Opentable Reviews Parser Spider

The Opentable Reviews Parser Spider is a powerful Apify Actor designed to extract detailed customer reviews from OpenTable restaurant pages. It scrapes comprehensive review data, including ratings, text, and metadata, enabling users to gather insights into dining experiences efficiently. This tool is ideal for businesses, researchers, and analysts seeking reliable data for market analysis and decision-making.

Features

• Comprehensive Review Extraction: Captures full review details such as text, ratings across multiple categories (overall, food, service, ambience, value, noise), and author information.
• High Data Quality: Ensures accurate parsing of structured data from OpenTable, minimizing errors and providing clean, usable outputs.
• Scalable Performance: Handles multiple URLs efficiently, with built-in handling for large datasets and minimal resource usage.
• Flexible Input: Accepts a list of OpenTable restaurant URLs for batch processing, supporting up to hundreds of pages per run.
• JSON Output: Delivers results in a standardized JSON format, easy to integrate with other tools or export to CSV/Excel.
• Reliable and Ethical Scraping: Adheres to OpenTable's terms of service, using respectful crawling techniques to avoid overloading servers.
• Real-Time Insights: Extracts the latest reviews, including reservation and posting dates, for timely analysis.

Input Parameters

Parameter	Type	Required	Description	Example
Urls	array	Yes	An array of OpenTable restaurant URLs to scrape reviews from. Each URL must be a valid HTTP/HTTPS link to a restaurant page.	["https://www.opentable.com/r/the-marshal-new-york", "https://www.opentable.com/r/another-restaurant"]

Example Usage

To run the Actor, provide the input in JSON format:

{
  "Urls": [
    "https://www.opentable.com/r/the-marshal-new-york"
  ]
}

Example output:

[
  {
    "review_id": "OT-247060-48386-110034587861",
    "reservation_date": "2025-11-08T02:30",
    "posted_date": "2025-11-08T17:35",
    "author": "Suzanne",
    "author_metro": "New York City",
    "review_text": "We attended the taping of the finale for CNN's Have I got News for You\" and it ran 45 minutes late thereby making us 45 minutes late for our reservation. Despite that, the restaurant was VERY accommodating. They also had a good selection of seasonal specialties. We particularly enjoyed the seasonal squash soup which the restaurant split for us. Our choices of trout and meatloaf were both delightful. Finally, we appreciated that they participated in InKind.",
    "ratings": {
      "overall": 5,
      "food": 5,
      "service": 5,
      "ambience": 4,
      "value": 4,
      "noise": 3
    },
    "positive_feedback": 0,
    "negative_feedback": 0,
    "actor_id": "yU6JxgToMNlUrlk9x",
    "run_id": "4U6FW3y3A4neMuWS7"
  }
]

Use Cases

• Market Research and Analysis: Analyze customer sentiments and ratings to identify trends in dining preferences and service quality.
• Competitive Intelligence: Compare reviews across restaurants to benchmark performance and uncover strengths/weaknesses.
• Price Monitoring: Track value ratings to assess pricing strategies and customer perceptions.
• Content Aggregation: Collect review data for blogs, reports, or dashboards on the food industry.
• Academic Research: Gather datasets for studies on consumer behavior in hospitality.
• Business Automation: Automate review monitoring for restaurants to respond to feedback promptly.

Installation and Usage

1. Search for "Opentable Reviews Parser Spider" in the Apify Store
2. Click "Try for free" or "Run"
3. Configure input parameters
4. Click "Start" to begin extraction
5. Monitor progress in the log
6. Export results in your preferred format (JSON, CSV, Excel)

Output Format

The Actor outputs an array of JSON objects, each representing a single review. Key fields include:

• review_id: Unique identifier for the review.
• reservation_date and posted_date: Timestamps in ISO format.
• author and author_metro: Reviewer's name and location.
• review_text: Full text of the review.
• ratings: Object with numerical scores (1-5) for overall, food, service, ambience, value, and noise.
• positive_feedback and negative_feedback: Counts of user votes.
• actor_id and run_id: Metadata for the Apify run.

Data is structured for easy parsing and integration.

Support

For custom/simplified outputs or bug reports, please contact:

• Email: support@getdataforme.com
• Subject line: "custom support"
• Contact form: https://getdataforme.com/contact/

We're here to help you get the most out of this Actor!

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Extract and analyze OpenTable reviews effortlessly with the Opentable Reviews Parser Spider. Key features include comprehensive data extraction (ratings, text, metadata), scalable batch processing, and high-quality JSON outputs. Perfect for market research, competitive intelligence, and business automation. Start scraping today—try it free on Apify Store! (148 characters)