TheFork Restaurant Reviews Scraper: Extract Ratings & Feedback at Scale

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What Is TheFork?

TheFork (formerly LaFourchette) is one of Europe's leading restaurant discovery and reservation platforms, operating across 20+ countries. Each restaurant profile hosts hundreds of verified diner reviews — a goldmine for restaurateurs, marketers, and food-tech developers. The TheFork Reviews Scraper automates extraction of this review data, turning pages of feedback into structured, analyzable datasets.

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Overview

This scraper targets TheFork restaurant review pages, collecting verified guest feedback with full metadata. It is built for:

• Restaurant owners monitoring reputation and tracking guest sentiment
• F&B consultants benchmarking competitors across ratings and keywords
• Data analysts building sentiment models on dining experiences
• Developers powering review aggregators or hospitality dashboards

Configurable sorting, pagination offset, and per-URL limits make it suitable for both quick snapshots and large-scale bulk collection.

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Input Format

{
  "ignore_url_failures": true,
  "max_items_per_url": 200,
  "offset": 0,
  "urls": [
    "https://www.thefork.com/restaurant/bistrot-xvi-r840349/reviews"
  ],
  "sort_by": "RATING-DESC"
}

Field	Type	Description
urls	array	One or more TheFork restaurant review page URLs (must end in /reviews). Add individually or via bulk edit.
sort_by	string	Sort order for reviews. Options: MEAL_DATE-DESC (Newest), RATING-DESC (Score high to low), RATING-ASC (Score low to low)
offset	integer	Review index to start from. Use 0 for the beginning; increase to resume from a specific position (e.g., 100 to skip the first 100 reviews).
max_items_per_url	integer	Maximum reviews to collect per URL. Default prefill: 20. Set higher (e.g., 200) for comprehensive collection.
ignore_url_failures	boolean	If true, failed URLs are skipped rather than stopping the entire run — recommended for bulk jobs.

Tip: To collect only negative reviews for analysis, use sort_by: "RATING-ASC". To collect the most recent feedback, use "MEAL_DATE-DESC".

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Output Format

Sample Record (abbreviated)

{
  "id": "005991a0-fd58-43bf-ab23-a9cdbe297584",
  "uuid": "005991a0-fd58-43bf-ab23-a9cdbe297584",
  "rating_value": 10,
  "meal_date": "2025-12-06T12:45:00.000Z",
  "review": {
    "review_body": "très bien positionné. La serveuse a su gérer en étant toute seule. top !",
    "__typename": "RatingReview"
  },
  "reviewer": {
    "id": "376e7cbf-e63c-4606-b6d2-29ad31b3f357",
    "avatar_url": "https://cdn.thefork.com/tf-lab/image/upload/v1779222864/avatar/376e7cbf-e63c-4606-b6d2-29ad31b3f357.png",
    "first_name": "vincent",
    "last_name": "d.",
    "review_count": 48,
    "__typename": "Reviewer"
  },
  "restaurant_reply": null,
  "photos": [],
  "likes": 0,
  "keywords_position": null,
  "from_url": "https://www.thefork.com/restaurant/bistrot-xvi-r840349/reviews"
}

Each record represents one verified diner review with the following fields:

Core Review Data

Field	Meaning
ID	Internal numeric identifier for the review
UUID	Universally unique identifier — useful as a stable key when deduplicating across runs
Rating Value	Numerical score given by the diner (typically on TheFork's 10-point scale)
Meal Date	The date the diner visited the restaurant (not the date the review was posted)
Review	Full text of the diner's written feedback

Reviewer & Response

Field	Meaning
Reviewer	Profile metadata of the person who left the review (may include display name, reviewer tier)
Restaurant Reply	The restaurant's official response to the review, if one exists — useful for tracking engagement quality

Enrichment Fields

Field	Meaning
Photos	Images attached to the review by the diner
Likes	Number of "helpful" or like reactions the review has received from other users
Keywords Position	Structured keyword or tag data associated with the review — may indicate dish mentions, service aspects, or TheFork-generated topic tags

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How to Use

1. Get the review URL — Navigate to any restaurant on TheFork and go to the Reviews tab. Copy the URL (format: .../restaurant/[name]-r[id]/reviews).
2. Configure input — Paste the URL(s), set sort_by and max_items_per_url to match your needs.
3. Set offset if resuming — Use offset to paginate large datasets across multiple runs.
4. Run and export — Download results as JSON or CSV for use in Excel, Google Sheets, or your data pipeline.

Common issues:

• If no data is returned, confirm the URL ends in /reviews — product or menu pages will not work.
• TheFork may vary page structure by country/locale; test with one URL before bulk runs.

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Use Cases & Business Value

• Reputation management: Track rating trends over time and flag negative feedback early
• Competitor benchmarking: Compare review volumes, average scores, and response rates across restaurants
• Sentiment analysis: Feed review text into NLP pipelines to extract topics and sentiment at scale
• Menu intelligence: Mine Keywords Position and review text for frequently mentioned dishes

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Conclusion

The TheFork Reviews Scraper delivers structured, verified dining feedback at scale — eliminating hours of manual reading and copy-pasting. Whether you're managing a single venue or analyzing hundreds of competitors, it provides the raw material for data-driven hospitality decisions.