As the travel industry becomes increasingly competitive, access to accurate, up-to-date hotel data is more critical than ever. Web scraping offers a powerful way to gather this valuable information at scale. However, many travel businesses assume web scraping requires extensive coding skills, putting it out of reach.
The good news is that with the rise of no-code web scraping tools, anyone can collect the hotel data they need – no technical expertise required. In this guide, we‘ll walk you through everything you need to know to build your own hotel data scraper as a non-techie. Let‘s get started!
What is Web Scraping?
First, let‘s clarify what we mean by web scraping. Simply put, web scraping is the process of extracting data from websites. It involves writing an automated program, known as a "scraper" or "crawler", to visit web pages, parse the HTML, and collect specific data points into a structured format like a spreadsheet.
Essentially, web scraping allows you to gather publicly available web data at scale much faster than manual methods. While it has many applications, it‘s particularly useful in the travel industry for aggregating hotel listings, prices, reviews and other details across booking sites and hotel websites.
Why Scrape Hotel Data?
The hotel industry generates a huge amount of valuable but unstructured online data. Web scraping unlocks this data so it can be leveraged in many powerful ways:
Competitor price monitoring – Scrape competitor hotel listings to track price changes and ensure your rates remain competitive.
Review analysis – Collect reviews from across the web to gauge customer sentiment and identify improvement areas.
Occupancy prediction – Analyze historical booking data to forecast demand and optimize pricing.
Lead generation – Gather contact details for hotels to build sales prospect lists.
Aggregating listings – Build comprehensive hotel databases to power booking platforms and travel agency sites.
The applications are nearly endless. With a constant feed of fresh, structured hotel data, travel businesses can make smarter, data-driven decisions to attract more guests and grow revenue.
Hotel Data You Can Scrape
So what specific hotel data points can you collect via web scraping? While the options are only limited by what‘s available publicly online, here are some of the most commonly scraped hotel details:
- Hotel name
- Location (address, city, country, etc.)
- Star rating
- Amenities
- Room types
- Nightly rates
- Review rating
- Number of reviews
- Availability
- Photos
- Contact details
- Geocoordinates
Depending on your needs, you may choose to scrape some or all of these attributes from the major hotel booking sites and aggregators like Booking.com, Expedia, Hotels.com, Kayak, and Tripadvisor, or directly from individual hotel and chain websites.
No-Code Web Scraping Tools
Until recently, building a web scraper required at least some knowledge of programming languages like Python or Javascript. However, a new wave of no-code web scraping tools have made the process accessible to non-technical users.
These tools provide visual, point-and-click interfaces for building scrapers without writing a single line of code. They handle the technical heavy lifting in the background, allowing you to focus on simply specifying what data you want to collect.
Some of the most popular no-code web scraping platforms include:
- ParseHub
- Octoparse
- Mozenda
- Dataminer
- Dexi.io
- Webz.io
- Apify
- Bright Data
These tools vary in terms of features, pricing, performance and complexity. For this guide, we‘ll use ParseHub as an example to demonstrate scraping hotel data, as it offers a generous free plan and an intuitive interface suitable for beginners.
Scraping Hotel Data with ParseHub
To show how easy it is to scrape hotel data without coding, let‘s walk through a real example using ParseHub. We‘ll scrape hotel listings from Booking.com, but the same process applies to any hotel website. Here‘s how to do it:
Create a free ParseHub account and install the desktop app.
Enter the URL of the Booking.com page you want to scrape, e.g. hotels in a specific city.
ParseHub will load the page and display its visual selector tool. Click on the first hotel listing to select it. ParseHub will highlight all the listings on the page, identifying the main repeating element.
Next, hover over and click the name, price, rating, and other details you want to scrape from each listing. ParseHub will extract them into separate columns.
If the data spans multiple pages, simply navigate to the next page. ParseHub will automatically detect and extract data from all the pages.
Finally, click "Get Data" to run the scraper and export your data as a CSV or JSON file.
That‘s it! In just a few clicks, you‘ve scraped structured hotel data without writing any code. ParseHub offers many more advanced features like API access, scheduled runs, and AJAX support, but this basic process is all you need to start collecting hotel data at scale.
Tips for Scraping Hotel Data
As you build your hotel scrapers, keep these tips in mind to get the best results:
Be mindful of website terms of service and robots.txt files that outline scraping permissions. Only collect public data in an ethical manner.
Start small and test your scrapers on a single page before scaling up to hundreds or thousands of pages.
Limit your request rate to avoid overloading servers or getting blocked. Most tools allow you to throttle requests.
Rotate IP addresses and user agents, especially when scraping large sites like Booking.com or Expedia. Many no-code tools include this functionality.
Regularly monitor and maintain your scrapers to handle any website changes that may break them over time.
Complement scraped data with other sources like APIs and manual research to fill in any gaps.
Ensure you comply with data privacy regulations like GDPR when collecting and processing personal data.
With a data-driven mindset and smart use of web scraping, you‘ll be well on your way to a competitive edge in the fast-paced travel market.
Conclusion
Web scraping is a game-changer for gathering hotel data, and it‘s never been more accessible for non-technical users. With the right no-code tool and a bit of setup, you can easily collect the specific hotel details you need from across the web to inform smarter pricing, marketing and sales decisions.
As you embark on your web scraping journey, remember to scrape responsibly, start small, and continually iterate and improve your process. The hotel data is out there – now it‘s up to you to unlock its insights.
To dive deeper into the world of no-code web scraping, check out these additional resources:
- ParseHub documentation and tutorials
- Octoparse blog and academy
- Web Scraping for Non-Programmers (Udemy Course)
- The Web Scraping Handbook by Seppe vanden Broucke
Happy scraping!