Scraping Hotel Data from Accor: A Step-by-Step Guide to Collecting 6,000+ Listings

Introduction

In today’s data-driven world, access to accurate and structured hotel data is essential for competitive analysis, marketing, and travel technology innovations. Actowiz Solutions, a leading provider of web scraping services, recently undertook a massive project to scrape and compile data from over 6,000 hotels listed on the Accor Hotels website into a structured Google Sheet format. This blog breaks down the entire process, highlighting the tools, techniques, and SEO strategies involved in this data scraping journey.

Why Scrape Hotel Data?

Web scraping hotel data empowers businesses and analysts to:

• Monitor real-time room pricing trends
• Understand global hospitality patterns
• Collect accurate contact information for outreach
• Compare hotel amenities and services
• Support travel recommendation engines and booking platforms

Actowiz Solutions specializes in scalable hotel data scraping services tailored to extract data from global hotel directories like Accor.

Project Objective: Structured Data for 6,000+ Accor Hotels

The primary goal was to extract key information for each hotel listed on Accor’s global directory (https://all.accor.com/gb/world/hotels-accor-monde.shtml) and structure this data within a shared Google Sheet.

Target Data Points:

• Hotel Name
• Nightly Rate
• Hotel Page URL
• Address
• City
• Country
• Phone Number
• Email Address

Additionally, Actowiz Solutions included an optional but highly valuable phase: gathering each hotel's General Manager's name and their LinkedIn profile URL.

Step-by-Step Process to Scrape Accor Hotel Data

1. Project Planning and Site Structure Analysis

Actowiz Solutions began by analyzing the structure of the Accor Hotels directory. The directory categorizes hotels by continent, country, and city. Each hotel listing leads to a dedicated hotel page containing comprehensive information.

2. Identifying HTML Tags and Patterns

The team inspected HTML patterns using tools like Chrome DevTools to identify consistent selectors for hotel names, rates, addresses, and contact details. Dynamic elements were detected and handled with headless browsers like Puppeteer or Selenium.

3. Automating Data Extraction Scripts

Using Python with libraries such as BeautifulSoup, Scrapy, and Selenium, custom scripts were written to:

• Navigate through all hotel listings
• Extract relevant data points
• Avoid duplicate entries
• Handle pagination and dynamic loads

4. Cleaning & Structuring the Data

Data was cleaned using Python pandas to remove extra spaces, unify formats (e.g., currency), and validate emails and phone numbers.

5. Uploading to Google Sheets

Actowiz Solutions automated the upload using the Google Sheets API to sync the data in real time. The final output was stored here:

Google Sheet Sample Output

6. Optional Task: Extracting LinkedIn Details

To go a step further, Actowiz Solutions used a separate scraping phase and third-party LinkedIn search APIs to gather:

• General Manager's Full Name
• LinkedIn Profile URL

This extra layer of data is valuable for B2B outreach and hotel executive research.

Sample Data Format (As Delivered)

Here’s a snippet of how the structured data appeared in the sheet:

Hotel Name: Sofitel Bahrain Zallaq Thalassa sea & spa

Nightly Rate: 269.23$AU

URL: https://all.accor.com/hotel/6722/index.en.shtml

Address: 105 Zallaq Highway, Building 2015, Block 1055, Zallaq 5554 MANAMA Bahrain

City: Manama

Country: Bahrain

Phone: +973 1763 6363

Email: H6722@sofitel(.com)

Challenges Encountered

Rate Variability

Nightly rates changed dynamically based on region, date, and availability. Actowiz implemented dynamic selectors and fallback strategies.

Anti-bot Mechanisms

To bypass detection, techniques such as rotating proxies, user-agent randomization, and browser mimicry were used.

Multi-language Support

While the default page was in English, several pages redirected to localized versions. Language settings were standardized across scraping sessions.

Technologies Used

• Scrapy: Framework for large-scale crawling
• Selenium & Puppeteer: For handling JavaScript-heavy hotel pages
• Python Pandas: Data wrangling and formatting
• Google Sheets API: Real-time data uploads
• LinkedIn Search APIs: For General Manager data

Benefits of Hotel Data Scraping

Actowiz Solutions enables clients to:

• Build global hotel directories and comparison platforms
• Track hospitality trends across regions
• Engage hotel decision-makers directly
• Fuel AI-based recommendation engines
• Simplify travel planning and analysis

Why Choose Actowiz Solutions for Hotel Data Scraping?

Actowiz Solutions enables clients to:

• Custom Scraper Development: Tailored scripts per website structure
• Scalable Solutions: From hundreds to millions of records
• Real-time Updates: Schedule-based or API-based scraping
• Data Delivery in Any Format: Excel, CSV, JSON, or direct integrations
• Support for Multiple Countries: Expertise across global hotel platforms

Looking for similar data scraping services?

Get in touch with Actowiz Solutions for a tailored quote and sample data today!

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Conclusion

Hotel data scraping, when done professionally, opens doors to immense business intelligence. Actowiz Solutions delivered a robust and structured dataset of over 6,000 hotels from the Accor Hotels directory, providing everything from contact info to nightly pricing. The data was not only structured into a clean Google Sheet but also enriched with optional executive-level contact info.

If you're looking to extract hotel data at scale, Actowiz Solutions is your ideal data partner. From hospitality to travel tech, we turn raw data into actionable insights.