How to scrape Airbnb data

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 rental data 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. But, when you look at this data in a wider context, you’re going to find patterns in your results, which will help you find out more about your customers, a specific market segment, or ongoing trends.

Is it legal to scrape Airbnb?

It is legal to scrape data that is publicly visible on the web. But there still are some regulations you need to adhere to, especially when it comes to web scraping information that might be protected by copyright or could contain personal data. These include the European GDPR or American CCPA for personal data and the DSM Directive in the EU or fair use doctrine in the US.

What are the use cases for scraped Airbnb data?

Now let’s get back to the reasons why you’d want to scrape Airbnb data. While the use cases 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 rental 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. Their official API is only offered to selected partners, and, given that they don’t currently accept new requests, you’re most likely not going to get access to it.

Now, there’s tons of information out there on how to make your own Airbnb scraper using Python, JavaScript, or any other popular programming language. Making a custom web scraper is a doable project and you can try creating one of your own here as well; in fact, we’ll teach you how to do that, for free.

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 rental 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 4 simple steps.

Step-by-step guide to scraping Airbnb data (no coding required)

Step 1. Find Airbnb Scraper on Apify Store

Visit the Airbnb Scraper page on Apify Store and click on Try for free. If you’re not signed in to Apify Console, you will need to create an account, which can also be done via Google or GitHub to speed up the process.

Step 2. Choose the data you want to scrape

Let’s try and scrape the Airbnb rental listings available in Sacramento. 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 Sacramento, California 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, and lots more.

Step 3. Run the scraper

Once you’ve figured out the input, Click the green 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 30 results. We’ve limited the number of results to 30 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.

Step 4. Download your Airbnb data

While you can see an overview of your results in the Output tab, to get the complete data, go to the Storage tab. Here, you can download your dataset in a myriad of 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). You can also 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 data, 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 🌴🧳