Google Hotels Fast Search

Hotel price snapshots for developers and data teams that need structured data for monitoring, analysis, or internal products.

Run city queries or specific hotel names, keep the requested market and currency in the output, and export each run to an Apify Dataset. Schedule the same input to build a history of observed prices over time.

Use this Actor to:

• capture a price snapshot for one or more cities;
• monitor a hotel watchlist on a daily or weekly schedule;
• build a dataset for pricing analysis or market research;
• send completed runs to a database, spreadsheet, or webhook workflow.

Pricing is Pay Per Event. The Actor charges hotel-result at $0.025 for each billable hotel row written to the dataset. Apify also charges the configured apify-actor-start event based on run memory. A query with no billable hotel result does not incur a hotel-result charge.

Results reflect what Google Hotels displayed for the selected dates, guests, country, and currency when the run executed. Provider coverage and booking links vary by hotel and query.

---

What the dataset contains

Each hotel is written as one structured row. Base fields include the query, hotel identity, ratings, observed summary price, requested currency, dates, and Google Hotels URL.

When detail scraping is enabled, the Actor can also collect:

• provider price rows with provider, price, currency, and bookingUrl when Google exposes a booking link;
• overview fields such as address, phone, highlights, and nearby places;
• reviews and third-party rating summaries;
• photo URLs;
• check-in details and amenities.

The Actor checks available currency, date, and market signals before retaining detailed provider prices. Rows with a detected context mismatch are dropped rather than mixed into the final prices array. This behavior was cloud-tested with Singapore inputs using country="sg", currency="SGD", and an explicit Residential proxy. It is evidence for that workflow, not a guarantee that every hotel will return the same number of providers.

---

Monitoring workflows

City price snapshots

Run queries such as hotels in Singapore Orchard Road or hotels in Tokyo Shinjuku. Store each completed dataset with its input dates and scrapedAt timestamp for later comparison.

Repeated hotel monitoring

Schedule a specific hotel query with the same country, currency, dates, and guest count. Compare datasets across runs in your own workflow to identify observed price changes. The Actor returns snapshots; it does not calculate historical diffs by itself.

Dataset building

Collect normalized hotel rows for a selected list of markets. Export JSON or CSV, or retrieve the dataset through the Apify API for loading into a warehouse, dashboard, or notebook.

Booking-link research

Use detail mode when your downstream process needs provider-level price rows. bookingUrl is included when it is present in the Google Hotels result. Availability and provider count vary by hotel.

Localized market checks

Set country and currency together, for example sg and SGD. The Actor keeps context-valid price rows in the requested currency and records detail status fields when enrichment is partial.

---

Key features

Feature	Details
Structured price snapshots	One dataset row per hotel with query, dates, observed prices, currency, identity, and scrape timestamp
Provider-level detail	Price and booking-link rows when exposed by Google Hotels; provider coverage varies by hotel
Currency and market validation	Detailed prices are checked against available currency, date, and market signals
Monitoring-ready output	Stable dataset fields for scheduled runs, API retrieval, and downstream comparisons
Optional detail sections	Overview and Prices are always in the output shape; Reviews, Photos, and About can be requested
Supported markets	22 country options and 22 currency options in the existing input contract
Filtering and sorting	Filter by rating or maximum observed price and sort the resulting dataset
Bounded fallback status	Detail runs report success or partial so pipelines can distinguish complete enrichment from a base-row fallback
Residential proxy support	Apify Residential traffic is aligned with the requested country when Apify Proxy is enabled
Existing scale limits	Up to 5 queries per run; search-only and detail modes retain their documented result limits

---

How to Use

Step 1 - Set your search queries

Enter one or more natural-language queries in the Search Queries field. Examples:

• hotels in New York
• hotels in Tokyo Shibuya
• luxury hotels Singapore Marina Bay
• budget hotels Paris near Eiffel Tower

You can run up to 5 queries per run, each returning up to 100 hotels.

Step 2 - Set your travel dates

Enter Check-in Date and Check-out Date in YYYY-MM-DD format. If left empty, the Actor defaults to tomorrow and the following day.

Step 3 - Configure guests and locale

Set Number of Adults (1-10), Country (affects which OTAs appear and local pricing), and Currency (the currency for all displayed prices).

