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The retail industry's competitiveness drives the development of innovative apps to engage with customers and attract new ones. Today's shoppers seek a wide array of choices when making purchases, conducting thorough research before deciding. Businesses face the on-going challenge of effective marketing and expanding their customer base. Enhanced shopping experiences are now being facilitated through the implementation of artificial intelligence technologies that extend beyond basic automation. The utilization of computer vision in retail has emerged as a leading technology, allowing store owners to personalize the consumer experience and develop innovative marketing strategies. This adoption of AI not only improves operational efficiency but also facilitates long-term planning and enhances overall management practices in the retail sector.

What is Computer Vision?

Computer vision is the result of combining machine learning and data analysis to imitate the visual perception of physical objects and their surroundings. In essence, it is a technology that assists machines in comprehending visual information obtained from cameras within a given location. These systems utilize image processing algorithms for initial data processing, and machine learning or deep learning models for further analysis. Through the computing capabilities of machines and advanced software, these systems can derive meaningful insights that business owners can leverage to implement innovative strategies.

Computer Vision in Retail

The retail sector is in a perpetual pursuit of attracting customers, optimizing product marketing strategies, enhancing customer satisfaction, and boosting productivity. This on-going quest is supported by the ever-evolving field of technology such as AI, machine learning, computer vision, and deep learning. The progress in computer vision is reshaping business operations and driving the creation of innovative applications that drive growth and enhance operational efficiency. A heat map is a useful tool for visually representing the intensity or scale of a specific event. Instances of heat maps include charts that illustrate population density, traffic patterns, user engagement on various sections of a webpage, and more. By utilizing the concept of "hot" and "cold" zones, areas of high or low activity, flow, or density can be clearly portrayed. For instance, a Geographic Information System (GIS) heat map is an interactive map that displays warm colors for areas with high activity levels and cool colors for regions with low activity levels. It has become increasingly common to use a color scale in heat maps, such as red to signify higher activity or density, and green to indicate lower levels.

Heat Maps

In a retail store, a common practice is to create a heat map by overlaying a map onto a shop image to indicate the areas that are either most or least frequented by visitors. Some advanced software packages not only analyse the density of foot traffic in certain areas of the store but also track which products are interacted with the most. Cameras strategically placed throughout the store capture images that are then processed through a computer vision system. This system can detect and monitor the movement of individuals without compromising their privacy by utilizing facial recognition or individual identification. Heat maps offer a wide range of benefits and practical uses, such as:

Smart store layout & design

Retailers are utilizing heat mapping technology to strategically design their store layouts based on customer traffic patterns. High-traffic areas are prioritized, creating more open and organized sections while eliminating underutilized spaces. By aligning aisle layouts with visitor volume, retailers aim to enhance the shopping experience and boost overall productivity in their stores.

Advanced product marketing

Understanding the most frequented sections of the store aids retailers in strategically positioning items to attract customers' attention. By placing new products in high-traffic areas, they ensure maximum visibility to shoppers. Moreover, heat maps depicting changes in customer traffic before and after a product launch assist store managers in evaluating the product's popularity.

Efficient staff placement

Store managers utilize heat maps to strategically position additional sales personnel in high-traffic areas within the store. This strategic placement not only maximizes staff efficiency but also enhances the overall customer experience.

Optimized shopper’s waiting time

Heat maps are utilized to assess the waiting times of shoppers in queues throughout the day, allowing for better staff allocation, sales representative availability, and efficient checkout counter utilization during peak hours. By strategically planning for slower periods, businesses can optimize labour and maintenance costs.

Self-Checkout

Numerous retailers such as Walmart, Target, Sainsbury, and various department stores are implementing traditional self-checkout systems to expedite the payment process. Customers scan barcodes of each item individually to generate their final bill and complete their transaction. The integration of computer vision technology is revolutionizing the self-checkout experience by eliminating the need for barcode scanning. This automated system can identify products and charge customers accordingly, with some platforms even utilizing facial recognition for payment deduction. These results in shorter wait times for shoppers and a more efficient service compared to traditional checkout lanes. The adoption of automated checkouts in retail establishments proves beneficial for both consumers and businesses. By streamlining the checkout process, companies can allocate resources towards enhancing the overall shopping experience for customers rather than focusing on manual cashier duties.

