Understanding the travel behaviors of individuals who use public transit is essential for enhancing the performance, sustainability and efficiency of public transportation. Contemporary methods for collecting data on transportation behavior are focused on manual or automated procedures for counting the number of individual passengers entering or exiting transit vehicles. While such methods provide useful data for understanding transit demand throughout a network, they ignore the important details of how passengers travel to and within a network as well as their personal experiences during their commute, all of which can enrich the ability of transit agencies to provide sustainable transportation. To address this issue, there has been a proliferation of location-based services (LBS) that allow for new methods of data collection involving passengers volunteering data about their commute. In this light, passengers engage in a crowdsourcing effort to generate data about experiences across the network. This project’s objective is to implement and test specific LBS in a bus transit network to better understand their potential and limitations for improving the crowdsourcing of travel behavior data.