Top Retail Surveillance Strategies

The Top 10 Retail Surveillance Strategies for Success

Retail surveillance is becoming smart.

The hybridization of traditional retail surveillance with AI-based video analytics is fast becoming the norm. Retailers are driving success through measurable and actionable insights delivered by retail analytics.

But if you’re new to all this—where do you start?

A great starting point is understanding how and why retail surveillance is driving innovation through intelligent video analytics (IVA) and the top 10 strategies you can adopt for success.

The Future of Retail Surveillance – Intelligent Video Analytics

Smart retail utilizes IVA to record, analyze, and aggregate real-time customer data and leverages dashboards to deliver actionable insights to craft the best customer experience, which boosts sales.

IVA enables decision-makers to make critical business decisions to improve:

  • Operational efficiency
  • Product placement strategies
  • Store layout optimization
  • Theft detection and prevention

But how exactly is this achieved? Here are ten strategies in smart retail surveillance that give businesses the insights they need to succeed.

The Top 10 Strategies in Smart Retail Surveillance

1. People Counting

People counting tracks the number of customers that enter the store or are within a defined region of the store. 

With this data, managers can analyze how dimensions like advertising, displays, time of day, day of the week, location, etc. influence the frequency of visits.

2. Entrants Vs. Passerby Surveillance

IVA can identify and distinguish the number of shoppers entering your retail outlets compared to foot traffic walking past. 

This gives insights into the amount of foot traffic passing your stores versus how much is entering.

3. Dwell Time Surveillance 

Retailers use dwell time to determine how long a customer stays within a pre-defined store, department, or region.

This data offers insights into what displays and products pique a customer’s interest and how much time they spend deciding on a purchase.

4. Occupancy Time Surveillance

With the occupancy time IVA, retailers can determine how long customers stay in different areas of their stores. In addition, occupancy time data is fed into heatmaps, which visually display store areas with the most foot traffic, with red and orange regions representing higher rates of foot traffic activity.

Businesses use occupancy time and heatmaps to analyze peak and non-peak times to optimize operational efficiency further, which we will discuss later.

5. Intrusion Detection & Prevention

IVA allows retailers to detect unauthorized customers and staff in predefined areas. This aids in detecting unauthorized access to restricted areas, suspicious loiterers, and blocklisted people. 

This can help prevent break-ins and customers or staff from entering sensitive or dangerous parts of your business premises.

6. Merchandise & Aisle Activity

Understanding which areas of a store are visited more than others is paramount for the success of any retailer.

While sales tracking software can offer insights into what customers purchase, it is vital to understand where customers make their purchasing decisions in-store. 

Merchandise and aisle activity offers these insights and allows retailers to analyze what areas of their stores are busier than others and how to prevent bottlenecks of customers with better product placements to improve customer flow and the overall shopping experience. 

7. Age and Gender Demographics

Retailers that don’t understand their customers can’t sell to them, and a key data point for success is demographic market analysis. Smart retailers utilize IVA to track variables such as age and gender to gain insights. 

Dimensionalizing age groups and genders lets smart retailers tune shopping experiences to match demographic product preferences. 

8. Heat Mapping 

Fuelled by people counting, dwell time, occupancy time, merchandise, and aisle activity, customer heat maps give retailers a visual representation of “hot” and “cold” zones for customer activities. 

Analytical heat maps track customer traffic concentration and the resting zone by tracking customer paths and occupancy time.

This data is essential for managers to manage staff and tune customer experiences and advertising efforts.

9. Multi-store Operations Management

Managing multiple stores requires a centralized database to streamline business operations and analytics.

Smart retailers utilize multi-store operations management tools with online dashboards to record, analyze, and report on store traffic management, performance, and popular product zones across stores.

These tools can give retailers real-time data on how stores’ opening and closing hours, weather, time of day, day of the week, time of year, purchase patterns, and demographics affect business success and which stores are their top performers.

10. Smart Retail Business Intelligence Dashboards

While the data collection and analysis process is complex, the ability to consume insights shouldn’t be. Analytical dashboards are critical for displaying actionable insights with supporting data points.

Innovative retailers now use business intelligence dashboards that feed customizable retail data points into one consolidated display.

These insights empower decision-makers to boost store operational efficiency by optimizing customer experiences in near real-time.

Such dashboards help managers to understand how cross-store campaigns perform and make real-time adjustments across the organization for enhanced business outcomes. 

How Does Smart Retail IVA Work?

Smart retail IVA works in four steps to monitor customers, collect and analyze data, store, and report main findings. These steps go as follows:

Step 1: Retail Data Collection

Surveillance and security cameras monitor areas, and the video is fed into IVA software.

Step 2: Retail Data Analysis

IVA performs comprehensive analytics on the footage in real-time to produce data points such as the number of customers, merchandise activity, aisle traffic, dwell time, and age & gender analysis. 

