What Does BrowserAct Booking.com Hotel Reviews Scraper Do?
Use BrowserAct Booking.com Hotel Reviews Scraper to collect public guest reviews from one Booking.com property, including hotel_name, positive_review, negative_review, review_text, score. The Bot stays within the selected public Booking.com page flow and returns structured review records for hotel operators monitoring guest feedback, hospitality teams comparing property reputation, or downstream automation without writing code or requiring a target-site login. Run it in BrowserAct or invoke the same published template through its API Tab.
Key Features of Booking.com Hotel Reviews Scraper
- Configure
review_sort,traveler_type,hotel_url,start_positionto reuse the same Bot for different public Booking.com targets. - Collect public guest reviews from one Booking.com property from the template's defined public page flow.
- Return structured review records with fields such as
hotel_name,reviewer_name,reviewer_country,review_date,stay_date. - Run without a target-site account login or custom scraper code.
- Use the API Tab to connect the same published template to downstream automation.
What Data Can I Extract from Booking.com?
| Field | Description |
|---|---|
position | Position returned from the public Booking.com page. |
review_id | Review Id returned from the public Booking.com page. |
hotel_name | Visible hotel name shown on Booking.com. |
reviewer_name | Visible reviewer name shown on Booking.com. |
reviewer_country | Structured reviewer country extracted from the public source. |
review_date | Visible review date when the source provides it. |
stay_date | Visible stay date when the source provides it. |
traveler_type | Traveler Type returned from the public Booking.com page. |
room_type | Room Type returned from the public Booking.com page. |
stay_length | Stay Length returned from the public Booking.com page. |
review_title | Visible review title shown on Booking.com. |
positive_review | Positive Review returned from the public Booking.com page. |
negative_review | Negative Review returned from the public Booking.com page. |
review_text | Visible review text returned by the public page. |
score | Structured score extracted from the public source. |
source_url | Public source URL associated with the review. |
next_start_position | Next Start Position returned from the public Booking.com page. |
How to Use Booking.com Hotel Reviews Scraper
Quick Start Guide
1. Open Run Task.
2. Review or change the populated input values.
3. Run the Bot.
4. Review the structured result in the Output Tab.
5. Connect the published template to your downstream workflow when needed.
Input Parameters
| Parameter | Configuration |
|---|---|
review_sort | Dropdown; required; default Most relevant. Choose one supported review sort option. Options: Most relevant, Newest first, Highest score, Lowest score. |
traveler_type | Dropdown; required; default All reviewers. Choose one supported traveler type option. Options: All reviewers, Families, Couples, Groups of friends, Solo travelers, Business travelers. |
hotel_url | String; required; default https://www.booking.com/hotel/us/new-york-95-west-broadway.html. Public hotel url to process. |
start_position | Integer; required; default 1. First one-based source position eligible for output. |
exclude_review_ids | String; required; default none. Previously collected identifiers or URLs to skip; use none when not needed. |
max_results | Integer; required; default 10. Maximum number of records to return. |
Example Output
The table shows one representative real result. Long text is shortened only in this documentation preview.
| Field | Result |
|---|---|
position | 1 |
review_id | 3f82f202f8286d6a |
hotel_name | The Frederick Hotel Tribeca, a Small Luxury Hotel |
reviewer_name | Annabelle |
reviewer_country | United States |
review_date | 2026-08-11 |
stay_date | 2026-08-08 |
traveler_type | Couple |
room_type | Premium 1 King Bed |
stay_length | 2 |
review_title | null |
positive_review | A simply decorated room, marble sink in bathroom, views, quiet. Old-fashioned feeling but not over the top. Breakfast was amazing. Great neighborhood with restaurants, coffee shops, supermarkets and pharmacies nearby.... |
negative_review | No water boiler in the room. But you can get coffee in the lobby in the morning between 5-7, before the breakfast room opens. |
review_text | A simply decorated room, marble sink in bathroom, views, quiet. Old-fashioned feeling but not over the top. Breakfast was amazing. Great neighborhood with restaurants, coffee shops, supermarkets and pharmacies nearby.... |
score | 9 |
source_url | https://www.booking.com/hotel/us/new-york-95-west-broadway.html |
next_start_position | 2 |
How Does It Work?
1. BrowserAct validates the supplied inputs and maps supported dropdown selections.
2. The Bot constructs or normalizes the target URL and opens the selected public review page.
3. It reads eligible review records in source order without entering unrelated pages or account-only areas.
4. It normalizes visible values, preserves valid optional values, and stops when the requested result limit or the end of the public list is reached.
5. The run returns one structured response for review, export, or downstream automation.
How to Build a New Scraper Bot with Agent Built
Step 1: Describe the data you need
Open BrowserAct and start Agent Built from the Home prompt box or from Create > Build with Agent. Describe the public website, records, filters or search conditions, output fields, result limit, and reusable inputs you need.
Step 2: Let BrowserAct build and test the Bot
BrowserAct explores the live website, creates the navigation and extraction workflow, and tests the resulting Bot. Provide any requested clarification about the target page, conditions, fields, or expected output in the same build conversation.
Step 3: Run the Bot and review the result
Run the completed Bot with its populated default inputs. Review the structured records, source URLs, missing optional values, and result count before reusing the Bot with other inputs or connecting it to another workflow.
Use Cases
- Hotel operators monitoring guest feedback.
- Hospitality teams comparing property reputation.
- Researchers analyzing traveler sentiment.
- Connect the structured result to API clients, n8n, Make, Zapier, MCP-based agents, or supported exports.
Why Use Booking.com Hotel Reviews Scraper?
- Reuse a tested public-page workflow instead of configuring the extraction from the beginning.
- Receive structured review records that can move directly into research, review, or automation.
- Change supported inputs without rebuilding the Bot for every run.
Who Can Use Booking.com Hotel Reviews Scraper?
- Teams working on hotel operators monitoring guest feedback.
- Teams working on hospitality teams comparing property reputation.
- Teams working on researchers analyzing traveler sentiment.
- Developers and automation teams connecting public web data to downstream systems.
How Many Results Can You Scrape?
Use the max_results input to control the requested result count. Start with the populated default of 10, then increase it gradually when the public source and your workflow support a larger run.
Automation and Export
BrowserAct produces structured data first. Use the result through Run Task, the JSON API, n8n, Make, Zapier, MCP-based agents, or the supported manual export flow.
Need Help?
Cannot find the exact capability you need, or need help composing several Bots?
