Although computer vision was introduced in the 1970s, there weren’t enough resources or technical expertise to bring related breakthroughs to the forefront. Lately, with the tremendous leaps in technology and the emergence of big data, artificial intelligence and computer vision adoption have reached a tipping point.
The computer vision revolution
GlobalData estimates a computer vision market size of US$28 billion by 2030 – a steep rise from US$3.5 billion in 2019.
Today, over 3 billion images and 700,000 hours of videos are shared daily across multiple social media channels like Facebook, Snapchat, Instagram, and WhatsApp. Industries and enterprises are embracing computer vision and deep learning technology to harness and extract actionable intelligence. The desire for broader access to these images and videos increases the public demand for and popularity of computer vision-driven applications.
Below is Statista’s study on the global computer vision’s market revenue by segment for 2015 – 2019.
Source – Statista
The present and future of computer vision in retail
Understanding customer product and brand sentiment have become critically important to improving customer experience, enhancing personalization, optimizing service delivery, and building strong brand loyalty. AI, computer vision, and deep learning technologies are now providing retail companies actionable insights on customers facilitating new ways to offer enhanced customer experience. Convolutional neural networks (CNNs) are specifically applied to identify objects and faces, monitor and analyze retail traffic, and power robots and driverless vehicles in the supply chain.
Advanced techniques employing visual search, automated recommendations, demand forecasting, intelligent task automation, optimized resource allocation, and emotion detection are areas where AI, computer vision, and deep learning make retailers more efficient, effective, resilient, and fundamentally better positioned to serve customers. These technologies support sustainable manufacturing, enhance supply chain processes, enable personalization, improve logistics, drive efficiency, and elevate responsiveness, all of which are critical for a retail operation in a competitive marketplace.
Heatmap analytics – a valuable tool for retailers
A heatmap is a graphical visualization of data that uses colors to depict the strength and magnitude of the occurrence of a phenomenon. Heatmap analytics helps retailers understand customer behavior and optimize conversions from visitors to customers.
Cameras installed within the retail store capture images processed by computer vision to detect, track, and analyze the patrons’ movements. These systems provide comprehensive and detailed insights into the activity of people within the store.
Computer vision-powered software generates heatmaps not just based on the density and movement of people in the store but also on the products they touch. Retailers then gain insights into which zones and product lines perform better, allowing them to incorporate this intelligence into operational plans for optimizing performance across other zones and stores.
Some benefits of heatmaps include
– Tracking customer footfall and their behavior
– In-store analytics help improve store design, positioning of shelves, product placement, lighting, etc.
– Minimizing customer wait time
– Optimally allocating resources according to hot and cold zones provided by heatmap analysis
– Optimizing labor and maintenance costs
– Excluding under-performing products
– Enhancing marketing strategies through the analysis of events and promotional activities
– Increasing sales and profit margins of products from insights provided by heatmap analytics
Self-checkout, the automated future – no more queues
Computer vision, deep learning, and AI are taking the self-checkout a step further by eliminating the need for manual barcode scanning. These advanced systems automatically recognize and bill the customer based on the products selected utilizing computer vision and AI technology. The automated systems include image and video processing, robust feature extractors, object detection, and object counting. Some of these systems even incorporate facial recognition technology to recognize individuals and assign charges to their accounts.
A few benefits of automated self-checkouts
– Fast and convenient in-store self-checkouts ensure the growth of store attendance, the checkout conversion rate, and the average shopping cart price, increasing overall store profits
– Reduction in losses due to checkout shrink, attracts more customers, and enhances customer-retailer relationships
– Encourages store management responsiveness allowing staff to engage with more service-oriented activities in the store
Amazon’s smart store, Amazon Go, uses computer vision-powered facial recognition cameras that monitor the products taken from the shelves and placed in the shopping cart. When the customer leaves the store, the appropriate charges are applied to their Amazon account. Apart from Amazon Go, many retail outlets are opting for smart technologies that allow their customers to pay for products without a traditional checkout.
One such example is McDonald’s. The fast-food giant introduced self-service kiosks in 2017. These kiosks are the touch screen kiosks that allow customers to scroll through their menu and place orders without interacting with staff, creating a smooth and streamlined experience for the customer.
