In this portfolio project, I wanted to gain insights into user behaviors pre-and-post acquisition of Ford GoBike by Lyft Baywheels. The Lyft BayWheels product is their latest initiative that provides rental bikes all across San Francisco through the Lyft app. I dove into the data & utilized SQL to clean & merge the data from 3 datasets:
- the old Ford GoBike dataset
- the new Lyft Baywheels dataset
- the San Fransisco weather dataset
With the datasets cleaned & merged, I imported the data into Tableau to create some data visualizations that helped me identify patterns in user behavior. Using these visualizations, I drew meaningful insights that informed the creation of two user personas for Lyft Baywheels.
These personas allowed me to gain a deeper understanding of the users from both Ford GoBike and Lyft Baywheels, and helped me make more informed decisions when it came to marketing and user acquisition strategies.
This project was a great showcase of my skills in data cleaning, merging, and visualization, all of which were accomplished using SQL and Tableau. Through these tools, I was able to effectively analyze complex datasets and extract valuable insights that helped drive marketing decisions that align with the goals & interests of Lyft Baywheels’ audience segments. Overall, this project demonstrates how data-driven insights can be used to create effective marketing strategies & optimize business performance.