Google Maps Sampling Frames

Organizational researchers use a variety of methods to obtain sampling frames. The utility of these methods, however, is constrained by access restrictions, limited coverage, prohibitive costs, and cumbersome formats. This project provides a new method for generating sampling frames for any type of organization that is cost-effective, uses publicly available data, and produces near-comprehensive sampling frames for any geographic area in the U.S. The

Python-based program we developed systematically scans the Google Maps platform to identify organizations of interest and retrieve their contact information. We demonstrate the program’s viability and utility by generating a sampling frame of religious congregations in the U.S.

To assess Google Maps’ coverage and representativeness of such congregations, we examined two nationally representative samples of congregations and a census of every congregation in Indianapolis. We found that Google Maps contains approximately 98% of those congregations––near-complete coverage that ensures a near-perfect degree of representativeness.

Using Google Maps to generate sampling frames promises to substantially improve the process for obtaining representative samples for organizational studies by reducing costs, increasing efficiency, and providing greater coverage and representativeness.