Dwell Time
How long people spend in each zone, store or area - visit by visit
Dwell time is the strongest signal of interest and friction. KSI measures it at the individual, anonymous visitor level - in every zone, store or area.
Traffic doesn't tell you if they stayed
A thousand people entering per day means nothing if half leave in thirty seconds. Traffic metrics tell you the door opened - not whether your proposition worked.
Aggregate averages don't cut it either: they hide that one zone keeps people for five minutes while another doesn't reach one, or that one mall store converts while the one next to it doesn't. Without per-zone, per-store, per-visit granularity, you can't diagnose where the leakage is.
Time in zone = measurable real interest
Anonymous entry/exit re-identification
1. Entry with anonymous ID
When crossing a zone perimeter, the visitor receives an anonymous ID based on their morphological signature.
2. Entry-exit matching
When the person exits, KSI re-identifies them against recent entries (configurable window, default 2 hours).
3. Dwell calculation
Exit time minus entry time. Result: the real dwell for each visit, without tracking individuals.
What dwell unlocks
In a store
Dwell across the whole store and by zone. The most direct signal of interest and a conversion predictor that traffic counts can't give you.
In a shopping mall
Dwell by store, tenant and common area. Discover which stores and mall zones retain visitors and which stay cold.
In an airport
Dwell by operational area: check-in, security, immigration, boarding and commercial zones.
Across locations
Compare dwell across stores, branches or terminals across your whole network - without installing anything new at each site.
Fitting room and decision zones
Time in the fitting room is one of the strongest predictors of conversion. Measure it and act on it.
Wait time in service areas
Detect when dwell at checkout, counter or check-in becomes friction and trigger operational alerts.
Engagement by section
Identify which categories retain visitors and which are avoided.
Staff filter
Automatically exclude staff - their dwell distorts any metric if not filtered out.
The interest signal traffic doesn't give you
98% validated accuracy
Anonymous morphological re-identification, without storing personal data. GDPR-compliant.
Per-zone, per-store, per-visit granularity
Not just averages. Every visit, every zone, every store or area, every shift - actionable.