AI Foot Traffic Prediction

The Problem

Predict foot traffic to optimize real estate decisions

Organizations face these key challenges:

1

Uncertain foot traffic projections lead to mispriced leases, higher vacancy, and weaker tenant performance

2

Manual counts and consultant studies are costly, slow, and not scalable across many assets or markets

3

Traditional methods fail to account for rapid changes (construction, transit disruptions, weather anomalies, new competitors, events), causing forecasts to become stale

Impact When Solved

More accurate site selection and underwriting with location-level traffic forecasts and confidence bandsFaster leasing and tenant-mix decisions by identifying high-potential zones, days, and hours for activationImproved portfolio performance through proactive interventions (marketing, events, amenities) tied to predicted traffic shifts

The Shift

Before AI~85% Manual

Human Does

  • Review every case manually
  • Handle requests one by one
  • Make decisions on each item
  • Document and track progress

Automation

  • Basic routing only
With AI~75% Automated

Human Does

  • Review edge cases
  • Final approvals
  • Strategic oversight

AI Handles

  • Automate routine processing
  • Classify and route instantly
  • Analyze at scale
  • Operate 24/7

Real-World Use Cases

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