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Introduction

Introduction

In the hospitality sector, access to structured, up-to-date data is essential for competitor benchmarking, regional market analysis, and strategic expansion. A leading travel intelligence firm approached Actowiz Solutions to extract hotel data from a publicly accessible online directory that spanned 318 unique pages, each containing listings of hotels with varying star ratings and address details.

This case study walks through the technical approach, challenges, and outcomes of this hotel data scraping project, showcasing how Actowiz Solutions delivered a high-quality, fully formatted dataset to meet the client’s analytical and operational needs.

Project Objective

The client needed: - A complete list of hotels from 318 category pages on a specific website - Key fields including: - Hotel Name - Address (including ZIP/postcode if available) - Star Rating (converted to numerical format: 1 star = 1, 2 stars = 2, etc.) - Delivery format: Clean Excel (.xlsx) spreadsheet - Output optimized for import into their internal CRM and analysis tools

This dataset was critical for: - Identifying potential partnerships - Mapping regional hotel density - Conducting pricing and quality benchmarking

Challenges

Although the task seemed straightforward, several technical and data quality challenges emerged:

  • Pagination: 318 separate pages required dynamic pagination handling.
  • Inconsistent data formatting: Some hotel names and addresses were in mixed-case or contained special characters.
  • Missing star ratings: Not all listings had ratings; fallback logic had to be implemented.
  • Data duplication: Some hotels were listed on multiple pages.
  • Export readiness: Ensuring the output matched the Excel format specifications for client-side ingestion.

Actowiz Solutions’ Approach

The-Client

Step 1: Target URL Mapping All 318 pages were crawled using a URL iterator script that indexed each listing page. Custom logic ensured all dynamic loads and filters were bypassed.

Step 2: Hotel Listing Extraction Using Scrapy and BeautifulSoup (Python), Actowiz extracted hotel names and addresses from structured HTML blocks.

Step 3: Star Rating Translation - Star icons or labels (e.g., “5-star hotel”) were parsed. - A conversion function translated visual or textual indicators into numbers. - Listings with no ratings were tagged as “0” for client-side filtering.

Step 4: Data Cleaning - Addresses were cleaned using regex patterns to standardize formats. - UTF-8 encoding was enforced to handle special characters. - Deduplication logic based on fuzzy name + address match ensured accuracy.

Step 5: Excel Formatting & Delivery - Final dataset saved to Excel with columns: - Hotel Name - Address - Star Rating (Numeric) - File passed through automated QA scripts before delivery.

Sample Data Preview

Hotel Name Address Star Rating
Grand Lux Resort 125 Ocean Drive, Miami, FL 5
The Budget Inn 43 King Street, Charleston, SC 2
Lakeside View Hotel 77 Maple Rd, Asheville, NC 4
Southern Comfort Motel 210 Peachtree Blvd, Atlanta, GA 3

Tools & Technologies Used

The-Client
  • Python (Scrapy, BeautifulSoup, Pandas)
  • ExcelWriter (Pandas) for generating spreadsheets
  • FuzzyWuzzy for duplicate detection
  • Requests/Retry Middleware for stable crawling
  • User-Agent Rotation + Proxy Management to avoid throttling

Timeline & Quality Control

The entire project was delivered in 7 business days:

  • Day 1: URL audit, website structure review, pagination planning
  • Day 2–4: Data extraction and rating logic implementation
  • Day 5: Data cleaning, de-duplication
  • Day 6: Excel formatting and validation
  • Day 7: Internal QA and final delivery

QA Protocols: - Sample-based record validation (50 listings) - Star rating verification for edge cases - Address formatting compliance with client CRM

Client Outcome & Impact

4,100+ unique hotel listings extracted across all 318 pages

100% structured dataset ready for upload into the client’s CRM

Enabled targeted partner outreach in high-density hotel regions

Saved 90+ hours of internal labor by automating the scraping task

Post-delivery, the client launched: - A hotel supplier segmentation dashboard - A geo-heatmap visualizing 5-star hotel clusters - A CRM enrichment process tied to newly scraped addresses

Client Feedback

“We were impressed by the precision and speed. The clean Excel output and star rating transformation saved us weeks of internal effort.”

Conclusion

This project exemplifies how Actowiz Solutions can transform public web listings into actionable business datasets. By automating the scraping of 318 hotel listing pages, translating inconsistent rating formats, and delivering the output in a clean Excel structure, the client was empowered with exactly the dataset they needed—without investing internal bandwidth.

Whether you’re a travel startup, OTA platform, or market researcher, Actowiz can scrape and deliver structured hotel data tailored to your location, format, and field needs.

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Our web scraping expertise is relied on by 4,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.

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