Opentable Reviews Scraper

How it works

This actor is designed to extract detailed reviews from OpenTable restaurant listings. The scraper captures comprehensive review data including ratings, review text, reviewer information, and visit details, allowing for in-depth analysis of restaurant feedback.

Features

This actor offers the following features:

• Comprehensive Review Extraction: Captures detailed review information including ratings, text, dates, and reviewer details.
• Pagination Support: Automatically handles pagination to collect all available reviews.
• Structured Data Output: Provides clean, structured data in JSON format for easy analysis.
• Proxy Support: Built-in support for proxies to avoid blocking and improve reliability.
• Customizable Configuration: Adjust settings like concurrency, retries, and item limits.

How to Use

1. Set Up: Ensure you have an Apify account and access to the Apify platform.
2. Input Restaurant URLs: Specify one or more OpenTable restaurant URLs to scrape reviews from, e.g.:
   • https://www.opentable.com/r/jays-fort-lauderdale
   • https://www.opentable.com/r/restaurant-name-new-york
3. Configure Settings (Optional):
   • Set maxItems to limit the number of reviews to scrape
   • Adjust concurrency settings if needed
   • Configure proxy settings if required
4. Run the Actor: Start the actor and monitor its progress.
5. Download Results: Export the scraped data in your preferred format (JSON, CSV, etc.).

Supported URL Formats

The scraper supports the following URL formats:

1. Restaurant Profile Pages
   • Example: https://www.opentable.com/r/restaurant-name-new-york
   • Example: https://www.opentable.com/restaurant/profile/1234567
   • Scrapes all available reviews for the specified restaurant

Input Data

Here's an example input for scraping reviews from OpenTable:

{
    "startUrls": [
        {
            "url": "https://www.opentable.com/r/restaurant-name-new-york"
        },
        {
            "url": "https://www.opentable.com/restaurant/profile/1234567"
        }
    ],
    "maxItems": 100,
    "maxConcurrency": 10,
    "minConcurrency": 1,
    "maxRequestRetries": 30,
    "includeListingDetails": true
}

Input Parameters

Parameter	Type	Default	Description
startUrls	Array	Required	List of URLs to start scraping from
maxItems	Integer	100	Maximum number of items to scrape
maxConcurrency	Integer	100	Maximum concurrent requests
minConcurrency	Integer	1	Minimum concurrent requests
maxRequestRetries	Integer	30	Number of retries for failed requests
includeListingDetails	Boolean	true	Whether to include detailed listing information

Output Structure

The scraper returns an array of review objects, each containing detailed information about a restaurant review. Here's an example of the output structure:

Example Review

{
    "id": "OT-1426036-2423-100179421960",
    "reservationDate": "2025-06-29T22:15",
    "postedDate": "2025-06-30T16:41",
    "author": "Michael",
    "authorMetro": "Miami - Dade",
    "review": "Excellent food and ambiance. I would definitely go again. Steaks were great!",
    "recommended": true,
    "statistics": {
        "overallRating": 5,
        "food": 5,
        "service": 5,
        "ambience": 5,
        "value": 4,
        "noise": 3
    },
    "positiveFeedback": 0,
    "negativeFeedback": 0,
    "authorDetails": {
        "initials": "M",
        "publicProfileColor": "MUSTARD",
        "approvedTextReviews": 0,
        "approvedRatingOnlyReviews": 0,
        "dinerIsVIP": false
    }
}

Common Output Fields

Review Information

Field	Type	Description
id	String	Unique identifier for the review (format: OT-{restaurantId}-{sequence}-{uniqueId})
reservationDate	String	Date and time of the reservation in ISO 8601 format
postedDate	String	Date and time when the review was posted in ISO 8601 format
author	String	Display name of the reviewer
authorMetro	String	Metro area where the reviewer is located
review	String	The full text of the review
recommended	Boolean	Whether the reviewer recommends the restaurant
positiveFeedback	Number	Count of users who found this review helpful
negativeFeedback	Number	Count of users who did not find this review helpful

Rating Statistics

Field	Type	Description
statistics.overallRating	Number	Overall rating (1-5)
statistics.food	Number	Food quality rating (1-5)
statistics.service	Number	Service quality rating (1-5)
statistics.ambience	Number	Ambience rating (1-5)
statistics.value	Number	Value for money rating (1-5)
statistics.noise	Number	Noise level rating (1-5, where 1=Quiet, 5=Very Noisy)

Author Details

Field	Type	Description
authorDetails.initials	String	Reviewer's initials
authorDetails.publicProfileColor	String	Color code for the reviewer's profile
authorDetails.approvedTextReviews	Number	Count of approved text reviews by this user
authorDetails.approvedRatingOnlyReviews	Number	Count of rating-only reviews by this user
authorDetails.dinerIsVIP	Boolean	Whether the reviewer has VIP status

Explore More Scrapers

If you found this Apify Smartbuyglasses Scraper useful, be sure to check out our other powerful scrapers and actors at memo23's Apify profile. We offer a wide range of tools to enhance your web scraping and automation needs across various platforms and use cases.

Support

• For issues or feature requests, please use the Issues section of this actor.
• If you need customization or have questions, feel free to contact the author:
  • Author's website: https://muhamed-didovic.github.io/
  • Email: muhamed.didovic@gmail.com

Additional Services

• Request customization or whole dataset: muhamed.didovic@gmail.com
• If you need anything else scraped, or this actor customized, email: muhamed.didovic@gmail.com
• For API services of this scraper (no Apify fee, just usage fee for the API), contact: muhamed.didovic@gmail.com