Priceline Hotel Reviews Scraper

Extract guest review data from Priceline hotel pages in a clean, analysis-ready dataset. Collect reviewer details, traveler type, review text, positive and negative remarks, category scores, and total review counts for hotel research, monitoring, and comparison.

Features

• Hotel URL or ID input - Start with a Priceline hotel page or a hotel ID.
• Guest review collection - Gather review text, reviewer metadata, ratings, and summary scores.
• Pagination support - Collect more reviews with results_wanted and max_pages.
• Clean output - Duplicate records and empty values are removed from saved records.
• Flexible URL handling - Supports standard Priceline /relax/at/ hotel URL patterns.

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Use Cases

Hotel Reputation Research

Track guest sentiment for a specific hotel. Review positive remarks, negative remarks, score patterns, and traveler profiles in one dataset.

Competitive Analysis

Compare hotels by guest feedback quality. Use scores for cleanliness, staff, location, and overall experience to evaluate strengths and weaknesses.

Travel Data Monitoring

Collect recent review samples for recurring reporting. Keep datasets small for fast checks or increase limits for deeper analysis.

Customer Experience Analysis

Study common complaints and praised amenities. Separate positive and negative remarks help teams classify recurring themes.

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Input Parameters

Parameter	Type	Required	Default	Description
hotelUrl	String	No	-	Priceline hotel URL to scrape
hotelId	String	No	-	Priceline hotel ID, used when URL is empty
results_wanted	Integer	No	20	Maximum reviews to collect
max_pages	Integer	No	5	Maximum review pages to request
sort	String	No	-	Optional review sort value
proxyConfiguration	Object	No	Disabled	Optional proxy settings

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Output Data

Field	Type	Description
hotel_id	String	Priceline hotel ID
source_url	String	Source hotel URL
page	Number	Review page number
current_page	Number	Current source review page
total_pages	Number	Total available review pages
review_id	String	Unique review ID
review_date	String	Review date
reviewer_name	String	Reviewer display name
reviewer_location	String	Reviewer location code
traveler_type	String	Traveler category
traveler_type_code	String	Traveler category code
review_text	String	General review text
positive_remark	String	Positive feedback
negative_remark	String	Negative feedback
score_overall	Number	Overall review score
score_cleanliness	Number	Cleanliness score
score_staff	Number	Staff score
score_location	Number	Location score
review_scores	Array	Detailed score labels and values
total_reviews	Number	Total available reviews
review_summary	String	Total review count label
review_summary_count	Number	Numeric review summary count
review_summary_scores	Object	Hotel-level summary scores
available_sort_options	Array	Sort options shown for reviews
available_filters	Array	Review filter groups and options

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Usage Examples

Scrape by Hotel URL

{
  "hotelUrl": "https://www.priceline.com/relax/at/326303/from/20260716/to/20260801/rooms/1",
  "results_wanted": 20
}

Scrape by Hotel ID

{
  "hotelId": "326303",
  "results_wanted": 50,
  "max_pages": 5
}

Larger Review Collection

{
  "hotelUrl": "https://www.priceline.com/relax/at/326303",
  "results_wanted": 100,
  "max_pages": 10
}

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Sample Output

{
  "hotel_id": "326303",
  "source_url": "https://www.priceline.com/relax/at/326303/from/20260716/to/20260801/rooms/1",
  "page": 1,
  "current_page": 1,
  "total_pages": 267,
  "review_id": "5299215231",
  "review_date": "Jun 2026",
  "reviewer_name": "Minnie",
  "reviewer_location": "ph",
  "traveler_type": "Group Traveler",
  "traveler_type_code": "GROUP",
  "review_text": "Decent hotel but a little bit old and needs some update.",
  "positive_remark": "Location",
  "negative_remark": "During check-in: felt mocked by staff.",
  "score_overall": 6,
  "score_cleanliness": 7,
  "score_staff": 8,
  "score_location": 8,
  "review_scores": [
    {
      "type": "CLEANLINESS",
      "score": "7",
      "label": "Cleanliness"
    }
  ],
  "total_reviews": 2668,
  "review_summary": "5,108 Reviews",
  "review_summary_count": 5108,
  "review_summary_scores": {
    "cleanliness": {
      "score": 7.3,
      "label": "Cleanliness"
    }
  }
}

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Tips for Best Results

Start Small

• Use results_wanted: 20 for test runs.
• Increase limits after confirming the hotel has enough reviews.

Use Valid Hotel Pages

• Use Priceline hotel pages that contain /relax/at/.
• If a URL changes, provide the hotel ID directly.

Tune Pagination

• Raise max_pages when collecting larger datasets.
• Use results_wanted and max_pages to control collection size.

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Integrations

Connect your data with:

• Google Sheets - Review data and score tracking
• Airtable - Searchable review databases
• Webhooks - Send results to your system
• Make - Automated reporting workflows
• Zapier - Trigger alerts from new datasets

Export Formats

• JSON - For developers and data pipelines
• CSV - For spreadsheets
• Excel - For business reporting
• XML - For system integrations

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Frequently Asked Questions

Can I use only a hotel ID?

Yes, you can provide hotelId without a URL.

Does it collect all reviews?

It collects up to your results_wanted and max_pages limits.

Why are some fields missing?

Fields are omitted when Priceline does not provide a value for that review.

Can I collect reviews from multiple hotels?

Run the actor once per hotel to keep datasets clearly separated.

What URL formats are supported?

Priceline hotel URLs using /relax/at/326303 and dated variants are supported.

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Support

For issues or feature requests, contact support through the Apify Console.

Resources

• Apify Documentation
• API Reference
• Scheduling Runs

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Legal Notice

This actor is designed for legitimate data collection purposes. Users are responsible for ensuring compliance with website terms of service and applicable laws. Use data responsibly and respect rate limits.