Step 4 - Choose data sections

The Actor always keeps Overview and Prices in the output shape. By default, it runs in fast search-only mode (scrapeOtaPrices=false) and extracts basic price/overview signals from search results. Enable Scrape Hotel Detail Pages to visit each hotel page for richer OTA prices, reviews, photos, and about data; this mode takes longer, uses a minimum 300-second per-request timeout, and can push a partial base row with detailScrapeStatus="partial" if optional detail enrichment times out. Optionally add:

• Guest Reviews — individual guest reviews plus third-party aggregated ratings
• Hotel Photos — full photo gallery
• About / Amenities — check-in times, check-out times, and categorized amenities

More sections increase run time but provide richer data.

Step 5 - Apply filters and sorting

Use Minimum Rating (0-5) and Maximum Price Per Night to narrow results. Set both to 0 (default) to disable filtering. Choose a sort order for the output dataset.

Step 6 - Run and export

Click Save & Run. Results appear in the Dataset tab as structured JSON records. Export to JSON, CSV, Excel, or XML. Connect to downstream systems via the Apify API.

---

Input Parameters

Parameter	Type	Default	Description
queries	string[]	required	Hotel search queries (max 5). E.g., ["hotels in New York"]
checkIn	string	tomorrow	Check-in date in YYYY-MM-DD format
checkOut	string	day after tomorrow	Check-out date in YYYY-MM-DD format
adults	integer	2	Number of adult guests (1-10)
country	string	"us"	Country code for localized results (22 options)
currency	string	"USD"	Currency code for displayed prices (22 options)
maxResults	integer	1	Maximum hotels per query. Search-only supports 1-100; detail-page scraping is capped to 20 for reliability
scrapeOtaPrices	boolean	false	Visit each hotel's detail page to collect OTA prices, reviews, photos, and about data. When enabled, runtime raises per-request timeout to at least 300 seconds and emits detail status fields for bounded fallback
dataSections	string[]	["overview", "prices"]	Data sections to collect: overview, prices, reviews, photos, about
sortBy	string	"price_low"	Sort order: price_low, price_high, rating, reviews, name
minRating	number	0	Minimum Google rating filter — set to 0 to disable
maxPrice	integer	0	Maximum nightly price filter — set to 0 to disable
proxy	object	Apify Residential	HTTP proxy configuration. Residential proxies strongly recommended for Google Hotels scraping
requestHandlerTimeoutSecs	integer	120	Maximum seconds allowed per request (120-1800). Detail-page scraping is automatically raised to at least 300 seconds; increase further for slow proxies or larger runs

Supported Countries

us, gb, sg, jp, kr, de, fr, au, ca, in, th, br, it, es, nl, ae, hk, tw, my, id, ph, vn

Supported Currencies

USD, EUR, GBP, JPY, KRW, SGD, AUD, CAD, INR, THB, BRL, TWD, MYR, IDR, PHP, VND, AED, HKD, CHF, SEK, NOK, DKK

Data Sections

Value	Always Included	Description
overview	Yes (cannot be removed)	Hotel description, address, phone number, highlights, and nearby places
prices	Yes (cannot be removed)	Available provider prices, booking URLs when present, and cancellation details when exposed by Google Hotels
reviews	No	Individual guest reviews, star rating breakdown, and third-party review site ratings
photos	No	Hotel photo gallery URLs
about	No	Full hotel description, check-in/out times, address, and amenities by category

---

Output

Each hotel is saved as a single JSON object in the dataset. Optional fields are present only when the corresponding dataSections entry is selected.

