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Real Estate verified Verified Outcome TRL 9

Retail Mobility Analytics (Foot Traffic)

domain Client: Commercial Landlords / Retailers handshake Provider: Placer.ai schedule Deploy: 2018-Present
95 Impact
Enterprise Ready
Evidence Score: 5/10
Strength: Very High

Executive Summary

ANALYST: COI RESEARCH

Use of aggregated mobile location data to analyze foot traffic patterns, allowing landlords to price leases based on actual visitor volume rather than estimates.

rate_review Analyst Verdict

"The 'Bloomberg Terminal' for physical retail. It replaced the guy with a clicker counting people at the door. It provides the definitive 'truth' on how a property performs, changing lease negotiations from art to science."

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Full Audit Report Available Includes Risk Register, Technical Specs & Compliance Data.

warning The Challenge

Retail leases were traditionally priced based on 'gut feel' or static demographics (e.g., 'high income zip code'). Landlords couldn't prove to tenants that a specific mall wing got more traffic, and tenants couldn't verify if a location was actually busy before signing a 10-year lease. Valuations were often inaccurate.

psychology The Solution

Aggregated anonymized data from millions of smartphones to visualize foot traffic. The platform shows exactly where customers come from (trade area), where else they shop (cross-shopping), and how many people visit a specific property daily. Landlords use this to justify higher rents for busy spots; retailers use it to pick winning locations.

settings_suggest Technical & Deployment Specs

Integrations
GIS Systems
Deployment Model
SaaS Platform
Data Classification
Geospatial / Mobile
Estimated TCO / ROI
Subscription
POC Summary ( to )

"N/A"

shield Risk Register & Mitigation

Risk Factor Severity Mitigation Strategy
Privacy Legislation Medium Aggregated/Anonymized only.
Data Bias Low Normalization algorithms.

trending_up Impact Trajectory

Audited value realization curve

Industry standard for site selection Verified Outcome
Primary KPIReduction in bad site selection decisions
Audit CycleGranular insight into competitor performance

policy Compliance & Gov

  • Standards: CCPA / GDPR
  • Maturity (TRL): 9
  • Evidence Score: 5/10
  • Data Class: Geospatial / Mobile

folder_shared Verified Assets

description
Verified Case Study
PDF • Version 1
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Technical Audit
PDF • Audited
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The "Blind Verification" Protocol

How we verified these outcomes for Commercial Landlords / Retailers without exposing sensitive IP or identities.

Private
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1. Raw Evidence

Audit ID: #PRIV-642
Evidence: Direct SQL Logs
Public
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2. Verified Asset

Outcome: Verified
Ref ID: #COI-642

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