Audits of neighborhood characteristics offer opportunities to study the mechanisms that link neighborhood conditions to unequal outcomes for individuals and communities, but the expense and logistical difficulties associated with conducting neighborhood audits has limited their use. The images collected by Google Street View promise to help researchers measure neighborhood environments across cities and to examine the variation in neighborhood conditions and effects across a much wider geographic scope than current studies. We describe the promise of using "virtual" neighborhood audits and discuss the practicalities of collecting data from virtual audits. We provide an example examining individual- and neighborhood-level inequality in the distribution of disorder for older adults across four cities: New York, San Jose, Philadelphia, and Detroit. Despite the promise of virtual audits, the opportunities afforded by this new data source introduce new perils that must be addressed as research progresses.