Szallas.hu Hotel Reviews Scraper

Scrape authentic guest feedback from Szallas.hu and turn it into structured, analysis-ready review data for travel research, hospitality benchmarking, and reputation monitoring.

Collect detailed hotel review insights including:

• ⭐ Overall guest ratings and score distributions
• 📝 Positive and negative guest feedback
• 🏨 Hotel-level summary metrics and aggregate review scores
• 📅 Review dates normalized for consistent reporting
• 👤 Reviewer labels, room information, and review metadata
• 🔄 Review pagination across the full available history

Built for teams that need reliable, searchable, and exportable hotel review intelligence from one of the leading accommodation review platforms in Hungary.

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✨ Features

• ✅ Scrape hotel reviews from Szallas.hu property pages
• ✅ Collect multiple properties in a single run via startUrls
• ✅ Filter results using cutoffDate for incremental updates
• ✅ Limit the result count per hotel with maxReviewsPerHotel
• ✅ Sort reviews by newest, oldest, highest score, or lowest score
• ✅ Return both individual review records and a hotel summary record
• ✅ Capture hotel-level aggregate score and review count
• ✅ Preserve raw review payloads for high-fidelity downstream analysis
• ✅ Ready for Apify API workflows and dataset export

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🔍 Supported Szallas.hu Pages

The scraper accepts valid Szallas.hu hotel detail URLs only. Standalone hotel IDs, city search pages, or arbitrary search queries are not supported.

Supported URL formats:

https://szallas.hu/aquamarina-hotel-visegrad
https://szallas.hu/hotel-villa-volgy-eger
https://szallas.hu/hotel-silver-hajduszoboszlo

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🔍 What You Can Use It For

This scraper is designed for:

• Hotel reputation monitoring
• Competitive review benchmarking
• Guest sentiment analysis
• Travel market intelligence
• Content and SEO research
• Hospitality analytics dashboards
• AI and machine learning datasets for travel and accommodation analysis

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⚙️ Input Configuration

Field	Type	Description
startUrls	array	One or more Szallas.hu hotel detail URLs
maxReviewsPerHotel	integer	Maximum reviews to return per hotel
cutoffDate	date	Return only reviews on or after this date (YYYY-MM-DD)
sortBy	string	Ordering: newestFirst, oldestFirst, highestRated, lowestRated
alwaysReturnSummary	boolean	Include a hotel summary record for each URL

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📥 Example Input

{
  "startUrls": [
    {
      "url": "https://szallas.hu/hotel-villa-volgy-eger"
    }
  ],
  "maxReviewsPerHotel": 100,
  "cutoffDate": "2025-01-01",
  "sortBy": "newestFirst",
  "alwaysReturnSummary": true
}

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📦 Output Dataset

The scraper returns a clean review dataset suitable for direct analysis, storage, or integration with business intelligence pipelines.

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🧾 Output Fields

Field	Description
recordType	review or summary
reviewId	Review identifier
reviewDate	Review date standardized for reporting
reviewScore	Overall review score
reviewText	Positive guest comment
negativeReviewText	Negative guest comment, when available
reviewerName	Reviewer label
hotelRoomName	Room type mentioned in the review
hotelSummary	Aggregate hotel performance metrics
rawReviewData	Original review payload returned by the source

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🏨 Example Review Output

{
  "recordType": "review",
  "reviewId": 4098653,
  "reviewDate": "2026-10-15",
  "reviewScore": 10,
  "reviewText": "Nagyon pozitív élményekkel távoztunk a Villa Völgyből...",
  "negativeReviewText": null,
  "reviewerName": "Fiatal pár",
  "hotelRoomName": "Superior Földszint/Emelet kétágyas szoba (pótágyazható)",
  "hotelSummary": {
    "url": "https://szallas.hu/hotel-villa-volgy-eger",
    "id": "458637",
    "reviewCount": 3919,
    "reviewScore": 9.1,
    "scoreDetails": {
      "all": 9.1
    }
  }
}

Example summary record:

{
  "recordType": "summary",
  "hotelSummary": {
    "url": "https://szallas.hu/hotel-villa-volgy-eger",
    "id": "458637",
    "reviewCount": 3919,
    "reviewScore": 9.1,
    "scoreDetails": {
      "all": 9.1
    }
  }
}

ℹ️ Review dates are normalized for clean reporting and analysis.

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🌍 Ideal Use Cases

Perfect for:

• Hotel reputation monitoring — Track how guests rate the property over time
• Competitive benchmarking — Compare review quality and aggregate scores across accommodations
• Guest sentiment analysis — Identify recurring positive and negative themes in feedback
• Travel market intelligence — Understand demand, customer satisfaction, and performance trends
• SEO and content strategy — Use guest feedback to inform landing pages and editorial content
• Hospitality analytics — Combine review data with broader customer experience metrics

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🚀 Integrations

Platforms:

• Apify API & Console
• Python
• Node.js
• JavaScript
• Go
• Java

Workflows:

• Zapier
• Make.com
• Google Sheets
• Airtable
• Slack
• Discord
• Custom webhooks

Data warehouses:

• Google BigQuery
• Snowflake
• Amazon Redshift
• Azure Data Lake
• Airbyte

AI/ML:

• OpenAI / GPT
• LangChain
• Hugging Face
• Custom NLP pipelines

Export formats:

• JSON
• CSV
• Excel
• API delivery

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📌 Notes

• The scraper is optimized for hotel review collection and scoring workflows.
• Results can be filtered by date and sorted by review ordering to match your research needs.
• Summary records give you a hotel-level view without losing the individual review detail.