Virtual Shopping

In the realm of the fashion industry, purchasing apparel from physical stores remains the favoured choice over online shopping. Consumers prefer the tactile experience of seeing, feeling, and trying on clothing items and accessories before making a purchase. The fashion industry leads in leveraging technology to enhance the customer experience. In response to the competitive market, businesses are turning to new and innovative apps to draw in a larger customer base. Consumers, in turn, are embracing the integration of virtual shopping experiences with the enjoyment of visiting a brand's physical store.

Virtual Mirrors

Virtual mirrors employ computer vision and augmented reality (AR) technology to enable users to effortlessly experiment with different outfits in varied sizes and colors, eliminating the need to physically change or utilize fitting rooms. By scanning the code of a garment, customers can view themselves in the attire through the virtual mirror. Furthermore, the lighting and background settings can be modified to provide shoppers with a realistic depiction of how the outfit may appear in different settings, offering a comprehensive understanding without actually trying it on. Gesture recognition algorithms are utilized by virtual mirrors to interpret user commands, while also incorporating a virtual cart feature. Customers can conveniently add selected items to their virtual basket for later payment and checkout.

Security and Detection

Security cameras are commonly found in shopping malls and retail stores to monitor various areas of the premises. Traditional surveillance systems require security personnel to continuously watch the footage, which can be challenging in busy or crowded environments. Advancements in computer vision technology have significantly improved security measures in brick and mortar retail establishments. By strategically placing cameras throughout the store, security software can detect suspicious activity, identify potential shoplifters, and act as a deterrent for theft. These systems can be further optimized by utilizing past footage of criminal activity to increase their accuracy in detecting and preventing theft. This approach also eliminates the need for additional security staff at different locations within the retail store.

Robot Assistants

Retailers are deploying robot assistants to serve as sales personnel, enabling consumers to interact with them through voice commands or touch displays to locate items within the store. Shoppers can input a shopping list, and the robot will navigate them through the store efficiently. Additionally, the assistant provides product information to customers. Through AI and computer vision technology, these robots analyse shopping behaviours and patterns, identifying popular items. This data assists retailers in making informed decisions.

Real life Examples

Explore the list below to discover which retail brands have implemented computer vision technologies to achieve substantial business results:

Technology

Usability

Platform/Brands

Facial recognition

Utilizing data to identify loyal members and deliver personalized messages to their mobile devices

Lolli and pops

Skin identification

Detection of skin health using images captured by a skin scanner.

Neutrogena

Product image recognition

Customers can access product information by taking a picture of the item.

Home Depot

Robot assistant

Performing inventory verification.

Walmart

Virtual mirror

Enhanced online shopping experience

John Lewis

Heat maps

Engaging in-store activities

Samsonite

Just Walk out

Automated checkout

Amazon Go

 

End-to-End Platform

The competitive nature of the marketing industry necessitates the association of contextual information with individual products. For instance, each item is linked to attributes such as colour, dimensions, cost, warranty, supplier information, and retail outlet details. A sophisticated Product Information Management not only manages fundamental product information but also its context via a centralized NERP platform. PIM systems serve as the primary source of product data for input into marketing or distribution channels and analytics platform. In a cutting-edge PIM system, customers have the ability to capture a product photo, which is then analysed to identify the product and provide comprehensive information about it. This innovative feature eliminates the need for monotonous barcode scanning, enabling customers to access instant product information including basic details, user manuals, customer reviews, and other relevant information.

Facial recognition technology within PIM systems can help identify loyal customers and their purchase history. By sending personalized product promotions and discount offers directly to their mobile phones, businesses can effectively engage with customers and encourage repeat purchases.

NERP has been meticulously crafted to accommodate all facets of business operations. Its adaptable architecture enables seamless integration with third-party tools and technologies, such as computer vision, empowering enterprises to soar to greater heights.

Summary

The possibilities for novel ideas and innovations in computer vision technology are limitless. The future of retail lies in the intersection of the physical world and digital technology. By integrating artificial intelligence with computer vision and analytics, the retail industry can elevate the customer experience, attract more shoppers, and streamline business operations for increased efficiency and reliability.

If you are seeking to enhance your business through innovation but have not yet deployed these technologies, reach out to us. We can help you leverage the latest advancements in technology to take your retail business to the next level.

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