.com/.../bristol.jpg",
  "destination": "Paris",
  "checkIn": "2026-06-15",
  "checkOut": "2026-06-18",
  "adults": 2,
  "rooms": 1,
  "scrapedAt": "2026-04-29T13:30:00.000Z"
}

16 fields per hotel. All fields may be null when the property card doesn't expose them — Booking ships A/B card layouts and missing data is normal.

Field notes (be honest before you buy)

• price is whatever Booking displays on the card — it can be per-night or total-stay depending on Booking's rendering for your locale and date range. Cross-check against the URL before treating as canonical.
• stars is counted by DOM-element heuristic (span/svg count inside the rating element). Reliable for 1–5 hotels but can return null or off-by-one when Booking changes the markup.
• distance is a free-text string ("1.2 km from center", "500 m from Eiffel Tower"). No parsing into numeric km.
• reviewCount parsing strips non-digits — works in most locales but can fail on RU/JP non-Latin formats.

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What this actor does NOT do (be honest)

• ❌ No detail-page enrichment. You get the search-card data only — no room types, no amenity list, no policies, no full review text.
• ❌ No JS rendering. Pure Cheerio. If Booking moves a price into a JS-rendered modal (they sometimes do), that field becomes null until selectors are updated.
• ❌ No proxy rotation built in. Booking doesn't aggressively block low-volume scraping, but at scale you should add Apify's residential proxy via the platform proxy config (and budget accordingly).
• ❌ No CAPTCHA solving. If Booking serves a challenge, the run will return whatever it parsed before the block.
• ❌ No deduplication across destinations. A hotel that appears under "Paris" and under a Paris-area neighborhood lookup will appear twice.
• ❌ No price history. One snapshot per run. If you need price-tracking, schedule the run on Apify Cron and append to your own dataset/DB.
• ❌ No alternative sites. Booking.com only — not Hotels.com, Expedia, Agoda, Trivago.

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Common use cases

• Travel-aggregator side projects — daily snapshots of top 50 hotels in 10 cities for a price-tracker dashboard.
• Market research — competitor pricing in a destination for a hotel-chain or OTA team.
• Affiliate content — populate "Top 10 hotels in Tokyo under $200" listicles with fresh data.
• Travel-agent automations — feed search results into Slack/email when a target hotel drops below a price threshold.

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When this actor stops being enough

If you need any of the following, that's a custom build (we deliver):

• Detail-page enrichment (amenities, room types, policies, review text)
• Multi-site comparison (Booking + Hotels.com + Expedia + Agoda in one record)
• Daily price-history with diff alerts
• Geo-bounded search (lat/lng + radius)
• Booking.com vacation-rentals or transport-search

Proof of delivery + urgency: This actor has 22 lifetime production runs as of May 2026 — part of an active 31-published portfolio (78 total). Trustpilot scraper alone: 951 lifetime runs. Author shipped a paid 3-article series in March 2026 ($150, proxy industry). Pilot pricing locked through May 2026 (table below).

Sample request? Reply sample to spinov001@gmail.com and you'll receive 2 published case-study articles within 24 hours, no obligation. Fastest way to evaluate writing style + technical depth before commissioning a custom build.

Tier	What you get	Price
Pilot	1 actor extension (e.g. detail-page enrichment), basic config, 7-day support	$97
Standard	Custom multi-site or scheduled snapshot pipeline + Slack/email alerts, 30-day support	$297
Premium	Full price-tracking dashboard + 90-day support + 1 modification round	$797

Track record: 31 published actors on Apify (78 total in portfolio), including:

• trustpilot-review-scraper — 951 runs in 30d, used by data teams for review monitoring
• reddit-discussion-scraper — Reddit JSON-API scraper at scale
• email-extractor-pro — bulk website email harvester (no Hunter cap)

Contact / sample work:

• Email: spinov001@gmail.com
• Blog & case studies: https://blog.spinov.online
• All actors: https://apify.com/knotless_cadence
• Telegram (scraping/AI tips): https://t.me/scraping_ai

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License

MIT — fork it, modify it, ship it.