Objective data on pedestrian travel has long been lacking, especially pertaining to quantitative information about flows and route choices. Recent ICT development has opened opportunities to collect position-determined data automatically/passively but has rarely been used to study walking behavior. This study analyses the use of two such data sources for pedestrian study. Data was collected in the autumn of 2019 in Umeå, Sweden, where residents (N = 88) in the study area were asked to use the travel survey app (TravelVu) for 5 days. A total of 3,856 trips were recorded of which 51% were walking. A measurement of travel patterns was also carried out with Wi-Fi (Bumbee) for 8 days at 14 points, which recorded 279,791 entries. The results show that what Bumbee loses in precision it makes up for in the number of registrations, while TravelVu provides a detailed picture of an individual’s travels. This pilot study addresses how well the combination of these data types describes pedestrian traffic in an area in terms of flow, route choice, and distribution in time and space. Furthermore, the study provides knowledge on how new data sources can be used to provide municipalities with a picture of their pedestrian traffic.