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Privacy-First Fair Analytics

You can understand how your grounds get used without tracking a single fairgoer’s phone. Insight and privacy aren’t a trade—off here.

The Two Ways to Measure a Crowd

There are broadly two ways to learn how people move through an event. One is to watch their phones: seed the grounds with Bluetooth beacons and Wi-Fi sensors that listen for the wireless addresses every phone broadcasts, then estimate position and dwell from signal strength. It runs silently, on everyone in range, whether or not they ever asked to be measured.

The other is to measure what people choose to do in an experience they opened themselves. That’s Yubigo. A fairgoer scans the QR code on your signage, the interactive map opens on their phone with no app to download, and every search, route, and interaction becomes an anonymous signal — because they engaged, not because they were surveilled.

Passive Tracking Is a Losing Bet — on Both Counts

Watching phones was always a hard thing to defend to attendees. It has now also become a hard thing to rely on. Phones fight back: both Apple and Google rotate randomized wireless addresses precisely to stop this kind of tracking — iOS since version 14, Android since version 10, and newer releases changing the address on nearly every connection. The industry that installs beacons is itself moving toward software-first measurement.

So passive tracking lands in the worst quadrant: it’s the approach fairgoers object to and the approach that grows less accurate every OS update. First-party, opt-in measurement doesn’t decay that way — because it never depended on a phone quietly giving itself away.

What “Privacy-First” Means in Practice

Why This Matters for a Community Fair

A fair runs on local trust. Fairgoers are more aware than ever of how their phones get tracked, and both expectations and privacy regulations are tightening. An analytics approach that never surveils attendees isn’t just the ethical choice — it removes a liability, and it lets you hand your board and sponsors real engagement numbers you can stand behind. See what those numbers look like on the fair visitor analytics page, or the platform overview for fairs.

Frequently Asked Questions

How do beacon and Wi-Fi tracking systems collect data?

Passive Bluetooth and Wi-Fi analytics identify nearby phones by the wireless addresses those phones broadcast, then use signal strength to estimate where a device is and how long it lingers. The visitor is never asked and usually never knows. Yubigo does none of this — it measures only what people do inside a map they chose to open.

Isn't passive phone tracking becoming less reliable anyway?

Yes. Modern phones now rotate randomized wireless addresses specifically to prevent this kind of tracking — iOS since version 14 and Android since version 10, with newer releases rotating the address on nearly every connection. That makes passive beacon and Wi-Fi tracking both privacy-invasive and increasingly inaccurate. Opt-in, first-party measurement doesn't degrade this way.

What does Yubigo actually collect?

Anonymous, in-experience interactions: what fairgoers search for, where they ask for directions, how long they engage, which sponsors they see. There is no account, no email, no background location, and no device fingerprint sniffed from the air. Every metric is tied to your event and nothing else.

Do fairgoers have to consent?

Consent is built into how it works: scanning the QR code and opening the map is the opt-in. Nothing is measured before or after that choice, so there's no hidden tracking to disclose and no surveillance running on people who never engaged.

Why does privacy-first analytics matter for a fair?

Fairgoers are increasingly aware of how their phones are tracked, and expectations — and regulations — are tightening. A measurement approach that never surveils attendees protects the trust a community fair depends on, and it gives your board and sponsors real numbers without the liability of covert tracking.

Want analytics your fairgoers never have to worry about?

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Sources

  1. Apple, “Use private Wi-Fi addresses on Apple devices.” support.apple.com/en-us/102509
  2. Android Open Source Project, “MAC randomization behavior.” source.android.com
  3. Yang et al., “A BLE-Based Indoor Tracking System with Overlapping-Resistant IoT Solution for Tourism Applications,” Sensors (peer-reviewed). ncbi.nlm.nih.gov