What is Footfall Analytics?
Sensor- and camera-based measurement of store visitors, time-of-day patterns and dwell time. Combined with loyalty data, enables footfall-to-revenue attribution.
Why it matters in modern loyalty
Footfall Analytics sits at the intersection of customer data, machine-learning models and operational decision-making. Operators that measure and act on Footfall Analytics consistently report 25-45% higher repeat-rate and 30-50% lower churn than those that don't. Fundle.ai's platform exposes Footfall Analytics as a first-class data construct — surfaced in dashboards, exposed via API, and consumed by every AI agent in the stack.
How Fundle.ai uses this
- Real-time Footfall Analytics computation across the member base
- Integration into campaign targeting and AI offer selection
- Exposed via natural-language query interface (Fundle Brain)
- Historical trend reporting + anomaly detection
Related concepts
Modern loyalty programmes combine many of these constructs — RFM, cohort migration, CLV, churn risk, incrementality — into a single operating model. Fundle.ai ships all of them native, no consulting required.
Related resources
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