MAC 随机化影响与数据完整性模拟器

模拟设备 MAC 轮换如何影响访客 WiFi 分析，并对数据对账进行建模。

模拟 MAC 随机化影响

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.

理解隐私轮换与数据准确性

现代移动操作系统定期随机化 MAC 地址以保护用户隐私。虽然这有利于安全，但它会通过虚增访客数量和缩短停留时间来扭曲线下场所分析。本模拟器展示了原始数据是如何被扭曲的，以及 Purple 如何对这些信号进行对账。

模拟的关键参数

由于地址轮换导致的原始设备数量虚增率。
回访客被重复计为首次到访访客。
使用强制门户登录和 cookie 拼接进行数据对账。

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.

Talk to a WiFi expert