Airbtics gathers and updates its data with this five-step process.
1. Source the data
Airbtics collects short-term and vacation rental data from dozens of sources, including Airbnb, independent property managers, and rental software providers.
2. Monitor the data on a regular basis
Acquiring rental data is just the beginning. This data is continually tracked, with various information collected and updated at different time points. This allows us to understand specific occupancy rates, pricing strategies, revenue, booking lead time, and guest demographics.
3. Use cutting edge technology to understand the profitability of rentals
We also use machine learning and statistical techniques, such as, binary classifications, natural language processing, time-series analysis, to understand seasonality and revenue. Binary classifications is the practice of classifying elements of a set into two separate groups based on a classification rule. At Airbtics, we use binary classification to find and recognize certain patterns in data, such as how the head to ratio or certain amenities can increase or decrease revenue in specific areas.
Natural language processing (NLP) is the process of using software to automatically manipulate natural language, the way we communicate with each other (speech and text). NLP allows us to take mass amounts of unstructured speech and text data generated every day and efficiently automate the analytics process. We extensively use NLP to analyze listings’ titles, summary and reviews to help identify insights that can make your short-term rental business unique.
The third statistical technique we use at Airbtics to understand the profitability of rentals is time-series analysis, which is a method of “analyzing time series data in order to extract meaningful statistics and other characteristics of the data”. This technique is significant because we use time series analysis to understand historical data and forecast future trends in a way that is helpful for STR investors.
Using the mentioned techniques, we are able to achieve our end goal, which is to understand the underlying factors that make vacation and short-term rentals profitable and bring substantial ROI.
4. Process calendar data
One of the most popular questions we get is: How do we know if the Airbnb calendar is booked vs. blocked by themselves?
Thanks to intensive qualitative research on dozens of Airbnb hosts to understand their common behaviors and patterns, we are able to create precise estimations of calendar availability. And by analyzing calendar data of listings at different periods, we are able to develop a model that can predict the availability of listings.
5. Analyze each market before showing them on our platform
For every region imported into the Airbtics platform, our team validates and ensures the accuracy of the gathered data through thorough research of that region. This is to clean up any data anomalies that come up. If you do not see your region on our dashboard, don’t hesitate to contact us.
The Airbtics data team is always reviewing their data processing models to give you the most accurate portrayal of the STR market.