Motivation Behind the Project:
I’ve always been curious about how people make decisions around travel, especially when price, location, and experience collide. With this project, I wanted to explore how booking behavior and listing traits could reveal meaningful patterns that marketers can use to segment audiences, personalize messaging, and better time campaigns.
What I Did:
Analyzed over 40,000 Airbnb listings in NYC to uncover pricing and listing trends across neighborhoods and room types
Identified key patterns that reflect user intent and value perception, such as demand for private rooms vs. full apartments
Mapped neighborhood-level price ranges and user behavior to uncover segmentation and re-engagement opportunities
Developed marketing-aligned insights to support lifecycle messaging strategy and campaign timing