Use traffic, attention, and walk-in conversion to decide on expansion
Two AI cameras proved a real estate storefront was driving walk-ins, and the validated data turned a single test location into a committed six-location signage rollout.
Locations committed to signage rollout after data validation
Measured data-stream uptime during the pilot
No way to measure what the storefront was actually doing
MiNORASU is a real estate agency in central Tokyo with no way to measure what its storefront was actually doing. There was no proof the signage was working and no data to base an expansion on. Store visits were assumed to follow from the display, but nothing tied specific content to actual walk-ins, so any decision to roll signage out to more locations rested on impression rather than evidence.
Two cameras measured attention and walk-in conversion per display
SpaceVision deployed two AI cameras covering the full storefront and all promotional displays. The setup measures pedestrian traffic, attention rate, and walk-in conversion per display and per time window, running on-device with no personal data stored. It gives an anonymous, continuous read of who passes, who stops, and who comes in, GDPR-aligned by design.
Validated performance turned one test store into a six-store rollout
Traffic, attention, and walk-in conversion increased after the signage installation. The data stream maintained 99.9% uptime. MiNORASU used the operating data to expand from one test store to six locations.
Measured storefront performance became the basis for expansion
Attribution
Ties specific displays and content to the walk-ins they actually drive.
Expansion call
Decides signage rollout store by store on validated performance, not impression.
Content scheduling
Compares performance by display and time window to rework the storefront.