Step 3: Data Management & Storage

Retail data points are then stored securely in a cloud, in an on-premise server, or in a hybrid cloud.

Step 4: Access & Reporting

Retail data points are presented through actionable graphs, charts, and widgets for detailed reporting on a centralized platform for managers to access and assess the necessary changes they need to drive into their business.

The Retailer’s Pathway to Business Intelligence for Success – Gorilla Smart Retail

With many strategies, retailers must adopt IVA to streamline operations and increase margins and profitability. 

Gorilla Smart Retail is a comprehensive, real-time solution for your surveillance system to provide insights into top-performing store layouts, shoppers, and conversion rates by delivering actionable insights for greater business outcomes.

Are you ready to enhance your retail surveillance with IVA for business success?


Facial Recognition

How Facial Recognition Works and How to Get Started in 2022

What is facial recognition? How does facial recognition work?

We’re here to answer those questions and give you a better understanding of this incredibly innovative technology and how to adopt it or adapt to it for your enterprise’s needs.

What is Facial Recognition?

Facial recognition is a technology that matches human faces with biometric data for identification purposes. It’s an innovative method of confirming a person’s identity using unique biometric data based on up to 80 facial nodal points. 

These data points are gathered from images, videos, or real-time footage of people and are generally stored in a secure database for future retrieval.

How Facial Recognition Works

Facial recognition creates a database of facial biometric data. This data is extracted from images or videos in which facial nodes are transformed into digitized data points. 

Step 1: Extract Facial Biometric Data 

  • A person’s face is captured in a photo or video using facial recognition technology 
  • Facial recognition software (such as Intelligent Video Analytics Recorder) analyzes biometric data to create a digitized and unique face profile

Capturing or uploading several images creates better facial feature extractions.

Step 2: Store Facial Biometric Data 

  • Facial biometric data is given a numerical value and is stored to compare against other face profiles in a database such as Gorilla Technology’s Biometric Analytics Provider

Step 3: Retrieve Facial Biometric Data for Identification

  • The facial recognition system connects with the facial data to identify and confirm a face profile
  • It can take up to 0.5 seconds to identify with up to 30 requests per second

Biometric data can also be used to create employee, VIP, and block lists, ensuring that only authorized people can be approved by the facial recognition system.

Key Features of Facial Recognition Systems 

Most facial recognition systems can create and manage face profiles, including easy integrations to third-party systems with APIs.

Depending on the system you adopt, you could have up to 100,000 profiles with demographic data, including gender, age, and more, with an intelligent video analytics management system.

How to Get Started with Facial Recognition

Facial Recognition requires a system that you need to build, manage, maintain, and continuously upgrade. You will need the following key components:

  1. Networked Cameras (to provide an image or video data)
  2. Server (to store and process data)
  3. Facial Recognition software (to analyze data)

Video management software collects videos from security cameras while biometric analytics systems analyze facial biometric data. Having these systems on a network edge will enable your business to perform faster data processing without returning biometric data back to the main server for authentication, saving valuable time. 

Basic Facial Recognition System Architecture

Most facial recognition systems follow a similar flow of data and processes:


The Growing Widespread Adoption of Facial Recognition

The COVID-19 pandemic increased the widespread use of facial recognition technology as a contactless form of identification. Facial recognition can also be used with other biometric security measures such as fingerprint, iris, and finger vein pattern recognition for multi-factor authentication. 

However, what makes facial recognition stand out from these security measures is that:

  1. It’s a contactless form of identification without touchpoints
  2. It’s more convenient and less intrusive 
  3. It only takes, on average, 0.5 seconds to verify a face
  4. It can quickly identify missing, unauthorized, and dangerous people effectively 

The technology is already in wide use, and applications exist in:

Facial recognition technology is a standard in our daily lives. With advances in AI and faster processors, facial recognition is a technology adopted as a new benchmark for biometric authentication.

Businesses, educational institutes, transportation hubs, and governments need effective systems to manage the flow of people.

For businesses, this could be managing employee attendance and preventing unauthorized persons from entering premises. For transportation hubs, the genuine danger of terrorism demands robust identification systems.

Gorilla Technology: A Market-leading Face Management System Solution Provider

Building facial recognition systems in-house is time-consuming, costly, difficult to maintain, and requires a high level of expertise. 

That’s where Gorilla Technology’s Biometric Authentication Provider (BAP) and IVAR (Intelligent Video Analytics Recorder) come in.

Our out-of-the-box software and hardware solutions were designed with existing AI-level face recognition capabilities to identify and verify facial biometric data.

Get started and check out our video analytics software and how it can be tailored to your enterprise’s business needs, or contact our team directly to schedule a demo.