Short answer: As tenants return after Labor Day, track seven access control metrics: unique visitors, peak hours, popular areas, amenity utilization, visitor volumes, enrollment adoption and fraud alerts. Edge.AI by Proptech.AI produces them as a by-product of everyday entry, enrollment and visitor invitations, so the upgrade that reduces badge and desk work also delivers building occupancy analytics. That double return is what makes it cost-effective.
Key takeaways
- Access control already sits at every entrance, making it the natural source of building occupancy analytics with no second sensor network to maintain.
- Seven metrics cover most owner decisions: unique visitors, peak hours, popular areas, amenity utilization, visitor volumes, enrollment adoption and fraud alerts.
- A metric belongs in the report only if someone owns it and a leasing, staffing, energy or capital decision depends on it.
- Edge.AI keeps analytics separate from the management console, tokenized and stripped of PII, so reports describe the building rather than individuals.
- A September baseline gives every later month, and the 2027 budget, a fair comparison point.
Why does the September return make a good baseline?
The weeks after Labor Day reset how tenants use the building, so data captured now becomes the yardstick for the year. Start later and next spring’s comparisons rest on estimates.
Badge swipes and manual lobby counts make weak baselines. Swipes count cards rather than people, so shared cards, waved-through guests and tailgaters distort the total, and manual counts depend on who was at the desk that morning.
Edge.AI facial recognition access control ties each recognized entry to an enrolled person instead of a card, and adds people counting, peak hours, unique visitor counts and popular areas. Of all the proptech data sources an owner can buy, this is one the building needs for security anyway.
Which access control metrics should a property manager track?
Track seven, each with a decision attached. If a number does not change what someone does next month, leave it out.
| Metric | What it tells you | Decision it informs | Who acts on it |
|---|---|---|---|
| Unique visitors | Different people using the building, not just entries | Leasing, renewals, space planning | Asset manager, leasing |
| Peak hours | When arrivals and departures cluster by weekday | Lobby shifts, cleaning windows, HVAC start times | Property manager, chief engineer |
| Popular areas | Entrances and shared spaces with the most traffic | Fit-out, signage and service spending | Property manager, owner |
| Amenity utilization | How often and when the gym, lounge or conference room is used | Keep, reprogram or resize | Owner, amenity staff |
| Visitor volumes | Guest numbers and their busiest days | Visitor desk hours, lobby coverage | Security or lobby lead |
| Enrollment adoption | Share of occupants on face, QR code or card | Card purchasing, onboarding outreach | Property manager |
| Fraud and spoofing alerts | Suspicious attempts at doors and turnstiles | Security procedures, staff training | Security director |
How do owners turn the numbers into leasing, staffing, energy and capital decisions?
Each metric earns its place by settling a question that would otherwise be settled by opinion.
Leasing
Unique visitor trends show whether the building is busier than last fall, giving renewal talks something firmer than anecdotes. Popular areas tell the leasing team which shared spaces to feature on tours.
Lobby and security staffing
Peak-hour curves show when the lobby needs two people and when one is enough. Visitor volumes by weekday show whether the visitor desk needs Friday afternoon coverage, especially once guests use appless pre-check-in for commercial building visitors.
Energy
Share the weekday arrival curve with your chief engineer. If Monday and Friday arrivals start later than the HVAC schedule assumes, engineering can test later start times. The access system does not run the HVAC; it supplies the evidence.
Capital planning
Amenity utilization turns capex debates into comparisons: a lounge busy only at lunch, a fitness center crowded at 7 a.m., a conference room reserved often but rarely entered.
Illustrative example: Assume a 400,000-square-foot multi-tenant office building that measures occupancy by hand. Every figure is a placeholder assumption; use your own.
- Manual lobby counts: assume 1.5 staff hours per weekday. 1.5 hours × 250 weekdays × $35 per hour = $13,125 a year.
- Monthly reporting: assume 8 hours a month merging badge exports and spreadsheets. 8 hours × 12 months × $60 per hour = $5,760 a year.
- Conditioning empty floors: assume arrival data lets engineering trim one hour on 10 floors every Monday and Friday, at $12 per floor-hour. 10 floors × 1 hour × 2 days × 50 weeks × $12 = $12,000 a year.
