Currently, information from the Airbnb platform is invaluable in providing insight into vacation rental market trends, real estate market opportunities, and consumer preferences. However, there are technical difficulties that make scraping the platform’s data a challenge. Discover how to scrape Airbnb data, and make the most of information from one of the world’s most popular rental platforms.
Airbnb is an online platform that allows people to book accommodations with hosts who list their properties. It is one of the most popular vacation rental platforms in the world and operates in 191 countries.
It was founded in 2008 by Brian Chesky, Joe Gebbia and Nathan Blecharczyk. The name “Airbnb” is a combination of the words “air” and “bnb” (bed and breakfast). It was born when two designers with spare space in their home decided to make it available to three travelers looking for a place to stay.
Among the distinguishing features of the Airbnb platform are
- It allows you to search and book accommodations based on location, dates and budget. It is designed for leisure, vacation and business travel.
- It offers unique experiences and activities such as tours, cooking classes, and more.
- Hosts can list their properties and manage reservations quickly and easily.
- Guests can leave reviews and comments about their experiences, making the service more transparent.
There are currently more than 5 million Airbnb hosts worldwide and more than 7.7 million active listings on the platform. Airbnb listings are available in more than 100,000 cities worldwide. At the same time, Airbnb has more than 150 million users worldwide who have booked more than 1.5 billion stays.
In fact, by 2024, more than 490 million nights and experiences will have been booked on Airbnb worldwide, resulting in more than $11 billion in Airbnb revenue. Airbnb’s current valuation is approximately $113 billion, and it is estimated that Airbnb currently has over 20% market share in the vacation rental sector.
Why Scrape Airbnb Data: Opportunities and Limitations
There is no doubt that Airbnb’s data is invaluable because it provides a detailed and multifaceted view of the vacation rental market, allowing individuals and businesses to make more informed decisions, identify opportunities, and better understand the dynamics of this market. From analyzing price trends to occupancy rates and popular locations, this information allows businesses to stay ahead of the competition.
The ability to access a wealth of public data through web scraping, given the platform’s lack of a public API, further enhances the value of this information. In addition, the Airbnb API typically only provides the first 300 results on the site and limits the API to 1,000 results.
Unfortunately, as of today, Airbnb does not offer a public API. Their official API is only available to select partners, and since they are not currently accepting new requests, it is highly likely that you, as a regular user, will not have access to it. This brings us back to web scraping and other mass collection methods, a necessary technique for obtaining additional data.
Among the risks of scraping the platform, Airbnb implements measures to prevent automated scraping, such as blocking IP addresses and using CAPTCHAs. However, rotating proxies can be used to mitigate this risk.
According to the use cases for the data to be collected, it is important to mention: -Monitoring prices and market trends.
- Competitor research.
- Identifying guest preferences (price, size, amenities).
- Analyzing reviews to identify successful locations.
- Support decision making for new tourism offerings.
- Count the total number of listings in an area.
- Identify emerging trends in the travel industry.
- Airbnb data image simulated with Gemini
How to scrape Airbnb data
Among the possible methods available, beyond the limitation of not having a public API, the following stand out:
- Pre-built Scrapers: Currently, Apify is promoting an Airbnb scraper as a “free” and “all-inclusive” solution that works as an API. It describes a 5-step process for using it, from finding it in the store to downloading the data in various formats.
- Python Programming Libraries: For those who want to extract data from Airbnb despite the risks and the possibility of being blocked, Python remains the language of choice thanks to its rich ecosystem of web scraping libraries. In this context, it will be necessary to use some essential libraries such as BeautifulSoup, Requests, and Selenium, as they can parse HTML/XML and handle complex tasks efficiently. All of this is taken into account for sites that use a lot of JavaScript, such as Airbnb.
- APIs and Third-Party Services: Using professional third-party solutions will help streamline and simplify the process of collecting massive amounts of data from any dynamic rental and real estate data platform, not just Airbnb. In this sense, with Scraping Pros, you can count on an excellent web data extraction service with proven experience in managing scalable, flexible and customizable data solutions for your business or company, including the common scraping challenges of sites with technical limitations.
- Custom Scraping : If none of these options appeals to you, creating your own scraper using languages such as Python or JavaScript is a viable option. However, the downside is that it requires significant technical, programming, and application security skills.
Challenges of Data Scraping on Airbnb
The main technical challenges of extracting data from the popular vacation rental platform are worth mentioning:
- Dynamic content: In the presence of dynamic content on the platform, JavaScript rendering techniques or headless browsers such as Puppeteer or Selenium can be used. At the same time, it is recommended to monitor network traffic to identify API endpoints and implement delay strategies to avoid detection.
- Pagination: It is important to mention the need to manage pagination to extract data from multiple pages, taking into account URL structure analysis and the use of query parameters and loops.
- IP Blocking and Rate Limiting: IPBurger’s Rotary Proxies solution is a clear alternative to avoid any IP blocking or rate limiting imposed by Airbnb, highlighting its vast IP pool, reliability, speed and geographic diversity.
At the same time, these practices should carefully consider the legal and ethical aspects of web scraping, such as applicable privacy, copyright, and terms of service regulations. It’s also important to respect fair use and protect user privacy and data integrity.
While extracting public data is generally legal, organizations need to be mindful of data privacy laws. With regulations such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States, protecting personal data is a priority.
Final Thoughts
There is no doubt that the business opportunities presented by web scraping are enormous and allow your company to make informed decisions.
In the case of Airbnb, one of the world’s leading rental platforms, this means access to a wealth of public data (including reviews, prices, locations and property features), potentially more data than a limited API (beyond the 1,000 maximum results and including all available listings), flexibility and customization (configuring parameters to tailor data searches to business needs) and detailed platform analytics, as the collected data can be used for a variety of purposes, such as maintaining an inventory of all listings, monitoring price changes, conducting market research, identifying emerging trends, analyzing guest preferences, and evaluating successful locations.
If you found this topic interesting and valuable to your business goals, we invite you to share this post with other professionals and executives, evaluate the possibility of implementing web scraping in your company, or schedule a call with the Scraping Pros team of experts.
