Uber Data Exploration
Analyzing and visualizing the data from Uber drives in New York City.
This short project was developed as part of a Marketing Analytics course at MIT Sloan.
We designed a dashboard that can be useful for Uber managers to analyze and visualize the data from Uber drives in New York City. The dashboard provides insights into hourly rides, average tips, wait times, driver pay, and shared-ride coordination. The data-driven approach ensures that managerial decisions are well-informed and strategically sound.
Estimated Drives Next Month This first section predicts the hourly rides for the upcoming month, enabling managers to predict demand fluctuations and allocate resources effectively. The map visualizes the estimated hourly drives across NYC boroughs, with Manhattan exhibiting the highest demand. Monitoring other boroughs for potential demand shifts can inform targeted marketing strategies.
Average Tip per Minute Driven The Average Tip per Minute Driven plot assesses tips across various trip durations and boroughs, segmented further by airport and non-airport trips. Data reveals that airport trips typically yield higher tips, particularly for shorter distances. This insight is pivotal for refining pricing strategies and driver incentives.
Average Wait Time by Hour This metric is critical for customer satisfaction and competitive positioning. The dashboard displays wait times by hour and day of the week, pinpointing peak periods during commuting hours and late-night. Strategies to optimize driver deployment during these times are crucial for reducing wait times and improving service quality.
Driver Pay by Day of the Week Analyzing driver pay by day and hour offers insights into earnings patterns, which are vital for motivating drivers and understanding their compensation trends. The data highlights Newark and JFK airports as lucrative zones, especially on Sundays and late nights.
Ratio of Matched Shared-Rides by Day and Hour The effectiveness of shared ride coordination is gauged through the Ratio of Matched Shared-Rides. This metric highlights successful areas like the Lower East Side and Alphabet City, where high match ratios indicate efficient shared ride implementations.
In conclusion, this Uber NYC Dashboard provides insights that help enhance customer experiences and driver satisfaction. The data-driven approach ensures that managerial decisions are well-informed and strategically sound.