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MAC randomization impact and data integrity simulator

Simulate how device MAC rotation affects guest WiFi analytics and model data reconciliation.

Simulate MAC randomization impact

1. Venue profile type

Choose a template that matches your venue footprint.

Large physical footprint, high pass-by count from adjacent streets, long dwell times, high return rate.

2. Ground truth footfall

Actual number of unique human visitors entering the venue per day.

3. Visitor return rate

40%
The percentage of daily visitors who have visited this venue previously.

4. Private address rate

80%
Percentage of visitor mobile devices running iOS 14+ or Android 10+ with MAC randomization enabled.
Data distortion simulation
+62%Raw Device Count Inflation

Without deduplication, raw probe sensors count rotated MAC addresses as new unique devices. In this scenario, raw logs record 24,240 devices, inflating your actual footfall of 15,000 guests.

Raw Probe Data (Skewed)24,240
Purple Reconciled (Corrected)14,775
Ground Truth (Actual Visitors)15,000
MetricUnique VisitorsReturn RateAvg Dwell
Raw Logs24,2405%58m
Purple14,77539%89m

Operational impact of data skew

Over-budgeting staff: Planning shift patterns based on raw device counts leads to over-staffing due to duplicate counts of rotated MAC addresses.
Skewed conversion rates: If visitor counts are artificially high, retail metrics like sales conversions (transactions / footfall) appear artificially low.
Undervalued loyalty: True returning visitors are masked, leading to poor customer loyalty tracking and inaccurate lifetime value modeling.

How Purple resolves address rotation and restores data integrity

Purple mitigates MAC randomization errors at the software layer by correlating signals across multiple touchpoints. When a user logs in via the captive portal, their account is anchored to their profile. Even if the device rotates its MAC address, subsequent logins are stitched together using session variables, browser cookies, and passive RF signatures. This cross-referencing corrects the database inflation, providing venue operators with accurate footfall, return frequencies, and dwell analytics.

Understanding privacy rotation and data accuracy

Modern mobile operating systems regularly randomize MAC addresses to protect user privacy. While beneficial for security, it distorts offline venue analytics by inflating visitor counts and shortening dwell times. This simulator demonstrates how raw data is skewed and how Purple reconciles these signals.

Key parameters simulated

  • Inflation rate of raw device counts due to address rotation.
  • Duplication of returning visitors counted as first time guests.
  • Data reconciliation using captive portal logins and cookie stitching.

Struggling with data accuracy?

Address rotation on iOS and Android can inflate raw footfall metrics. Purple reconciles guest signals through multi-source correlation, restoring analytics integrity.

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