<p>Administrative units such as constituencies or municipalities are commonly used as the level of analysis for studying aggregated election results. This is primarily due to the availability of sociodemographic data at these levels, while smaller units such as electoral precincts often lack relevant structural information. However, administrative units are usually too large to adequately capture micro-level spatial variations that may influence voting behavior. In recent years, statistical offices have started publishing sociodemographic information at the level of grid cells, often with resolutions as fine as 100 by 100&#xa0;m. This paper proposes using grid cell data as a useful level of analysis for studying many spatial effects on election results. Grid cells enable researchers to detect spatial variation in voting behavior that results from proximity to specific local features such as airports, roads, or transit infrastructure. Two case studies are used to illustrate the use of grid cells in electoral research: a 2017 referendum on the continued operation of the Tegel airport in Berlin and a 2021 referendum on a car-free city center in Halle. The results demonstrate the usefulness of grid cells for electoral analyses and underscore the need to move below the precinct level.</p>