Browsing Airbnb listings is the go-to way for finding accommodation anywhere in the world. Here's how to use our Airbnb Scraper to extract Airbnb data on rental offers, including prices, size, reviews, and host details.
Over a decade, Airbnb has become the largest marketplace for renting out local housing in the world. Being a textbook example of the sharing economy, its successful business model has to withstand countless replication attempts, fascination as well as criticism. The hosts like it for convenience and autonomy. The guests like this platform for the flexibility, price offerings, smooth UX, and the sense of infinite wanderlust possibilities (I mean, have you seen their website?).
What is Airbnb all about?
Airbnb doesn’t own any of the listed properties; its business lies in offering a shared space where hosts and guests can easily find each other and work out the technicalities of lodging with the least headache possible. The most common Airbnb listing would be an apartment for two or a single room, but it’s just as easy to come across accommodation offers in a cave, a boathouse, a futuristic orb, or even a castle. Apart from house rentals, you can also find entire packages of guided tours named “Airbnb Experience” which pulls Airbnb into the format of a digital travel agency rather than just a third-party rental service.
But the biggest power of Airbnb has to lie in its filters. The availability of flexible filters gives guests a sense of complete control over how well their lodging experience will go. They can find a perfectly fitting place, whether it’s a room or a villa with a pool, in the city center or off the beaten track, for a short stay or for the whole summer, for one person or rather for a group. They can easily compare prices and weed out the unwelcoming spots by checking the comments for negative experiences. All of these search choices mean a lot of data, data that is openly available and ready to be collected and analyzed for your individual and business needs.
Why scrape Airbnb listings?
Whether you’re on one side of this story trying to find a perfect getaway spot, or on the other wondering whether it would pay off to rent out your place for the upcoming tourist season, scraping Airbnb listings might offer a solution.
It’s not like you can’t just go on the website, copy-paste the fitting information from there, and compare it in some sort of an Excel sheet. But that would take ages and lots of effort. While you’re considering getting an army of professional copy-pasters, here are a few challenges your Airbnb dataset will have to tackle:
- How many available listings are there in my area of interest?
- How can I quickly categorize them by size, price, ease of commute, and special features?
- How do I identify the ones that fit me best - by going through the reviews?
- How do I make sure my data is well organized and doesn’t have mistakes/inaccuracies?
You won’t have to answer any of those if you have a program that will collect and sort that information for you, like our Airbnb Scraper. On the other hand, scraped Airbnb data is just what it is - data. And while the use cases for it vary across the board, a few of them tend to stand out:
- Keep a count of all Airbnb listings from a chosen area.
- Monitor price changes for those listings and prepares for the upcoming tourist season.
- Do your own market research when looking for a perfect place.
- Find emerging trends within the travel industry.
- Take a good look at guest preferences in terms of the price range, housing size, features, available infrastructure, etc.
- Analyze Airbnb comments and identify the most successful locations in town.
- Zoom in on the up-and-coming areas to target new offers for tourists.
- Support your decision-making with data when opening/visiting a new spot away from the most popular touristic paths.
Those are just a few examples of how to apply scraped Airbnb data. You'll definitely think of it even more once you download your first dataset.
What about Airbnb API?
Unfortunately, to this day, Airbnb doesn’t provide any public API. If you’re curious about what is an API and why it’s an important term for web scraping, just head over to the blog post.
However, not to discourage you, but Airbnb has developed a pretty strong defense strategy against scrapers, including browser fingerprinting, IP tracking, and other rather unpleasant measures. You can read more about what techniques websites use to rebuff scrapers, but usually, that only means that your scraper will have to be extra swift and resilient to be successful - use proxies, for example.
So why reinvent the wheel when there’s a free all-inclusive solution created for you already - our Airbnb Scraper. It will scrape the Airbnb listings data from any city within minutes and include all the reviews, prices, and host/guest details to your request. Here’s how to set it up on our platform in 7 simple steps.
Step-by-step guide to scraping Airbnb data (no coding required)
Find your actor in Apify Store
1. Head over to the Airbnb Scraper page and click the green Try for free button.
2. If you don’t have an Apify account yet, you’ll land on the sign-up page first. You can sign in using your email, Gmail, or GitHub account.
3. Now you’re out of Apify Store and in your web scraping workspace - Apify Console. This is where you’ll run tasks for your scrapers. The scraper won’t start running until you set it up with your scraping request.
4. Let’s try and scrape the Airbnb rental listings available in New York City, shall we? You can expect the scraper to get all the details, including prices, reviews, ratings, number of guests, and other guest/host details for those places. In order to do that, simply type New York into the Location field. Usually, that would be enough for the scraper to do its job, but you can add extra parameters as well such as price range, date range, number of reviews, etc.
5. Once you’ve figured out the input, Click the orange Start button. Your task will change its status to Running, so wait for the scraper's run to finish. It will be just a minute before you see the status switch to Succeeded. You can see the search got us the first 10 results. We’ve limited the number of results to 10 on purpose this time, but in general, the scraper won’t stop running until it gets all the data it’s been set up for.
6. Now you can move to the Dataset tab to preview or download the results. The Dataset tab contains your scraped data that can be downloaded in many formats: HTML table, JSON, CSV, Excel, XML, and RSS feed. Preview the data by clicking the Preview 👁 button or View in a new tab ⤴️, if the dataset is too large (as might be the case for an average Airbnb dataset).
7. Now you can easily download the scraped data onto your computer to further use it as a spreadsheet, incorporate it into other apps, or further process it for your Airbnb data analysis projects.
Now that you know how to scrape Airbnb, you can surely play around with the input parameters and see just how much data you can get in so little time. Feel free to share your results with us or check out other travel industry scrapers 🌴🧳