Author: BnB Facts

This analysis uses natural language processing (NLP) to explore guest reviews on Airbnb. It looks at the distribution of positive and negative reviews on the platform and what are some of the leading causes of bad reviews.

Machine learning uncovered 9 segments of Airbnb hosts. Understanding these segments will give hosts a sense of the competitive landscape on the platform – i.e., who hosts are competing with for business. It also demonstrates which hosts drive the most value for Airbnb and helps to explain their marketing, program and policy choices.

This analysis looks identifies factors that influence the cleanliness rating on Airbnb. Factors explore include the size of the listing, the number of properties managed by the host and the minimum nights requirement.

Do Airbnb hosts stay with you Do Airbnb hosts stay with you depends on the type of room. In an entire house, the host will not stay with you. If the Airbnb is a private room, the host will stay in the same home while the guest is there, but the guest will have their […]

This analysis looks at if a higher cleaning fee leads to a cleaner Airbnb listing. It also looks at if the cleaning fee impacts the guest’s perception of value.

This analysis looks at how including or not including certain amenities impacts the overall rating and category ratings on Airbnb.

This analysis looks at the relationship between number of amenities listed and overall rating.

Instant Book is a feature on Airbnb that allows hosts to accept booking requests without approval. In this analysis we’ll look at how many hosts use it, the benefits of using it and the impact it has on reviews.

On Airbnb, hosts set house rules on their profile to set expectations for guests. Policies on smoking, pets and parties appear as default house rules. This analysis uncovers other popular house rules.

The listing name is the first thing a guest sees. Hosts try to make the title catchy and attention-grabbing but this leads many to using the same descriptive words. In this analysis, we’ll use text mining to find the most frequently used adjectives used in Airbnb listing names.