Base Fields (always present)

Field	Type	Description
query	string	The search query that returned this hotel
hotelName	string	Hotel name
address	string | null	Hotel address or location description
rating	number | null	Google rating score (e.g., 4.2)
reviewCount	integer | null	Total number of reviews
starRating	integer | null	Hotel star classification (2-5)
lowestPrice	number | null	Lowest nightly price retained from the available result rows
currency	string	Requested currency code for the hotel row
prices	OtaPrice[]	Context-valid provider price rows available for this hotel
amenities	string[]	Hotel amenities list
imageUrl	string | null	Hotel thumbnail image URL
latitude	number | null	Latitude coordinate (from API intercept)
longitude	number | null	Longitude coordinate (from API intercept)
checkIn	string	Check-in date in YYYY-MM-DD format
checkOut	string	Check-out date in YYYY-MM-DD format
adults	integer	Number of adult guests
dealText	string | null	Special deal text (e.g., "25% less than usual")
url	string	Google Hotels URL for this hotel
scrapedAt	string	ISO 8601 timestamp of when data was scraped
detailScrapeStatus	string | null	Detail-mode status: success when requested detail data was collected, partial when base search data was pushed after a bounded fallback
detailScrapeStage	string | null	Detail stage that completed or triggered fallback, such as detail-hotel, api-fallback, or actor-deadline
detailScrapeElapsedMs	integer | null	Detail stage elapsed time in milliseconds
detailScrapeError	string | null	Fallback reason when detailScrapeStatus is partial; null on detail success

OTA Price Object (prices[])

Field	Type	Description
provider	string	OTA provider name (e.g., "Booking.com")
price	number	Nightly price from this provider
currency	string	Currency code
bookingUrl	string	Provider booking link when exposed by Google Hotels
cancellation	string | null	Cancellation policy (e.g., "Free cancellation")
features	string[]	Additional features (e.g., "Breakfast included")

Optional Nested Objects

overview (when overview section selected)

Field	Type	Description
description	string | null	Hotel description and highlights summary
address	string | null	Hotel address
phone	string | null	Hotel phone number
highlights	string[]	Key highlights and features
nearbyPlaces	string[]	Nearby points of interest

reviews (when reviews section selected)

Field	Type	Description
overallRating	number | null	Overall review score
totalReviews	string | null	Total review count text
ratingBreakdown	object	Star rating distribution (1-5 stars)
reviews	ReviewItem[]	Individual guest reviews (text, rating, date, author)
thirdPartyReviews	ThirdPartyReview[]	Aggregated ratings from Tripadvisor, Priceline, etc.

photos (when photos section selected)

Field	Type	Description
photos	string[]	Array of hotel photo URLs

about (when about section selected)

Field	Type	Description
description	string | null	Full hotel description
checkInTime	string | null	Check-in time (e.g., "3:00 PM")
checkOutTime	string | null	Check-out time (e.g., "12:00 PM")
address	string | null	Hotel address
amenitiesByCategory	object	Amenities organized by category name

---

Sample Output

The record below illustrates the existing output shape for a "hotels in New York" query with all five data sections enabled. Values, provider coverage, photos, and booking links vary by query, hotel, dates, and market.

