There are 204 BoaVida Communities locations in the United States of America as of January 26, 2026. The state or territory with the most BoaVida Communities locations is California, with 80 sites, accounting for roughly 39.2% of the total.


BoaVida Communities operates 204 United States of America locations across 31 states. Largest clusters are in California, Oregon, and Nevada; the top 10 states contain 79.4% of sites. Coverage is thinner in Pennsylvania, Texas, and Wyoming.

Locations concentrate around major metros such as Butte, Riverside, Shasta, Tulare, and Fresno. The top 10 cities account for 27.5% of U.S. sites.

Street-level clusters show corridors where multiple BoaVida Communities locations sit within the same neighborhood indicating strong local presence and coherence. BoaVida Communities operates a total of 204 nationwide.

The complete dataset of BoaVida Communities locations across the United States of America is available for download, including coordinates, traffic patterns, and operational status.

BoaVida Communities has 204 locations across the United States of America. The key variables shows the most infleuntial aspects for BoaVida Communities locations nationwide. This provides a closer look of how BoaVida Communities is operating from different prespectives.

The table summarizes land area for the top states by location count.

This section summarizes customer sentiment toward BoaVida Communities. Using ratings and review totals from 204 locations, we highlight where scores are consistently high and where feedback volume is greatest. Average star ratings reflect perceived quality, while total reviews indicate engagement and reach across the network.


BoaVida Communities POI data enables clear measurement of footprint and demand. Analysts can rank states and cities by location count, compare coverage on a per-capita basis, and use traffic scores and review volumes to spot high-performing markets and under-served pockets. The result is an objective view of saturation, growth opportunities, and performance outliers.
For network planning, the data supports scoring candidate trade areas using location density, population per location, and nearby traffic intensity. Teams can evaluate cannibalization risk via nearest-store distance, surface whitespace along key corridors, and prioritize sites near retail anchors, campuses, or transit where observed activity is strongest.
Planners can map clusters and service gaps to understand commercial access at the neighborhood level. Per-capita coverage highlights communities with limited access, while changes in openings or closures signal shifts in activity. These insights inform corridor revitalization, streetscape and transit planning, and data-driven zoning decisions.