What is AirBnB Rental Data? Definition, Sources & Datasets to buy

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Eugenio Caterino
Editor & Data Industry Expert

What is Airbnb Data?

Airbnb data is information collected and stored by Airbnb, a popular online marketplace for lodging and vacation rentals. This data includes details about the properties listed on the platform, such as location, amenities, availability, and pricing. It also encompasses user information, such as guest reviews, host profiles, and booking history. Airbnb uses this data to facilitate bookings, improve user experience, and make informed business decisions.
Examples of Airbnb data include information about listings, bookings, reviews, host profiles, and pricing. Airbnb data is used for various purposes such as market analysis, property investment decisions, pricing strategies, and research on the sharing economy. In this page, you’ll find the best data sources for accessing and analyzing Airbnb data, including options for downloading historical datasets or purchasing specific subsets of Airbnb data.

Best Airbnb Datasets & APIs

4.8(4)
Available Pricing:
One-off purchase
Monthly License
Yearly License
Usage-based
revenue share
Pricing available upon request
Free sample preview
5.0(1)
Pricing available upon request
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Airbnb data for research purpose

Available for 249 countries
10 years of historical data
Pricing available upon request
Free sample preview
Starts at
$7 / 10,000 records
Free sample preview
Starts at
$30 / purchase
Pricing available upon request
Free sample preview
Pricing available upon request
Free sample preview
Starts at
$30 / purchase
Pricing available upon request

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Top Airbnb Data Providers

When choosing Airbnb data providers, consider factors such as the accuracy and reliability of their data, coverage of geographical areas, frequency of updates, availability of historical data, data format compatibility, and compliance with privacy regulations.

Airbnb Data Use Cases

Airbnb Data Explained

How is AirBnB Data collected?

AirBnB collects data when users visit the website. It provides analytics on location interest as well as stay durations by documenting a property’s booking history. This gives a clear report of consumers’ interests and rental trends.

Consumer input is also important for AirBnB data collection. User-generated content like reviews and photos provide property data from a consumer perspective.

AirBnB market data provides insights on the short-term rental industry in general. Real estate market data is collected both by web scraping and compiling property report from a given area.

What are the attributes of AirBnB Data?

There are many different aspects to AirBnB data from both the consumer and host side of the operation.

Consumer-side data
This can include user-generated content like reviews and experiences shared in forums. More basic data includes average duration rate.

Host-side data
This includes property availabilities, property size and features as well as nightly rates. AirBnB data can also be refined to show data for a specific country or area to ensure that your property is actively competing against.

The best way to understand the attributes included in an AirBnB dataset is to ask for a data sample.

What is AirBnB Data used for?

AirBnB data is used by property owners and businesses to maximize their profitability. You can see which areas and property types are the most successful to ensure that your AirBnBs keep up in the busy market. This data can be useful for established renters or people looking to get started in the market.

For example, nightly rate data can show how your costs compare to those of properties around you. Likewise, reviews tell you what consumers are looking for, as well the local demand for AirBnBs. Businesses buy AirBnB data to see which areas gain the most interest and consumer footfall. From here, they can tailor their services to the visitors’ needs.

How is AirBnB Data used?

In practice, AirBnB data has a range of applications. One of the most frequent use cases is investment and market research. AirBnB investors use external datasets for real estate market analysis. With AirBnB data analysis, they can invest in a property which gives them the best ROI as a short-term rental home.

There are two stages in real estate market analysis: location research and property research. Location research is where the investor scouts out an area, like a given town or city. They aim to understand its demography, local amenities, transport connections and tourist attractions. These factors all play into how lucrative renting an AirBnB is. In the end, location research allows them to select an area which will make the most rental profit.

The second stage is property analysis. Here, an AirBnB database comes into its own. It shows the user details about individual properties. For example, recent sale price, energy efficiency, and occupancy rate.

Other users download AirBnB to make financial calculations. These include:

AirBnB Monthly Rental Income
Any AirBnB business needs to know how much potential income a property can generate. An AirBnB dataset ensures users balance cost vs revenue by showing investors and property owners monthly income.

AirBnB Cash on Cash Return
Cash on cash return is a way of measuring a property’s ROI. It considers debt and financing options to calculate profit from the AirBnB post-purchase.

AirBnB Cap rate
Another metric real estate investors use to determine property profitability is cap rate. Most AirBnB datasets include cap rate calculations as a data attribute. Cap rate = net operating income divided by current market value. Real estate investors know that the higher the cap rate, the higher the investment risk. So it’s an important metric for making decisions about AirBnB investing.

How can a user assess the quality of AirBnB Data?

It’s important to ensure that any AirBnB dataset you choose is up to date. This is because the short-term rental market, especially the AirBnB sphere, is constantly evolving. Always make sure to check the data provider’s reviews before buying AirBnB data. Lastly, consult a data sample before buying to ensure that the database matches your business’ needs.

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