What Is WiFi Presence Analytics? Probe Requests Explained

Key Takeaways: WiFi presence analytics is a passive detection technology that measures foot traffic, dwell time, and zone occupancy by capturing wireless probe requests broadcast by smartphones and other WiFi-enabled devices — without requiring those devices to connect to the network. Every modern smartphone periodically transmits probe request frames when WiFi is enabled, and access points within range can detect these signals to estimate visitor counts, movement patterns, and dwell duration. MAC address randomization has made individual tracking unreliable, but statistical methods still produce accurate aggregate footfall data.

Every smartphone with WiFi turned on is broadcasting. Not connecting — just broadcasting. These signals are called probe requests, and they're detectable by any access point within range.

WiFi presence analytics captures those broadcasts and converts them into foot traffic data: how many people are near the venue, how many enter, how long they stay, which zones they visit, and what percentage return.

This is fundamentally different from captive portal analytics. Portal data requires the guest to connect and authenticate. Presence data requires nothing from the guest — just a WiFi-enabled device in their pocket.

For resellers, presence analytics is the "top of funnel" data layer. It measures everyone. The portal captures a subset. Together, they tell the complete story.

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How probe requests work

The 802.11 probe mechanism

When a WiFi-enabled device is not connected to a network (or is scanning for better networks), it periodically sends 802.11 management frames called probe requests. These frames contain:

• •Source MAC address — the device's hardware address (often randomized)
• •Supported data rates — the device's WiFi capabilities
• •SSID list (sometimes) — names of networks the device has connected to previously
• •Information elements — vendor-specific data, HT/VHT capabilities

Probe requests are sent on every WiFi channel the device supports. A typical smartphone sends 5-15 probe bursts per minute when actively scanning, and 1-3 per minute in low-power background mode.

Any access point or wireless sensor within range receives these frames. Range depends on AP radio power and device transmit power — typically 30-100 meters indoors, up to 200 meters outdoors with commercial APs.

What the AP records

When an AP detects a probe request, it can log:

• •MAC address (source of the probe — may be randomized)
• •RSSI (Received Signal Strength Indicator) — distance proxy
• •Timestamp — when the probe was detected
• •Channel — which frequency the probe was sent on
• •Frame data — capabilities, SSID list, vendor OUI

By collecting probes across multiple APs, the system triangulates approximate device location within the venue. RSSI-based positioning achieves 3-8 meter accuracy indoors (IEEE, 2024). CMX-style systems (Cisco Connected Mobile Experiences) achieve 1-3 meter accuracy using dedicated location engines.

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The MAC randomization challenge

What changed

Before 2020, most smartphones used their real (hardware) MAC address in probe requests. This made presence analytics straightforward — one MAC = one device = one visitor. Tracking was precise.

Then Apple (iOS 14, 2020), Google (Android 10, 2020), and Microsoft (Windows 10 1803, 2018) implemented MAC address randomization by default. Devices now use randomly generated MAC addresses in probe requests, changing the random MAC every 15-30 minutes or with each new network scan.

Impact by the numbers:

• •Pre-randomization: 1 MAC = 1 device (95%+ accuracy)
• •Post-randomization: 1 device generates 4-20+ MACs per hour
• •Raw probe counts overestimate unique visitors by 2-5x (Wireless Broadband Alliance, 2024)

How modern systems compensate

Presence analytics platforms use statistical deduplication to correct for randomization:

1. •Frame sequence analysis — probe requests from the same device share incremental sequence numbers within a session, even with randomized MACs
2. •Timing pattern correlation — inter-frame arrival times create a device "fingerprint" that persists across MAC changes
3. •Capability fingerprinting — the combination of supported rates, HT capabilities, and information elements identifies device type (iPhone 15 vs. Galaxy S24)
4. •RSSI trajectory matching — a device moving through the venue produces a consistent RSSI pattern across multiple APs, linkable even with MAC changes
5. •Statistical modeling — machine learning models trained on ground-truth data (from venues with both cameras and WiFi) apply correction factors

Post-deduplication accuracy: ±10-20% for unique visitor counts. Good enough for trend analysis and comparative metrics (week-over-week, zone-vs-zone), but not precise enough for exact headcounts.

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Presence analytics metrics

Footfall count

Total unique devices detected within the venue's AP coverage area. Segmented by:

• •Visitors — devices detected inside the venue for >2 minutes
• •Passersby — devices detected briefly (<2 minutes), likely walking past
• •Connected — devices that actually joined the network
• •Conversion rate — visitors ÷ passersby (what percentage of passing traffic enters)

A typical retail store sees a passerby-to-visitor conversion rate of 20-35%. Knowing this number — and tracking it over time — is worth more than most marketing campaigns.

Dwell time

How long a device remains within detection range. Calculated from first-seen to last-seen timestamps, with idle gaps filtered out.

Zone occupancy

With multiple APs, presence analytics maps device density by physical zone. Each AP covers a defined area — a dining room, a checkout zone, a specific floor. The system counts devices per AP to produce zone-level occupancy data.