That is $30,885 a year spent on counting, compiling and conditioning empty space. Compare it with a subscription quote from Proptech.AI, remembering that the same system also runs entry, visitor invitations and credentials. Count the energy line only if your engineers will act on the data.
What belongs in a one-page monthly access report?
Use one page and the same layout every month. Owners read trends, so consistency beats detail.
- Occupancy: unique visitors against last month and the September baseline.
- Peak hours: arrivals by hour for a typical Tuesday and Friday.
- Spaces: the five busiest areas and amenities, and the two least used.
- Visitors: invitations, busiest days and any change in lobby coverage.
- Adoption: the share on face, QR code and card, plus planned outreach.
- Security: spoofing or fraud alerts and the follow-up on each.
- Decisions: one or two actions for next month.
Flag holidays, severe weather and tenant moves so a quiet week is not mistaken for a trend.
Can you report occupancy without monitoring individuals?
Yes, by reporting on the building rather than on people. Owners need counts, curves and trends, not where one tenant employee went on Tuesday.
Edge.AI is designed for that split: the analytics platform is separate from the management console, analytics data is tokenized and stripped of PII, and PII is kept apart from the Edge.AI device. Edge.AI can show when and where people move through a property, so treat that view as a security tool governed by your written privacy policy, not a tenant report.
Enrollment starts with biometric privacy consent, people who decline can use a QR code or RFID card, and all data can be deleted on request. Under GDPR Article 9, biometric data used to uniquely identify someone is special-category data, and the FTC’s 2023 policy statement on biometric information warns against unsubstantiated claims and unfair practices. This is general information, not legal advice.
How soon can a building start collecting this data?
As soon as readers are live at the main entrances, because Edge.AI works with the system you have, which keeps the upfront cost of this proptech upgrade low. It can connect to existing panels via Wiegand, run in parallel during a pilot, mix both in a hybrid layout, or replace the legacy system as a standalone platform, hosted in the cloud or on-prem. See how this applies to towers in AI access control and visitor management for commercial real estate.
101 Greenwich in New York, managed by JLL, began where many buildings are today: the 25-floor, 480,000-rentable-square-foot building with 1,500 tenants relied on manual counting and a limited access control system. Six Edge.AI sensors were installed on six turnstiles and integrated with the existing card-based system, giving 24/7 secure access, and the building team recognized Proptech.AI’s work in its BOMA Pinnacle Award speech. Read the 101 Greenwich case study.
For several buildings, roll the same seven metrics up across sites, as described in managing access control across a multi-site portfolio from one dashboard.
Frequently asked questions
Building occupancy analytics is the measurement of how many people use a building, when they arrive and leave, and which spaces they use. In an office building, the most practical source is the access control system, because it already sits at every entrance. Edge.AI by Proptech.AI reports building usage, people counting, peak hours, unique visitor counts and popular areas from everyday entry activity.
Access control data can take over much of the work of manual headcounts once every main entrance has a reader and most occupants are enrolled. Card swipes alone can mislead, because shared cards and tailgating distort the count. At 101 Greenwich in New York, a building that previously relied on manual counting, six Edge.AI sensors were installed on six turnstiles and integrated with the existing card-based access control system.
Leasing teams get the most value from unique visitor trends, peak hours, popular areas and amenity utilization. Unique visitors show whether the building is busier than last season, peak hours show when the building feels busiest, and amenity utilization shows which shared spaces deserve a place on a leasing tour. Edge.AI reports describe the building as a whole rather than individual tenant employees.
Edge.AI occupancy reporting is designed around aggregated building data. Proptech.AI separates the Edge.AI analytics platform from the management console, and analytics data is tokenized and stripped of personally identifiable information. Personal data is also kept separate from the Edge.AI device. Property teams should still adopt a written privacy policy that defines who may view entry records and for what purpose.
A monthly report suits owners and asset managers, while property managers benefit from a quick weekly look at peak hours, visitor volumes and fraud alerts. Keep the monthly report to one page with the same layout every time, compare each month with a fall baseline, and note holidays, severe weather or tenant moves that could distort the numbers.
Capture your baseline before the September return
See how Edge.AI turns everyday entry into the occupancy reporting owners ask for. Use the contact form at the bottom of this page or email sales@proptech.ai for a demo or a subscription quote.