Smart product information management
A product information management (PIM) system is a centralized system that manages product detail like descriptions, properties, categories, and attributes in real-time in the retail store. A smart PIM system includes detailed answers for customer queries, customer reviews, and customer data to improve personalization. Further, the computer vision and deep learning-powered PIM system uses facial recognition to keep track of customers and their purchasing behavior for sending automated targeted product discounts and promotions.
A computer vision-powered PIM will
– Create a holistic persona for the buyer by detecting the objects in images or the videos that the customers engage with
– Improve in-store and warehouse product management, providing more time for employees to spend on customer engagement activities
– Facilitate efficient inventory management operations based on geographical locations, product features, and customer segments
– Allow more personalized services through a better understanding of customer preferences
– Promote better business decisions by illuminating product performance
Virtual mirrors for fashion
According to Deloitte, around 90% of retail sales occur in physical stores. However, to compete with the ever-increasing demand for online shopping, enhanced customer experiences and brand engagement are crucial for retail.
A smart or virtual mirror is a two-way mirror with an electronic display that simulates trying on garments or accessories where the display shows the customer various types of information. The mirrors are powered by computer vision and augmented reality technology.
Computer vision-powered cameras and scanners capture an individual’s size and shape, enabling the construction and display of a virtual mannequin mirror. These mirrors also recognize customer commands as they invoke gesture recognition algorithms. A virtual shopping cart allows the customer to add items if they like what they tried for later checkout and payment.
Microsoft Kinect offers an example of this concept providing a Windows-based virtual mirror that allows shoppers to engage with products and try them on. Further, Kinect supports shoppers trying variations of outfits via voice commands and ultimately product purchases. The platform utilizes social media for gaining additional marketing reach.
Computer vision-powered smart mirrors have the potential to benefit retailers by
– Enhancing customer retention and return-store visits
– Increasing in-store and online conversion rates
– Enable improved merchandising decisions through insights gained from customer preferences, choices, and decisions
Security and surveillance – redefined by computer vision
Many brick and mortar stores face shoplifters, refund scams, and general theft.
Dell estimates that US retailers lose nearly $50 billion a year in inventory, with most of the impact occurring at the point-of-sale (POS). The increasing accuracy of computer vision and deep learning improves the cost-effectiveness of intelligent retail loss prevention solutions. High-resolution cameras, data storage, and advanced AI-based deep learning software help detect behavior associated with inventory loss.
A smart surveillance solution with high-resolution cameras powered with computer vision and deep learning helps retailers identify and process facial images. This software emulates the cognitive processes of human vision. The analytics drawn from the store videos transform retail analytics by providing retailers insightful data on customer behavior.
Video analytics will
– Provide better operational and branding insights along with valuable customer intelligence
– Help retailers with understanding where and how much time customers are spending interacting with products and displays
– Provide real-time as well as offline insights on customer behavior interacting with the ads and displays
– Improve operational and administrative control by minimizing fraud and theft and help better manage inventory
Even though the advent of online retail has tremendously reshaped the retail industry, many people still prefer to visit retail stores as they want to try out products such as clothes, furniture, and cosmetics before they purchase them. Challenges associated with offering personalized shopping experiences and excellent customer service, whether brick and mortar or online, are more effectively addressed leveraging artificial intelligence and computer vision technology.
Companies are transforming their customer experiences by adopting computer vision that allows retailers to speed up operations like payments, shelf management, and inventory management. The technology integrated with Internet of Things (IoT) devices monitor stores, spot suspicious behavior, and deter theft.
Computer vision has come a long way from merely categorizing images to recognizing faces and adding AR/VR capabilities. Thus, today the scope and application of computer vision transcend almost every industry – from defense to manufacturing to healthcare, retail, agriculture, security, and transportation.
If you would like to learn more about implementing computer vision in your retail business, send us your query to intellect2@intellectdata.com. Intellect Data, Inc. is a software solutions company incorporating data science and artificial intelligence into modern digital products with Intellect 2 TM. Intellect DataTM develops and implements software, software components, and software as a service (SaaS) for enterprise, desktop, web, mobile, cloud, IoT, wearables, and AR/VR environments. Locate us on the web at www.intellectdata.com.
1 Comment
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