The Manhattan at Times Square Hotel

{
  "query": "hotels in New York",
  "hotelName": "The Manhattan at Times Square Hotel",
  "address": "790 7th Ave, New York, NY 10019",
  "rating": 4.2,
  "reviewCount": 8547,
  "starRating": 4,
  "lowestPrice": 259,
  "currency": "USD",
  "prices": [
    {
      "provider": "Vio.com",
      "price": 259,
      "currency": "USD",
      "bookingUrl": "https://...",
      "cancellation": "Free cancellation",
      "features": []
    },
    {
      "provider": "Booking.com",
      "price": 271,
      "currency": "USD",
      "bookingUrl": "https://...",
      "cancellation": "Free cancellation",
      "features": []
    },
    {
      "provider": "Hotels.com",
      "price": 285,
      "currency": "USD",
      "bookingUrl": "https://...",
      "cancellation": "Free cancellation",
      "features": []
    },
    {
      "provider": "eDreams",
      "price": 377,
      "currency": "USD",
      "bookingUrl": "https://...",
      "cancellation": null,
      "features": []
    }
  ],
  "amenities": ["Free Wi-Fi", "Parking ($)", "Air conditioning", "Pet-friendly", "Fitness center", "Restaurant"],
  "checkIn": "2026-03-06",
  "checkOut": "2026-03-07",
  "adults": 2,
  "dealText": null,
  "scrapedAt": "2026-03-05T09:15:22.000Z",
  "overview": {
    "description": "Located in the heart of Midtown Manhattan, steps from Times Square...",
    "address": "790 7th Ave, New York, NY 10019",
    "phone": "+1 212-581-3300",
    "highlights": ["Prime Times Square location", "Recently renovated rooms"],
    "nearbyPlaces": ["Times Square (0.1 mi)", "Central Park (1.2 mi)", "Empire State Building (0.8 mi)"]
  },
  "reviews": {
    "overallRating": 4.2,
    "totalReviews": "8,547",
    "ratingBreakdown": { "5": 3200, "4": 2800, "3": 1500, "2": 700, "1": 347 },
    "reviews": [
      {
        "text": "Great location, clean rooms, friendly staff. Would stay again.",
        "rating": 5,
        "date": "2025-07-15",
        "author": "John D."
      }
    ],
    "thirdPartyReviews": [
      { "siteName": "Tripadvisor", "rating": "4.0", "reviewCount": "4,200" },
      { "siteName": "Priceline", "rating": "8.2", "reviewCount": "1,100" },
      { "siteName": "Trip.com", "rating": "4.1", "reviewCount": "980" },
      { "siteName": "Hotels.com", "rating": "8.4", "reviewCount": "2,300" }
    ]
  },
  "photos": {
    "photos": [
      "https://lh5.googleusercontent.com/p/AF1QipN...",
      "https://lh5.googleusercontent.com/p/AF1QipN..."
    ]
  },
  "about": {
    "checkInTime": "4:00 PM",
    "checkOutTime": "12:00 PM",
    "address": "790 7th Ave, New York, NY 10019",
    "amenitiesByCategory": {
      "Connectivity": ["Free Wi-Fi", "Business center"],
      "Dining": ["Restaurant", "Bar/Lounge", "Room service"],
      "Fitness": ["Fitness center"],
      "Policies": ["Pet-friendly", "Parking ($)", "Air conditioning"]
    }
  }
}

This example does not promise a fixed number of providers, reviews, or photos. Use a small run with your own market and dates to confirm coverage before scheduling a larger job.

---

Pricing

This Actor uses Pay Per Event (PPE) pricing.

Event	Price	When it is charged
hotel-result	$0.025 per event	Once for each billable hotel row written to the dataset
apify-actor-start	$0.00005 per event	At run start; Apify determines the event count from the run memory configuration

Diagnostic rows are not billed as hotel-result. A query that produces no billable hotel row has no hotel-result event, although the Actor start event still applies. In successful runs, chargedEventCounts.hotel-result should match the number of billable hotel rows.

Hotel-result cost examples

The estimates below show only the hotel-result component. The Actor start event is additional.

Scenario	Billable hotel rows	Hotel-result charge
Single city snapshot	20	$0.50
Three-city snapshot with 20 rows per city	60	$1.50
Daily watchlist with 50 rows	50 per run	$1.25 per run

Start with maxResults: 1 to check coverage and output for your target market before increasing the result count.

---

Runtime notes

• Search-only mode (scrapeOtaPrices: false) reads summary data without visiting each hotel detail page.
• Detail mode visits hotel pages for provider prices and optional sections. It takes longer and can return a base row with detailScrapeStatus="partial" when optional enrichment cannot finish within the bounded timeout.
• Multiple queries are supported, but duration depends on result count, selected sections, proxy quality, and Google Hotels response time.
• Retry deduplication prevents an already collected hotel from being billed twice when a query is retried.

---

Operating tips

Use residential proxies The Actor defaults to Apify Residential proxies because Google Hotels may block datacenter traffic. Custom or datacenter proxies can produce empty results or navigation failures.

Start with a small test run Set maxResults to 1 and keep dataSections at ["overview", "prices"] for your first run. Check the dataset, currency, and booking-link coverage before increasing the result count.

Enable only the sections your pipeline uses Each additional detail section can increase run time. Select only the fields your downstream pipeline uses.

Use specific, location-aware queries More specific queries return more relevant results. "hotels in Tokyo Shibuya near station" is more precise than "hotels in Japan". Google Hotels returns city-level results — overly broad geographic queries may not return useful data.

Disable scrapeOtaPrices for fast metadata runs When you only need hotel names, ratings, and summary prices from search results, set scrapeOtaPrices: false. This avoids the per-hotel detail-page step.

