Demands for ride-sharing services in urban areas are sometimes remarkably high at a particular time of day. The high requests would result in longer waiting times, and more cancellations might occur. Cancellations in ride-sharing services are problematic; it means a bad user experience, and the company would lose revenue potential.
Application owners can anticipate this by using their users’ location data to create clusters to identify when and where the demand was usually high. A strategy can then be devised to position available drivers in a specific location at a particular time of day to reduce cancellations and increase customer trust and satisfaction.
This 3-day online workshop is a beginner-friendly introduction to customer demand analysis using DBSCAN. In this session, we will analyze demands from ride-sharing application data using an underrated clustering algorithm. Throughout the online course, we will provide you with hands-on examples and a rich interactive experience. One Instructor and two Teaching Assistants will help participants troubleshoot or help with any difficulties encountered.
NOTE: This workshop will be delivered in Bahasa Indonesia.