Booking.com Hotel Price Tracker

An Apify actor that scrapes hotel prices from Booking.com across a configurable date range. Ideal for price monitoring, travel planning, and competitive analysis.

What it does

For each check-in date in your range, the actor:

1. Acquires fresh cookies via a headless Playwright browser to bypass basic bot detection.
2. Fetches search results using fast HTTP requests (not full browser rendering) for speed.
3. Extracts structured data from each hotel card: name, prices, discounts, deals, review scores, and links.
4. Pushes results to an Apify dataset in real time.

Input — Two Ways to Start

Option 1: Paste a URL (easiest)

Search on booking.com, copy the URL from your browser, and paste it into the bookingUrl field. The actor extracts destination, dest_id, and dest_type automatically.

Option 2: Enter Manually

Fill in destination (e.g., "Cardiff Center"), districtId (e.g., "1233"), and destType (e.g., "district"). You can find these in any Booking.com search URL.

Field	Type	Default	Description
bookingUrl	string	—	Booking.com search URL (Option 1)
destination	string	Cardiff Center	Search destination (Option 2)
districtId	string	1233	Booking.com dest_id (Option 2)
destType	string	district	Destination type (Option 2)
startDate	string	tomorrow	First check-in date (YYYY-MM-DD)
numDays	integer	7	Number of consecutive dates to scrape
currency	string	GBP	Price display currency
adults	integer	2	Number of adult guests
rooms	integer	1	Number of rooms
children	integer	0	Number of children
maxRetries	integer	5	Retry attempts per failed request
maxPages	integer	1	Result pages per date (25 hotels/page)
proxyConfig	object	Apify residential	Proxy configuration

Example Input — Using a URL

{
    "bookingUrl": "https://www.booking.com/searchresults.html?ss=London+City+Centre&dest_id=-2601889&dest_type=city",
    "numDays": 14,
    "currency": "GBP",
    "maxPages": 2,
    "proxyConfig": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

Example Input — Using Manual Fields

{
    "destination": "London City Centre",
    "districtId": "-2601889",
    "destType": "city",
    "numDays": 14,
    "currency": "GBP",
    "maxPages": 2,
    "proxyConfig": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

Output

Each record in the dataset contains:

{
    "dateCaptured": "2026-03-26T12:00:00Z",
    "hotelName": "Park Plaza Westminster Bridge",
    "checkIn": "2026-04-01",
    "checkOut": "2026-04-02",
    "originalPrice": "£245",
    "currentPrice": "£189",
    "originalPriceNumeric": 245.0,
    "currentPriceNumeric": 189.0,
    "discountPercent": 23,
    "dealType": "Early 2026 Deal",
    "reviewScore": "8.4",
    "distance": "0.3 km from centre",
    "currency": "GBP",
    "destination": "London City Centre",
    "hotelUrl": "https://www.booking.com/hotel/gb/...",
    "searchUrl": "https://www.booking.com/searchresults.html?..."
}

Tips

• Use residential proxies. Booking.com is aggressive with bot detection. Datacenter IPs will get blocked quickly.
• Keep numDays reasonable. More days = longer runtime = higher costs. Start with 7 to test.
• Schedule runs for daily price tracking — Apify's scheduler works well for this.
• Export to Google Sheets or webhook for automatic dashboards.

Cost Estimate

With residential proxies: ~$0.10–$0.30 per run for 7 days × 1 page each, depending on retry rate.