There are 43 Pokémoto locations in the United States of America as of December 01, 2025. The state or territory with the most Pokémoto locations is Connecticut, with 14 sites, accounting for roughly 32.6% of the total.


Pokémoto operates 43 United States of America locations across 15 states. Largest clusters are in Connecticut, Massachusetts, and Florida; the top 10 states contain 88.4% of sites. Coverage is thinner in Pennsylvania, Rhode Island, and Tennessee.

Pokémoto shows strong visitor engagement: 17 locations are above the mean traffic score (mean: 51.51) and 3 qualify as highly visited.
Pokémoto operates 43 locations across the United States, with Connecticut leading at 14 locations, representing 32.6% of the total. The top three states—Connecticut, Massachusetts, and Florida—account for 55.8% of all locations. Connecticut offers the best access, with one location per 257,951 people, while Texas and California are the most stretched, each serving over 13 million people per location. The top ten states cover 88.4% of Pokémoto's locations nationwide.
Locations concentrate around major metros such as New Haven, Fairfield, New London, Bristol, and Sedgwick. The top 10 cities account for 58.1% of U.S. sites.

Pokémoto has a total of 43 locations in the United States, with the top 10 cities accounting for 58.1% of these. New Haven, Connecticut leads with 5 locations, followed by Fairfield, Connecticut with 4. Several cities, including New London (CT), Bristol (MA), and Sedgwick (KS), each have 3 locations. The remaining top cities have between 1 and 2 locations.
Street-level clusters show corridors where multiple Pokémoto locations sit within the same neighborhood indicating strong local presence and coherence. Pokémoto operates a total of 43 nationwide.

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

Pokémoto has 43 locations across the United States of America. The key variables shows the most infleuntial aspects for Pokémoto locations nationwide. This provides a closer look of how Pokémoto is operating from different prespectives.

Pokémoto's data for the United States shows Texas as the largest state by land area at 695,668 km², while Connecticut is the smallest at 14,358 km². Connecticut also has the highest location count with 14, followed by Massachusetts with 6. Despite their smaller sizes, these states have more locations compared to larger states like California and Kansas, each with only 3 locations.

Pokémoto has a total of 38 locations across ten states in the United States, all of which are currently open with no closures. Connecticut leads with 14 open locations, followed by Massachusetts with six and Florida with four. Each state listed maintains a 100% open business status, indicating full operational presence.
This view compares activity near Pokémoto locations across states. Using traffic scores observed around 43 sites, it highlights the busiest markets, states with a high share of above-average locations, and areas where activity is comparatively light. Use it to benchmark performance, prioritize field operations, and spot expansion or optimization opportunities.

Pokémoto's busiest locations in the United States show New York and South Carolina leading with 50% of their stores marked as busy, each having 1 busy location out of 2 total. California and Kansas follow with 33.3% busy stores, while Connecticut has the highest number of busy locations at 3, representing 21.4% of its 14 total stores. States like Mississippi, Rhode Island, and Texas reported no busy locations.
This section summarizes customer sentiment toward Pokémoto. Using ratings and review totals from 43 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.

Pokémoto's highest average ratings in the United States are in Florida and New York, both at 4.8, followed by Rhode Island with 4.7. California and Kansas have average ratings of 4.6. Connecticut leads in review volume with 2,096, while New York and Florida also have substantial numbers of 1,104 and 1,011 reviews respectively.
Pokémoto's highest average ratings in the United States are found in Florida and New York, both at 4.8, followed by Rhode Island at 4.7. Connecticut leads in total reviews with 2,096, more than double New York's 1,104 reviews. Florida and Massachusetts also have significant review counts, with 1,011 and 969 respectively. Kansas appears in both top lists, with a 4.6 average rating and 390 reviews.

Pokémoto achieved full phone coverage in all listed states across the United States, with each state showing 100% coverage. Connecticut had the highest number of phones covered at 14, followed by Massachusetts with 6 and Florida with 4. Several states, including Mississippi and Rhode Island, had only one phone covered each. This indicates consistent complete coverage regardless of the total number of phones per state.
Pokémoto 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.