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OYO Rooms Reviews Scraper: Extract Hotel Reviews & Ratings

What Is OYO Rooms?

OYOrooms.com is one of Asia's largest budget hotel chains and booking platforms, operating thousands of properties across India, Southeast Asia, and beyond. Guest reviews on OYO carry significant weight for booking decisions and brand reputation. Manually collecting this feedback at scale is impractical — the OYO Rooms Reviews Scraper automates extraction, delivering structured review data ready for analysis.

Overview

The OYOrooms.com Reviews Scraper targets a specific hotel's review section by ID, pulling guest feedback with flexible sorting and pagination controls. It suits:

• Hotel managers monitoring guest sentiment
• Reputation management teams tracking rating trends
• Market researchers benchmarking properties
• Data analysts building hospitality sentiment datasets

Input Format

The scraper uses a simple JSON configuration — no URLs required, just a hotel ID:

{
"hotel_id":"20146",
"sort_by":"rating-low",
"offset":30,
"max_items_per_url":200,
"ignore_url_failures":true
}

Input Fields

Tip: To collect the most critical feedback first, use "sort_by": "rating-low". For reputation monitoring, use "date-high" to surface the newest reviews.

Output Format

Sample Output Record

{
"review_id":444914740,
"user_name":"Rabiya",
"user_image":"usr.image",
"review_text":"A very nice hotel in banglore.\nThe reception gay is very friendly and helpful. Rooms are neat and clean.. specially washroom was very clean all was very good and nice..\nA very good hotel with a comfortable price...",
"date":"11 Nov 2025",
"rating":{
"bg_color":"#346000",
"title":"5"
},
"user_image_feedback_list":null,
"from_url":"https://www.oyorooms.com/api/pwa/updateHotelCall?url=https%3A%2F%2Fbff.oyorooms.com%2Fv1%2Fhotels%2Freviews%3Fovh_property%3Dfalse%26ai_generated_tags_flow%3Dfalse%26limit%3D30%26hotel_id%3D20146&offset=30&source=Web+Booking&user_mode%5B%5D=Consumer_Guest&sort_option=relevance_desc"
}

Each review returns a record with 7 fields:

How to Use

1. Find the hotel ID — Open the OYO hotel page (e.g., https://www.oyorooms.com/20146/). The number in the URL is the hotel_id.
2. Configure sorting — Choose sort_by based on your goal: sentiment analysis → rating-low; recency monitoring → date-high.
3. Set pagination — Use offset to paginate across large review sets. For example, run with offset: 0, then offset: 200, etc.
4. Set item limit — Adjust max_items_per_url based on how many reviews you need.
5. Run and export — Download results as JSON or CSV for analysis.

Common issues:

• If User Image or User Image Feedback List is empty, the reviewer did not upload a photo — this is expected behavior.
• If the hotel has fewer reviews than your max_items_per_url, the scraper returns whatever is available.

Use Cases & Business Value

• Sentiment analysis: Feed review text into NLP pipelines to classify guest satisfaction themes
• Reputation tracking: Monitor rating distribution over time for a property
• Competitive benchmarking: Compare review patterns across multiple OYO properties
• Training data: Build labeled datasets for hospitality-focused ML models using ratings + text pairs

Conclusion

The OYO Rooms Reviews Scraper makes it straightforward to collect structured guest feedback from any OYO property at scale. With sorting, pagination, and photo URL extraction built in, it delivers everything needed for reputation analysis, sentiment research, and competitive intelligence — in a single, clean dataset.