How can we analyze our “big data” to understand HSR customers’ experiences of the reliability of our transit service?
Project Description: HSR has invested in a suite of real-time, trip-planning tools to help customers plan their travel (mobile app, online, SMS text, and phone). Yet HSR customers have told us that reliability is the most important factor in their decision to use transit, and is currently one of the main drivers of dissatisfaction, meaning they don’t think our information is reliable enough. We want to understand why this is the case.
We want to evaluate the accuracy of these tools to the real-life experiences of our customers. How do they perceive the accuracy? How do our tools compare to third-party tools on the market like Google and Transit App? How can we crunch the prediction data against the bus location data to understand how reliable we are in real life?
Are there specific times of day, specific routes, specific geographies, specific traffic conditions that are creating disconnects between the estimated trip times and the actual experiences of customers? How could the accuracy and reliability be improved? Can we “audit” the experience and/or data feed over time to plot the reliability to come up with a score? We don’t have the expertise to develop the algorithm or analysis framework. We don’t have the computing expertise to crunch the “big data” to generate reports.
City Staff: Jay Adams, Senior Project Manager, Customer Experience, HSR Transit, City of Hamilton
Deliverables: Primary Research (i.e. analyzing demographics, engaging directly with the community), Prototype, Design, Marketing Report, App or Game Development
Project Start Date/ Availability: Fall 2021 (September - December)
Location: City-Wide
City Strategy Priority: Economic Prosperity & Growth, Clean & Green, Build Environment & Infrastructure
