Recipe for Building a Widget: How We Helped to “Peak-Shift” Demand by Helping Passengers Understand Travel Trends

This post details the development of the 'Travel Trends Widget' which aims to 'peak-shift' demand by helping passengers understand travel trends. The widget uses historical supply and demand data and machine learning to forecast pricing trends for the next two hours. The development process was agile and collaborative, involving multiple teams. The widget pulls together historical imbalances between supply and demand for the user's current location and nearby time periods, displaying aggregated data visually. The design team drew inspiration from Google's Popular Times and focused on an intuitive tapping gesture for interaction. The data science team worked on deducing historical surge trends and ensuring reliable data storage and access. The widget was developed and released within two weeks, with ongoing iterations based on user feedback.