This is what turns presence analytics into heatmaps — visual overlays showing where people cluster within a space.

Repeat visit rate

By matching connected device MACs (post-authentication, using real MACs), the system tracks how often identified guests return. Presence-only repeat tracking (using randomized MACs) is unreliable for individual identification, but combined with portal authentication data, repeat rates become precise.

Industry benchmarks for repeat visit rates:

• •Restaurants: 25-40% monthly repeat rate
• •Retail: 15-25%
• •Gyms: 40-60%
• •Coffee shops: 35-55%

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Presence analytics vs. other footfall technologies

WiFi presence analytics wins on cost (zero hardware investment if APs already exist) and data depth (dwell time + zones + frequency). It loses on absolute counting accuracy to camera and infrared systems. The sweet spot for resellers: WiFi presence for behavioral intelligence, supplemented by portal data for identity.

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Privacy and legal framework

GDPR position

The European Data Protection Board's Opinion 01/2017 on WiFi tracking explicitly addresses probe request collection:

• •MAC addresses (even randomized) are considered personal data if they can be linked to a device or person
• •Collection requires a lawful basis (legitimate interest or consent)
• •Data minimization applies — collect only what's necessary
• •Transparency obligation — inform people that tracking is occurring (signage)

Practical implication: Venues using presence analytics in the EU should display signage informing visitors of WiFi analytics, provide an opt-out mechanism (typically "turn off WiFi to avoid detection"), and anonymize/aggregate data within a defined retention window.

CCPA position

California treats MAC addresses as personal information when linked to a consumer. Presence analytics using aggregate, de-identified data falls outside CCPA scope. Linking MAC addresses to identity data (via portal authentication) brings the data fully into CCPA scope.

Industry best practice

1. •Aggregate presence data within 24 hours (hash individual MACs, retain only counts)
2. •Display venue signage about WiFi analytics collection
3. •Keep raw probe data for ≤72 hours
4. •Separate presence data from identity data architecturally
5. •Provide documentation for venue clients on compliance obligations

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Deploying presence analytics as a reseller

Hardware requirements

Any commercial AP that supports probe request logging or location APIs:

• •Cisco Meraki — CMX Scanning API provides real-time probe data with location coordinates. The richest presence data in the industry.
• •Juniper Mist — Mist Location Services with zone-level occupancy and dwell time via cloud API
• •Aruba — ClearPass provides presence analytics through Aruba Central
• •Ruckus — SmartCell Insight (SCI) for presence and location data
• •Ubiquiti UniFi — Basic presence via client connection logs; no native probe analytics

Enterprise APs provide richer presence data. SMB APs provide connection-level analytics only. Check hardware compatibility for your deployment.

Pricing the service

Presence analytics adds $50-$150/month to a WiFi marketing package. Resellers typically tier it:

Bundled with WiFi marketing and portal data, presence analytics justifies moving clients from a $149/month package to a $299/month "venue intelligence" package.

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Frequently asked questions

Does presence analytics work if people have WiFi turned off?

No. If a device's WiFi radio is disabled, it doesn't send probe requests. However, 94% of smartphones have WiFi enabled in public spaces (Cisco, 2025), so the detection rate is high.

Can presence analytics identify specific individuals?

Not reliably through probe requests alone, due to MAC randomization. However, when combined with captive portal authentication (which captures the real MAC), known guests can be tracked accurately across visits. The system works best as a two-layer approach: aggregate from presence, individual from portal.

How is presence analytics different from WiFi analytics?

Presence analytics measures devices passively — no connection required. WiFi analytics captures data from connected and authenticated guests. Presence gives you the numerator (total traffic). Portal gives you the denominator (identified visitors). Both are needed for a complete picture.

Does MAC randomization make presence analytics useless?

No. It makes individual tracking unreliable, but aggregate metrics (total footfall, dwell time averages, peak hours, zone occupancy) remain accurate within ±15% after statistical deduplication. For trend analysis and comparative metrics, that accuracy is sufficient.

What's the range of WiFi presence detection?

Indoor: 30-100 meters from the AP, depending on walls, interference, and AP radio power. Outdoor: up to 200 meters with commercial directional antennas. For accurate zone-level data, AP placement should create overlapping coverage with 15-20 meter spacing.

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Bottom line

WiFi presence analytics measures what captive portals can't — the full picture of foot traffic, including everyone who walks by or enters the venue without connecting. It's passive, uses existing infrastructure, and produces actionable metrics: footfall, dwell time, zone occupancy, and visit frequency.

MAC randomization has reduced individual tracking precision, but statistical methods maintain aggregate accuracy. The combination of presence data (everyone) and portal data (authenticated guests) creates a two-layer intelligence system that answers both "how many?" and "who?"

For resellers, presence analytics is the upgrade path — the reason a client pays $299/month instead of $149/month. It turns WiFi marketing from "we capture emails" into "we measure everything that happens in your physical space."

Explore presence analytics features and see which hardware vendors support the deepest presence data for your deployments.