Data collection methods and poverty measures have not caught up with the reality of an increasingly urbanised world; as a result, urban poverty may be underestimated. This has important implications for targeting interventions and allocating resources in the 2030 Agenda for Sustainable Development. Several problems affect the measurement of urban poverty: definitions of ‘slum’ settlements vary widely, data collection may undercount slum populations, insufficient data disaggregation may conceal intra-city disparities, and common indicators and assumptions may be ill-suited to assessing both income and multidimensional poverty in urban contexts. However, not enough is known about the extent to which these issues affect the resulting estimates. This paper contributes to the existing literature by illustrating the scale of the bias associated with common practices in measuring urban poverty at different stages of the production of poverty estimates. The analysis draws on selected examples in the literature alongside new analysis of data from Demographic and Health Surveys and Household Income and Expenditure Surveys. The article also provides recommendations on how to address each of these problems to improve urban poverty measurement.