Ayonix Video Analytics

Industry

Video analytics for shopping centre leasing and operations

In short

Shopping centre video analytics measures centre-wide footfall, the routes visitors take between anchors, which zones they reach and how busy each area becomes. Leasing teams gain evidence for unit pricing, and operations teams gain occupancy visibility during peak trading.

Customers waiting in organised checkout queues at a modern supermarket
Conceptual illustration of checkout queueing used for wait measurement. AI-generated conceptual image, not a customer deployment.

The problem

What shopping malls teams are dealing with

  • Unit rents are negotiated on centre-wide footfall because zone-level evidence does not exist.
  • Upper floors underperform and nobody can show whether the problem is reach or conversion.
  • Marketing campaigns are evaluated on total footfall, which hides whether they changed where people went.
  • Operations learn a mall area is congested when it is already visibly crowded.
  • Tenants dispute footfall figures because the measurement method is opaque.

Camera placement

Where cameras need to be, and why

Camera position decides more of the outcome than any software setting. These are the placements that matter in this sector.

Recommended camera placement forShopping malls
Location Purpose What matters
Every mall entrance Directional footfall Completeness matters more than precision — a missed entrance invalidates every derived proportion.
Escalator and lift lobbies Inter-level route volumes These are the measurement points that answer the upper-floor reach question.
Mall corridors between anchors Route volumes Consistent direction labelling across all corridors is what makes route data comparable.
Food court and seating Zone occupancy and dwell Elevated views over defined zones; seating areas need their own dwell treatment.
Unit frontages in scope Passing traffic for leasing evidence Comparable camera geometry across units is essential if units are to be compared fairly.

Workflow

From event to acknowledged action

Event workflow

  1. 1 Entrance, corridor and lobby cameras are ingested and monitored.
  2. 2 Directional counts are produced at every entrance and route measurement point.
  3. 3 Zone activity and dwell are accumulated over the reporting period.
  4. 4 Route volumes and zone reach are computed as aggregate proportions.
  5. 5 Occupancy thresholds raise operational warnings where configured.
  6. 6 Series are published to leasing, marketing and operations dashboards.

Operator workflow

  1. 1 Operations receives an occupancy warning for a mall zone approaching its threshold.
  2. 2 Cleaning, security or flow-management staff are directed to the area.
  3. 3 Leasing pulls unit-frontage passing traffic and zone reach for a rent review.
  4. 4 Marketing compares campaign-period route volumes against the stored baseline.
  5. 5 Tenant reporting is issued from a documented, consistent measurement method.

Operations

Dashboards, integration and deployment

Dashboard metrics

  • Centre footfall by entrance and interval
  • Route volumes between anchors and levels
  • Zone reach as a share of arrivals
  • Unit-frontage passing traffic
  • Zone occupancy against threshold
  • Coverage completeness and camera availability

Integration options

  • REST and webhook delivery into leasing and centre-management platforms
  • Tenant reporting exports
  • VMS event delivery for occupancy and security rules
  • ONVIF and RTSP ingestion from the centre camera estate
Compatibility states →

Deployment options

  • On-premise processing, normal because a centre already aggregates cameras
  • Edge processing per building in a multi-building centre
  • Multi-site management across a centre portfolio
  • Hybrid deployment for portfolio-level benchmarking on aggregate series only
Compare architectures →

Evidence

Deployment pattern

Centre leasing and operations pattern

Complete entrance counting, inter-level route volumes, zone reach and occupancy thresholds, delivered to leasing, marketing and operations with documented coverage.

All figures are measured on your own centre. No footfall or reach benchmarks from other centres are published, because catchment, layout and anchor mix make them misleading.

This is an anonymised pattern describing how a deployment of this kind is structured. It is not a named customer reference. No customer names, logos, testimonials or measured results are published on this site, because none have been supplied for publication. More on how evidence is handled .

Governance

Privacy and governance in this sector

  • All leasing and marketing outputs are aggregate volumes and proportions; no individual journey is reconstructed.
  • Cross-camera re-identification is not deployed, so tenant reporting cannot and does not track individuals.
  • Where demographic estimation is requested for retail-media inventory, the lawful basis and impact assessment come first.
  • Tenant-facing figures should be accompanied by the measurement method and known coverage gaps, which is what makes them defensible in a rent review.
  • Centre privacy notices should cover the analytics purpose explicitly.

Frequently asked questions

Can you track a shopper from the car park to a unit?

No. Cross-camera re-identification is not deployed. Route volumes and zone reach are aggregate proportions computed from counts at defined measurement points, which answers the leasing and layout questions without building individual journeys.

What happens if we miss an entrance?

Every derived proportion becomes unreliable, which is why entrance completeness is the first priority and coverage gaps are documented explicitly rather than quietly absorbed into the figures.

Will tenants accept these figures?

They are far more likely to when the measurement method, the counting error and the coverage gaps are published alongside the numbers. Opaque footfall figures are what generate disputes.

Other industries

Author
Gabriel Bamola, Chief Marketing Officer, Ayonix
Technical review
Dr Sadi Vural, Founder and Chief Executive Officer, Ayonix
Published
Last reviewed

Design a shopping malls pilot around your own cameras

Start with a camera readiness review and a log-only baseline, then measure against acceptance criteria we agree before the pilot begins. That is what turns an analytics evaluation into a decision.