Table of Contents

Video Analytics in Retail: Minimizing Security Incidents and Shrinkages

Implementing video analytics in the retail industry can be helpful in preventing a variety of security incidents and shrinkage scenarios such as spillage, intrusion, trespassing as well as other suspicious activities. Keep reading to find out how.

There has been a lot of emphasis on video surveillance in retail stores, owing to the fact that an average of 1.44% of the revenue of retail chains and stores is lost due to shrinkage, according to the National Security Survey. Shrinkage includes theft, employee and customer malpractices, pilferage and inefficient business practices.

Video surveillance helps the retail industry in multiple ways to different stake-holders, which includes customer journey management, store management, and employees’ behavior management. Of these, the most important factor where video surveillance contributes is reducing shrinkage and loss, which falls under the category of ‘security & surveillance’.

Security for retail stores is more than just theft or loss prevention. It includes preventing spillage and leakage, as well as ensuring the occupants (consumers as well as employees) safety. There are advanced video analytics features that come with video surveillance today to ensure flawless security when it comes to protecting the large retail stores from theft and loss, especially where manual surveillance proves to be highly inadequate.

Let us understand how video analytics ensure the security of retail store against loss and shrinkage:

Pre-emptive Security Alerts

Video Analytics enables preventive measures by detecting the events that prove to be a precursor to any security incidents. These primarily include crowd behavior analysis as well as prediction of certain situations that may lead to security incidences such as spillage detection, unattended object left behind etc.

Post-Event Alerts

Some Video Analytics algorithms help raise the alarm on detection of some safety-related incidences such as fall detection, people scattering, shelf sweep or sweet-hearting etc.

Following are some common use cases which constitute most of the security incidences and go a long way in minimizing the security issues for retail chains:

  • Loitering: This is one of the predictive threat detection algorithms, which takes into account tracking ID of the person and the time spent in the specific ‘Region of Interest (RoI)’ without any meaningful activity. When a person spends more than the required time at a specific location of a store it is likely to follow some or the other malpractices. This can be prevented using video analytics
  • Shelf Sweep: Shelf sweep is an action that employees usually perform outside office hours to clear out shelves for replacing the merchandise. However, this can be categorized as a suspicious activity if performed during the store operating hours, specifically by customers. Retail video analytics can detect this as a precursor to theft or nuisance creation
  • Spillage Detection: Any spillage of colored liquids or fluids may result in accidents, compromising the occupants’ safety and may also lead to hefty lawsuits at times. The video analytics algorithm can detect such scenarios and help prevent losses. It also helps in maintaining the effectiveness and cleanliness of the store and warehouse
  • Intrusion and Trespassing: In a retail store, access to certain regions such as billing desks, display cases high-value merchandise and central monitoring room need to be regulated based on authority. Video analytics raises intrusion alerts whenever trespassing into no-go areas are detected. Shelf sweep, as well as authority based monitoring, needs a dress code or tag detection to identify employees from a crowd, which can be done using video analytics
  • Threat and Theft Detection: Direct post-event alerts include detecting objects left behind or unattended for a certain stipulated time period. Algorithms can also be designed for detecting sweet-hearting and pick-and-hide kind of theft incidences in the RoI
  • Fall Detection: When a human being topples inside a store, fall detection algorithm can generate a quick alert, enabling store operators to provide a quick assistance that may be required. This not only is a post-care mechanism for the safety of customers and employees, but also falls under customer experience category
  • Camera Tampering & Malfunction: Any miscreant, who is aware of the cameras and their placements in the store first tries to tamper the camera functioning by screening or spraying some liquid to make the view hazy enough to hide the activities in ‘RoI’. This can be detected by certain rule sets in terms of percentage of view obstructed and respective alerts sent to the central server
  • Crowd Behavior Monitoring: Crowd behavior analysis is one of the most important sets of video analytics features that help ensure effective security and surveillance of a retail chain. Below are some key features in this category:
    • Crowd scattering: A sudden scattering of the crowd needs to be detected and responded as it can be a security threat.
    • Crowd gathering: Crowd gathering may, in some cases lead to vandalism and other malpractices and is tracked using crowd behavior analytics algorithms.
    • High-speed alerts: A walking or standing person when suddenly starts running at a high velocity, needs to be tracked for the further activities to ensure he/she is not involved in any security incidents.
    • Fights and chasing: There are algorithms, specifically to track physical altercations and chasing so as to safeguard the store and employees as well as consumers from such incidences and to get quick resolution of conflicts if they arise.
  • Other Suspicious Activities: Anything that resembles a weapon or is potentially harmful for the humans or property needs to be tracked along with the person carrying the same. The Video Analytics monitors harmful object and suspicious person/action for protecting the retail chains from security threats arising out of the same

eInfochips with more than 15 years of experience in video management solutions, brings the understanding of all the above features and leverages the expertise gained over the years in the field of video analytics to provide integrated security solutions for retail chains. Here’s are some good reads about how a partner like eInfochips can make fool-proof security a reality for the large retail chains.

To know more about our video surveillance solution, download the brochure – Snapbricks VMS:  For Advanced Video Surveillance.

Explore More

Talk to an Expert

Subscribe
to our Newsletter
Stay in the loop! Sign up for our newsletter & stay updated with the latest trends in technology and innovation.

Our Work

Innovate

Transform.

Scale

Partnerships

Device Partnerships
Digital Partnerships
Quality Partnerships
Silicon Partnerships

Company

Products & IPs