Online retail channels increasingly shape consumers’ purchase behaviour: we access a diversity of product types through web-shops; employ both smartphones and digital screens in stores; navigate the retail space by browsing online; and order pantry items, fresh groceries as well as prepared foods to be delivered at our doorsteps. The profound impact of online retail on mobility in cities, where the concentration of consumers resides, is, therefore, an extensively investigated and growing topic of interest in research. In the field of urban logistics, studies that evaluate the various impacts of e-commerce or propose efficiency or sustainability-enhancing applications are plentiful. Regardless, the general lack of solid urban e-commerce logistics data is supported widely. In this study, we systematically review the literature to identify and compare the types of e-commerce data that are currently known, employed and disclosed in urban logistics research as well as the data sources that provide access to them. Within the set of identified data, knowledge concentrates on consumer preferences and number of deliveries related to e-commerce. However, our findings confirm the general data paucity, specifically on delivery trip-related information such as deliveries per trip, number of delivery rounds and vehicle specificities. Discrepancies are found in methodologies to collect and compile data, as well as data units used (e.g., orders, parcels, deliveries) that cause large variations in information possibly diverging from reality. The study contributes to current literature and practice by compiling and analysing currently available data on urban e-commerce logistics and by presenting recommendations and best practices for future enhancements in this research field. Based on the systematic literature review, we propose a common data agenda for urban e-commerce logistics research, focused on addressing data gaps and topics that are under-developed and un-developed; pursuing data collection standardisation; disclosing data collection methodologies and sources; and specifying temporal and spatial information as well as units of data. Some data methodologies and sources can be recommended for future research: using interviews to collect quantitative data; collaborating with sector organisations; exploring open maps; employing existing household and time use surveys; and leveraging technological opportunities and new ways of collecting data.