Retailers evaluating new locations face a complex multi-variable decision that, when approached with incomplete market intelligence, leads to underperforming stores and costly expansion mistakes. This use case leverages BigGeo's geospatial platform to combine demographic profiles, consumer spending behavior, pedestrian and vehicular traffic patterns, competitor proximity, workforce availability, and nearby points of interest to score and rank candidate sites. Analysts can compare multiple potential locations side-by-side within a unified spatial environment, identifying trade areas, estimating revenue potential, and flagging cannibalization risk before committing capital. The result is a data-driven site selection process that dramatically improves the probability of long-term store success and reduces the number of costly site closures driven by poor location choices.

Organizations deploying electric vehicle (EV) charging infrastructure struggle to identify where new chargers will have the greatest impact. This use case combines EV ownership rates, road traffic flows, existing charging station locations, population growth projections, and commercial activity density to pinpoint underserved regions where demand is likely to outpace supply. By layering geospatial analysis across these signals, planners can prioritize deployment locations that maximize charger utilization, reduce range anxiety for drivers, and improve equitable access across urban, suburban, and rural corridors. The output supports capital allocation decisions, permitting prioritization, and partnership strategies with property owners, utilities, and municipalities.