This proposal aims to take a critical look at how new technologies used by transit riders can transform transportation. We are interested in the question “What do riders do after they get travel information?” This research project will explore this question using a new “big data” source generated by travelers looking for real-time transit and shared-mobility information through a smartphone application called Transit App, as well as other large scale data sources. As a backend record of mobility software interactions, the Transit App dataset has the potential to demonstrate how real-time travel information can be used to improve transportation evaluation and planning. The app is widely used by consumers to access information on public transit, ride-hailing (e.g., Uber), car-sharing (e.g., Car2Go), and bike-sharing (e.g., Citi Bike). The authors look to explore the potential for continuous measurement tools to augment existing travel survey and operational data and also increase the information that is available to study transitory travel patterns and seasonal variation in demand and supply of transportation services. Analysis of the massive dataset from Transit App will serve as a demonstration for the potential of using emerging data sources from new rider technologies in the future to improve transportation outcomes.