Schedule daily runs for price monitoring Use Apify Scheduling to run this Actor on a daily cadence with the same queries. Use the Apify API to compare datasets across runs and detect price changes over time.

Review timeout settings for detail runs The Actor applies a dynamic minimum timeout in detail mode. Larger result sets, slow proxies, or extra sections may still require a higher requestHandlerTimeoutSecs value.

---

Limitations

• Maximum 5 queries per run — each query is a separate Google Hotels search
• Maximum 100 hotels per query — capped by Google Hotels' result set pagination
• Display prices only — prices reflect what Google Hotels shows at scrape time and do not include taxes, fees, or member-only discounts applied during checkout
• Dynamic DOM dependency — Google Hotels updates its frontend periodically; minor extraction issues may occur after major UI changes
• OTA coverage varies by hotel — smaller or boutique properties may have fewer OTA partnerships and fewer prices in the comparison table
• Residential proxy recommended — the Actor defaults to Apify Residential because datacenter traffic may be blocked or return empty pages
• Adults-only occupancy — currently supports adult guest count only; children and multi-room configurations are not supported

---

Integrations

Apify API

Trigger runs and retrieve results programmatically:

# Start a run
curl -X POST \
  "https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "queries": ["hotels in Singapore"],
    "checkIn": "2026-04-01",
    "checkOut": "2026-04-02",
    "maxResults": 20,
    "dataSections": ["overview", "prices", "reviews"]
  }'

# Retrieve results from the dataset
curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_API_TOKEN&format=json"

Webhooks

Configure webhooks in the Actor settings to receive a POST notification when a run completes. Use the notification to load a dataset into a database or start your own comparison and alert workflow.

Scheduled Runs

Use Apify Scheduling to run the same input daily or weekly. Store the resulting dataset IDs so your own pipeline can compare observations across runs.

Data Export Formats

Results can be exported directly from the Dataset tab:

• JSON — full structured data, ideal for API consumers and data pipelines
• CSV — flat format for spreadsheet analysis (nested objects are serialized)
• Excel (.xlsx) — for manual review and reporting
• XML — for legacy system integration

Zapier and Make

Connect Actor runs to Zapier or Make (Integromat) workflows via the native Apify integration. Push hotel price data automatically to Google Sheets, Airtable, Slack, or any connected service.

---

FAQ

Does this Actor require a Google account or API key?

No. The Actor accesses Google Hotels as a standard browser session. No Google account, API key, or special credentials are required.

How accurate are the prices?

Prices reflect what Google Hotels displays at scrape time for the specified dates and guest count. They are display prices before taxes and fees. Actual checkout prices on OTA sites may differ due to taxes, service charges, or member-only discounts.

Can I search for a specific hotel by name?

Yes. Use a precise query such as "Marriott Marquis Times Square New York" to target a specific property. Note that Google may still return nearby alternatives. You can filter by hotelName in post-processing.

Why do some hotels have fewer OTA providers?

Smaller or boutique hotels may have fewer OTA partnerships. If a hotel has no price comparison data on Google Hotels, prices will be an empty array and lowestPrice will be null.

Can I run multiple queries to compare prices across different date ranges?

All queries in one run share the same checkIn and checkOut values. Run the Actor separately for each date range. hotel-result is charged per billable hotel row, not per query.

What happens if Google updates its UI?

The Actor combines API interception with DOM selectors. Changes to Google Hotels can affect either extraction path and may require an Actor update.

Why is scrapeOtaPrices disabled by default?

The default search-only path returns hotel identity, ratings, and summary price signals without visiting each hotel detail page. Enable scrapeOtaPrices when you need provider-level prices and booking URLs, and allow more run time for that work.

Can I use custom proxies instead of Apify Residential?

Yes. Set proxy.useApifyProxy: false and provide your proxy URLs in proxy.proxyUrls. Residential or mobile proxies are recommended; datacenter proxies may be blocked by Google Hotels.

Why is starRating null for some hotels?

Star rating is extracted from Google Hotels search results. Some hotels — particularly smaller or unclassified properties — do not have a star classification displayed by Google, resulting in a null value.