How to Optimize Shopping Center Security Ahead of Black Friday and the Holidays
Proactive Preparation for Security around the Holidays
Now that summer is over, the winter holiday season is a mere three months away. Companies that manage shopping centers need to prepare by thinking logistically about that critical retail season. The National Retailers Foundation estimates that for some retailers 30% of their annual retail revenues occur during the winter holiday season. The thefts may be perpetrated by consumers or by internal staff. Large crowds and consumer congestion, combined with an uptick in theft, require security managers to step up their efforts. Better security across a shopping center/mall is good for everyone: the owners of the shopping center, the retail merchants, and the shoppers.
One way to ensure better building security and inventory tracking during the holidays is to improve existing security infrastructure now, before the holidays hit. Are your security staff team members up to date in their job training? Do you have enough security staff in place for the upcoming busy holiday season? Are your video surveillance cameras working properly? And, just as importantly, do you have ways to review the video footage that is collected by those cameras?
Video Surveillance Optimization for Streamlined Security
Like retail stores, many shopping centers rely on video surveillance camera networks. But clearly, shopping centers/malls are much harder to surveil because they encompass much more territory and more complex building structures than a single retail store. Malls have multiple entrances and exits, plazas, lobbies, food courts, garages and/or parking lots, and delivery/loading docks, as well as access-controlled office areas and hallways. It’s impossible for security staff to effectively monitor every real-time camera feed, and it’s time-consuming for staff to review camera footage after an incident, when there is so much additional investigative work to accomplish. The amount of available video can be overwhelming to manually review and effectively scan. Furthermore, human observations can be prone to error and, as a result, most video footage goes under-utilized.
Shopping centers are turning to video content analytics (VCA) technology to better leverage their existing video surveillance systems. Powered by Deep Learning and Artificial Intelligence, VCA technology processes video, identifies objects in the video footage (people, vehicles, and other items), and indexes them so that footage can be easily and quickly searched and analyzed:
Improve Security Response Times with Real-Time Alerts
Video intelligence technology enhances security’s situational awareness by notifying security managers in real time when anomalous or suspicious persons, objects or behaviors are detected. When security teams know what normative activity to expect, they can configure alerts to notify them when irregular activity is detected that might warrant a response. For instance, count-based alerts can be triggered when a certain number of people are detected in a pre-defined area within in a specified time period. Security can reference data about typical shopping center traffic to define these alerts, taking expected peaks in traffic into account. When more people than expected are dwelling in an area, security teams can be notified and then assess the situation: Has a medical emergency or an altercation transpired? Was there simply a crowd of shoppers waiting in a long queue? With real-time alerts, the security operator can assess the situation and swiftly coordinate a response.
Prevent Losses from Theft
Dwelling or loitering can also indicate intent to commit a crime – especially when people are lingering in areas such as entryways or facilities that store valuable inventory. According to a National Retail Federation Survey, inventory losses cost retailers almost $48.9 billion in 2017, and 66.5% of those losses were attributed to external shoplifting or employee theft . Video investigation software and real-time alerting helps shopping centers detect signs of shoplifting, track shoplifters once an incident has taken place, identify employee theft and stop shrinkage.
When retail stores are missing inventory, security staff can use video intelligence technology to rapidly search weeks of video, focusing on specific areas, to identify suspects. Traditionally video investigators had to prioritize video to be manually reviewed, but with video content analysis, larger volumes of video can be reviewed by fewer people in less time, empowering security to search through even more video to pinpoint suspicious persons and behaviors and – ultimately – solve theft crimes and improve alerting logic for more proactive prevention.
Track Activity During Off-Hours
Alerts can also be set to detect dwelling and monitor movement after-hours in parking lots or the shopping center itself. Activity on the premises after hours could be innocuous, but with alerting, security can carefully monitor the situation and determine if something suspicious is afoot.
Quickly Locate Missing Children
When a child is lost in the shopping center, security staff can search volumes of video camera footage in a matter of minutes by using the advanced filtering capabilities of video content analysis technology to locate and reunite the child with his/her family.
Face Recognition for Theft Prevention, Investigation and Security Clearance
In locations where it is allowed, facial recognition is a powerful tool for shopping center security. Based on artificial intelligence, this technology matches faces detected in video against a watchlist of images (extracted from video or collected from external sources) to identify specific persons in video:
Triggering Real-Time Alerts
Security staff can extract images of suspects from different shoplifting incidents and assemble a suspect watchlist based on video surveillance footage. When a suspect from a watchlist is detected entering the shopping center, security can be on high alert and track the suspected shoplifter, intervening if a repeat offense is surveilled or deploying security staff to deter future attempts.
Biometric Identification and Access Control
Face recognition can be used for granting access permissions to employees and barring access to unauthorized individuals trying to enter a space. This can be applied in access-controlled areas of a shopping center, such as a loading dock, inventory closets or retail offices.
Identifying and Investigating Persons of Interest
Using analytics software, security and law enforcement can search footage based on face matching, identifying faces that match those on a watch list to extract evidence in an investigation.
Drive Business Intelligence with Aggregated Video Data
Using video intelligence technology, video data can be aggregated over time to uncover quantifiable data and trends. The aggregated data can be presented in visual reports, dashboards and heatmaps that not only help shopping center security managers reduce crime but also help operations staff better understand their customer behavior and needs. By mapping common customer paths, object interaction and dwell time, security and operations staff can accomplish the following:
- Identify crime hotspots
- Optimize traffic flow at major traffic interchanges or store locations
- Track crowd demographics, size and movement patterns
- Design more effective floor plans or parking lots
- Demonstrate the value of different store properties for retailers renting shop space
It’s challenging for security staff to protect shopping center buildings, store inventories and the people who shop and work in the centers. But their job can be much easier with video content analytics software enabling them to improve situational awareness; drive proactive responses; quickly search and review footage to solve crimes or identify theft; and derive business intelligence. With the holiday season just around the corner the stakes are higher, and it makes sense for shopping center managers to consider the benefits of deploying VCA technology to derive more benefit from their existing video camera networks.