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I chose Austin for this analysis because my brother lived there for four years and I didn’t get the chance to visit him. He loved the city so much that no one could resist the urge to go there after listening to him. Unfortunately, I’ll have to settle with this analysis..., but not for long.
I used two files obtained from Inside Airbnb: 1) listings, which has a vast number of variables from every available Airbnb rental in Austin, and 2) calendar, which is a sales-oriented dataset showing reservations and prices. Important: By the time of this analysis, listing dataset includes data as of Jun 2023, and calendar dataset from Jun 2023 to Jun 2024.
Data Cleaning in Excel was done focusing primarily on data related to location, type of rental, price, occupancy, sales, and time. Additionally, detected outliers were removed and all necessary calculations were made in Tableau.
Due to the vast amount of information available, the analysis was structured in three categories: Rentals, Price, and Sales, so that the data could be presented efficiently.
For Properties and Price, the two analyses that proved to be the most suitable were: map distribution views and the count distribution. For Sales, I chose a calendar view because seasoning is extremely important in this type of business.
The design follows the same idea of the three categories: Rentals, Price, and Sales, transforming the dashboard into a 3-in-1 interactive report to maximize user experience. The color palette is in line with the Airbnb logo, and some design elements were also included, like the Texas map highlighting Austin.
Rentals
Price
Sales
The high number of Entire Home/Apartment rentals with availability under seven days indicates that owners typically live in the property and offer them during particular periods/days of the year. This is a great opportunity for promoting the house-swapping feature in Austin by targeting these owners with special offers/connections for long weekends or summer/winter vacations.
Considering the high volume of Entire Homes/Apartments rentals, it would be advisable to analyze tendencies related to amenities.