Smart Loss Prevention Solutions

Detect threats, prevent theft, and secure assets with AI analytics.

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Preventive Insights

Spot risks early - before shrinkage occurs.

FootfallCam identifies unusual shopping behaviours around high-risk shelves and highlights them for routine staff attention. This turns loss prevention into a simple daily SOP rather than a reactive scramble.

Real-Time Awareness

Clear, actionable alerts - sent directly to your team.

When behaviour escalates, FootfallCam sends a short video clip to the store’s mobile devices, enabling quick, safe, and informed action without confrontation or guesswork.

14-Day Traceability

All related behaviours - searchable in minutes.

FootfallCam compiles all relevant clips and paths across the last 14 days, making investigations fast, structured, and accurate, without hours of rewinding CCTV footage.

Suspicious Activity Monitoring

AI-Theft Detection

Learn how AI models detect suspicious behaviour and send alerts to staff.

Suspicious Behaviour Monitoring and Alert

Suspicious Behaviour Monitoring and Alert

AI analytics detect loitering, concealment, and suspicious actions near high-value items. Real-time alerts notify staff for immediate response, preventing incidents before escalation. This proactive approach shifts from passive CCTV monitoring to intelligent detection, minimising false alarms while safeguarding assets and enhancing security efficiency across retail operations.

How it Works (00:51)
Facial Recognition for Repeat Offender Alerts

Facial Recognition for Repeat Offender Alerts

Facial recognition identifies known shoplifters upon entry and alerts staff instantly. This proactive measure deters repeat offenders, ensuring a safer environment for shoppers and employees. Integration with existing CCTV systems makes it scalable and cost-effective, helping retailers reduce theft while strengthening store-wide security and customer confidence.

Blacklisting

Retailers can centralise offender data across multiple branches. Once flagged, individuals are automatically identified network-wide, preventing exploitation of location gaps. Effective against organised retail crime groups, blacklisting ensures all stores remain informed, creating a strong collaborative defense and reducing repeated losses across the retail chain.

Internal Theft Detection

Internal Theft Detection

By analysing video streams, Centroid flags irregular staff activity, such as cash drawer access without transactions, inconsistent stock handling, or unauthorised entry into restricted areas. Linked with attendance and access logs, alerts integrate into SOPs, ensuring systematic, discreet investigations. Transparent monitoring deters misconduct, protects assets, and reinforces operational trust.

ePOS Audit

ePOS Audit

Integrating video with ePOS data allows automatic verification of every sale, refund, or void. The system highlights discrepancies, fraudulent refunds, or under-ringing items while providing video evidence. Automated audits reduce manual checks, strengthen financial controls, and give retailers effective protection against transaction-level fraud and shrinkage.

Case Study

Convenience Store
Beauty Chain
Fashion Boutique

Convenience Store (Real-Time Alert)

Case Study 1

Convenience Store (Real-Time Alert)

Problem

A convenience store near a late-night bus station suffered frequent grab-and-go thefts. Staff could not predict when incidents would occur and CCTV footage rarely offered actionable insight.

Solution

FootfallCam’s real-time alerts sent 5-second clips directly to the cashier whenever customers exhibited rapid shelf approach → quick grab → immediate exit patterns.

Outcome

Staff learned to intervene early with simple customer engagement, reducing night-time theft attempts by 42% within two weeks. The team reported feeling safer and more in control during late shifts.

Beauty Chain (Preventive)

Case Study 2

Beauty Chain (Preventive)

Problem

A beauty retailer struggled with high shrinkage in fragrance and skincare categories. Theft behaviours were subtle — extended dwell, repeated item touch, and grouping.

Solution

FootfallCam’s preventive list highlighted the top 30 most unusual behaviours each day. Staff were instructed to greet and offer assistance to individuals flagged.

Outcome

Passive deterrence reduced suspicious behaviour by 35%, and shrinkage dropped noticeably without any confrontational incidents. SOP became routine, requiring only 5 minutes of staff time per shift.

Fashion Boutique (Traceability)

Case Study 3

Fashion Boutique (Traceability)

Problem

Expensive apparel periodically went missing from a premium boutique. Traditional CCTV made investigations slow and inconclusive.

Solution

FootfallCam’s 14-day traceability allowed LP staff to filter only visitors who interacted with specific rails and review sorted behavioural clips.

Outcome

Within minutes, the manager identified repeated suspicious tag-swapping patterns over two weeks. Staff were rebriefed, store layout improved, and shrinkage reduced. The boutique avoided escalating to accusations or police involvement.

Ready to learn more?

Next Steps

Selecting the appropriate functions and devices to serve your specific purpose is crucial. To get started with your own designs, it can be helpful to review deployments of similar systems in other malls for inspiration.

Talk to an Expert

Talk to one of our FootfallCam consultants to identify your requirements, budgets, and possibly conduct a Proof of Concepts, to help ensure that FootfallCam system is the right fit for your mall.