How do I connect Make to Scrapernode?

Use Make's webhook trigger to receive data from Scrapernode. Copy the webhook URL from Make and paste it into Scrapernode's webhook settings for the scraper. Each completed job sends results automatically.

What Google Hotels search data fields are sent to Make?

All 16 output fields from the Google Hotels Search scraper are included: url, hotel_id, hotel_name, rating, review_count, star_classification, and more. The full payload is sent as structured JSON — no fields are filtered out.

Can I schedule recurring Google Hotels scrapes to Make?

Yes. Use Make's scheduling features to trigger Scrapernode scrapes on a recurring basis via the REST API. You can also set up Make to process results as they arrive via webhooks.

How much does it cost to scrape Google Hotels search into Make?

Each search record costs 1 credit. Credits start at $9 for 3,000 credits (Starter plan). The Make integration itself is included free — no additional charges for data delivery.

What happens if the Make delivery fails?

Your scraped data is always stored in Scrapernode regardless of the integration status. If delivery to Make fails, you can re-trigger the sync or download results manually as CSV or JSON from the job details page.

Google HotelsMake

How to Scrape Google Hotels Search into Make

Extract search data from Google Hotels and pipe into Make automatically

Step-by-step guide

Choose the Google Hotels Search scraper

Navigate to the Google Hotels Search scraper in Scrapernode. Select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 1 credit.

Set up your Make connection

Create a new Make scenario with a Webhook trigger module. Copy the webhook URL into Scrapernode's webhook settings. Use Make's built-in JSON parser to map scraper fields to downstream modules like "Create Spreadsheet Row" or "Send Email".

Provide your Google Hotels input URLs

Paste the Google Hotels URLs you want to scrape — one per line, or upload a CSV. Scrapernode accepts direct profile links, search result URLs, and content pages.

Launch the scraping job

Click "Start Extraction" to begin. Scrapernode handles proxy rotation, rate limiting, and anti-bot detection automatically. Jobs typically complete in under 60 seconds per batch.

Receive data in Make

When the job completes, Scrapernode sends the full results to your Make workflow. Each record includes 16 fields like url, hotel_id, hotel_name, rating. Route the data to any downstream app — CRMs, databases, email tools, and more.

Cost per record

1 credit

Output fields

16 fields

Destination

Make

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5

Url

sample_url

Hotel Id

sample_hotel_id

Hotel Name

sample_hotel_name

Rating

4.5

Review Count

sample_review_count

Star Classification

1,000

Address

600 Guerrero St, San Francisco, CA 94110

Phone Number

sample_phone_number

Photos

sample_photos

Description

Enterprise-grade data pipeline platform with real-time processing and 99.99% uptime SLA.

Amenities

sample_amenities

Price Info

sample_price_info

Reviews

475

Location

San Francisco, CA

Website

https://stripe.com

Input Url

https://www.linkedin.com/in/sarahchen

Data Dictionary

16 fields returned per record

The URL of the hotel listing on Google (100.00% fill rate)

Hotel unique identifier (100.00% fill rate)

The official name of the hotel (100.00% fill rate)

The overall rating of the hotel (87.66% fill rate)

The total number of reviews (87.66% fill rate)

The star classification of the hotel (61.94% fill rate)

The full street address of the hotel (73.62% fill rate)

The contact phone number for the hotel (72.31% fill rate)

Hotel photos (99.32% fill rate)

Hotel description text (78.45% fill rate)

List of hotel amenities (91.23% fill rate)

Pricing information for the hotel (82.14% fill rate)

Sub-fields

priceNumberPrice per night

currencyTextPrice currency

check_inTextCheck-in date

check_outTextCheck-out date

guestsNumberNumber of guests

Customer reviews for the hotel (65.32% fill rate)

Sub-fields

authorTextReview author name

ratingNumberReview rating

dateTextReview date

textTextReview text

sourceTextReview source platform

Geographic location of the hotel (73.62% fill rate)

Sub-fields

latitudeNumberLatitude coordinate

longitudeNumberLongitude coordinate

neighborhoodTextNeighborhood name

Hotel official website URL (68.44% fill rate)

The URL that was entered when starting the scraping process (100.00% fill rate)

Frequently Asked Questions

Common questions about How to Scrape Google Hotels Search into Make

Ready to connect Google Hotels data to Make?

Start extracting google hotels search data and pipe into Make in minutes.

Go to Google Hotels Search scraper Browse all integration guides

No code requiredAuto-delivery to Make16 data fields