How do I get utilisation data from my meeting rooms?
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Real meeting room utilisation comes from triangulating three independent data sources: booking platform data (what was booked), occupancy sensor data (what was actually used) and AV usage data (what the room was used for). Relying on any single source typically overstates utilisation by 40 to 70% because booked-but-unattended ghost meetings, walk-in informal use and AV-free in-person meetings each get missed by different sources.
The three data sources and what each one tells you:
| Source | What it shows | Typical platforms | Limitations |
|---|---|---|---|
| Booking platform | What was booked vs what was checked in or no-showed | Robin, Smartway2, Eptura, Microsoft Places, Outlook native | Misses walk-in use, overcounts ghost meetings without check-in |
| Occupancy sensors | Whether anyone is actually in the room and how many | PIR (cheap, presence only), ToF (accurate, head-count), mmWave (people-count without cameras) | Sensor calibration, false positives in glass-walled rooms |
| AV usage | Whether and how the in-room AV was used (call count, duration, platform) | Microsoft Teams Rooms Pro Management, Zoom Rooms admin, Crestron XiO Cloud, Q-SYS Reflect | Misses in-person meetings that didn't use AV |
Why triangulation matters in practice. A room that shows 80% booking utilisation but only 30% sensor occupancy is being ghost-booked: people block it without using it. A room with 60% sensor occupancy but 10% AV usage is being used for in-person meetings, so investing more in VC kit there is the wrong move. A room with 90% sensor occupancy and 80% AV usage is genuinely stretched, and warrants either a spec upgrade or a duplicate room next door.
Sensor choice is the part most clients get wrong. PIR is cheapest and tells you "someone is in here" but not how many. Time-of-flight (ToF) sensors give a reliable people-count and are the right default for desk and meeting room utilisation work. mmWave radar offers people-count without any camera or video, which solves the privacy and works council questions that often block sensor rollouts in the UK and EU. Cameras (using on-device anonymous head-counting) are the most accurate but the hardest to get sign-off for in regulated sectors.
A meeting room AV integrator running consultation and design on a utilisation programme will normally combine sensor data into the same dashboard as booking and AV telemetry, so workplace, IT and property teams see one number per room rather than three competing ones.
Quick reference: triangulate booking platform + occupancy sensors + AV usage. Single-source data overstates utilisation by 40-70%. ToF sensors for accurate count, mmWave for privacy-sensitive rollouts.
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