Tiket Hotel Reviews Scraper

Extract comprehensive hotel review data from Tiket hotel pages with a single run. Collect verified guest reviews, rating breakdowns, trip context, hotel metadata, and review summaries for analysis, monitoring, and reporting.

Features

• Review extraction — Collect individual guest reviews with timestamps, reviewer names, ratings, trip type, and helpfulness counts
• Rating breakdowns — Capture overall scores plus per-category ratings such as cleanliness, service, location, facilities, and value
• Hotel metadata — Enrich every review with hotel name, address, chain, star rating, facilities, nearby destinations, and location details
• Summary insights — Include aggregate review totals, average rating, impression labels, and topic highlights
• Pagination control — Stop at your requested result count while capping the maximum number of pages to scan

Use Cases

Reputation Monitoring

Track how guests describe a property over time. Spot recurring issues, strong service themes, and changes in review sentiment before they affect bookings.

Competitor Benchmarking

Compare rating distributions, review volume, and traveler segments across similar hotels. Build benchmarking datasets for internal reporting or market analysis.

Hospitality Research

Study guest feedback at scale for pricing, service quality, and property positioning. Use structured review outputs for dashboards, scoring models, or BI pipelines.

Lead Qualification

Evaluate hotel quality and traveler fit before outreach or partnership work. Summary metrics and detailed reviews help prioritize the right properties faster.

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Input Parameters

Parameter	Type	Required	Default	Description
hotel_url	String	No	—	Full Tiket hotel URL to scrape
hotel_id	String	No	—	Tiket hotel inventory ID, used when you do not want to pass the full URL
results_wanted	Integer	No	20	Maximum number of unique reviews to collect
max_pages	Integer	No	5	Maximum number of paginated review pages to fetch
proxyConfiguration	Object	No	—	Optional Apify proxy configuration for higher reliability

At least one of hotel_url or hotel_id should be provided.

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Output Data

Each item in the dataset contains review-level data enriched with hotel and summary details.

Field	Type	Description
hotel_id	String	Tiket hotel inventory ID
hotel_name	String	Hotel name
hotel_chain_name	String	Hotel chain or brand name
hotel_address	String	Full hotel address
hotel_city_name	String	City name
hotel_region_name	String	Region or province name
hotel_country_name	String	Country name
hotel_star_rating	Number	Star rating shown for the hotel
hotel_main_facilities	Array	Primary facilities available at the property
hotel_nearby_destinations	Array	Nearby destination titles from the hotel page
review_total_count	Number	Total review count for the hotel
review_average_rating	Number	Aggregate average review rating
review_topics	Array	Topic highlights associated with the property
review_id	String	Unique review identifier
reviewer_name	String	Guest name shown on the review
trip_type	String	Traveler segment such as family, business, couple, or solo
overall_rating	Number	Overall review score
review_text	String	Review body text
review_date	String	Review submission timestamp in ISO format
stay_start_date	String	Journey start timestamp in ISO format
stay_end_date	String	Journey end timestamp in ISO format
helpfulness_count	Number	Number of helpful votes
cleanliness_rating	Number	Cleanliness score when provided
service_rating	Number	Service score when provided
location_rating	Number	Location score when provided
facilities_rating	Number	Facilities score when provided
value_for_money_rating	Number	Value score when provided
review_image_urls	Array	Review image URLs when available
raw_comments	Array	Original comment objects from the source
raw_review_answers	Array	Original structured review answer objects

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Usage Examples

Basic Hotel URL Extraction

Collect reviews from a hotel page URL:

{
  "hotel_url": "https://www.tiket.com/en-us/hotel/indonesia/neo-denpasar-hotel-by-aston-807001751612811865",
  "results_wanted": 20
}

Inventory ID Input

Run the scraper using only the hotel inventory ID:

{
  "hotel_id": "neo-denpasar-hotel-by-aston-807001751612811865",
  "results_wanted": 50,
  "max_pages": 3
}

Proxy-Assisted Collection

Use Apify Proxy for more consistent runs at scale:

{
  "hotel_url": "https://www.tiket.com/en-us/hotel/indonesia/neo-denpasar-hotel-by-aston-807001751612811865",
  "results_wanted": 100,
  "max_pages": 5,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}

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Sample Output

{
  "hotel_id": "neo-denpasar-hotel-by-aston-807001751612811865",
  "hotel_name": "Neo Denpasar Hotel by ASTON",
  "hotel_chain_name": "Archipelago Hotels & Resorts",
  "hotel_address": "Jl. Gatot Subroto Barat, Padangsambian Kaja, Kec. Denpasar Bar., Kota Denpasar, Bali",
  "hotel_city_name": "Denpasar",
  "hotel_region_name": "Bali",
  "hotel_country_name": "Indonesia",
  "hotel_star_rating": 3,
  "hotel_main_facilities": [
    "Swimming Pool",
    "WiFi",
    "Parking"
  ],
  "review_total_count": 1836,
  "review_average_rating": 4.394,
  "review_topics": [
    "food",
    "staff",
    "price"
  ],
  "review_id": "64a6726c4b136500012651a8",
  "reviewer_name": "Rengga Erlinawati",
  "overall_rating": 5,
  "review_text": "Nyaman banget nih hotel dgn harga yg trjangkau Sayang jauh dr kuta",
  "review_date": "2023-07-06T10:31:08.539Z",
  "stay_start_date": "2023-07-03T05:30:00.000Z",
  "stay_end_date": "2023-07-04T05:30:00.000Z",
  "helpfulness_count": 2,
  "cleanliness_rating": 5,
  "service_rating": 5,
  "location_rating": 5,
  "facilities_rating": 5,
  "value_for_money_rating": 5,
  "review_source_label": "Verified review from tiket.com"
}

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Tips for Best Results

Choose a Valid Hotel Page

• Use a live Tiket hotel page or inventory ID
• Prefer the English hotel URL format when sharing links across systems

Start Small

• Use results_wanted: 20 for quick validation
• Increase the count once you confirm the property returns review data

Control Collection Scope

• Use max_pages to keep larger runs predictable
• For deep historical review collection, increase both results_wanted and max_pages

Use Proxies for Volume

• Residential proxies are recommended for repeated or larger runs
• Keep request sizes reasonable to reduce retries

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Integrations

Connect your dataset with:

• Google Sheets — Build quick review dashboards and scorecards
• Airtable — Organize hotels, segments, and traveler feedback in a searchable base
• Make — Trigger downstream automations from fresh review runs
• Zapier — Send alerts or records into business workflows
• Webhooks — Push review datasets into your own systems

Export Formats

• JSON — For custom applications and data pipelines
• CSV — For spreadsheet analysis
• Excel — For business reporting
• XML — For downstream integrations

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Frequently Asked Questions

Can I scrape reviews without the full hotel URL?

Yes. You can provide the Tiket hotel inventory ID with hotel_id.

Does the actor stop at my requested count?

Yes. It collects unique reviews until results_wanted is reached or max_pages is exhausted.

Why do some reviews have fewer fields?

Some guests do not provide every optional detail, image, or traveler label. The dataset keeps only fields that are present in the source.

Can I collect more than the newest page of reviews?

Yes. The actor paginates review pages automatically up to your max_pages limit.

What if the hotel has no reviews?

The actor will finish without records if the selected property does not expose review content.

Is proxy usage required?

No, but it can improve reliability for repeated or higher-volume runs.

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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.