![\"Applications](\"https:\/\/solutionsreview.com\/marketing-automation\/files\/2022\/08\/Applications-of-AI-and-Computer-Vision-in-Retail-and-Beyond.jpg\")
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As part of Solutions Review\u2019s\u00a0Contributed Content Series<\/a>\u2014a collection of articles written by industry thought leaders in maturing software categories\u2014<\/span><\/span>Rohan Sanil, the CEO and Co-Founder of <\/span><\/span>Deep North<\/span><\/span><\/a>, shares insights into the ways AI and computer vision can help retail businesses.<\/strong><\/em><\/p>\n The past ten years have seen traditional retailers struggle to increase customer engagement and foot traffic in their physical locations. The Internet, the emergence of online merchants like Amazon, and the spread of the epidemic have dramatically altered the retail environment. So how can stores compete with their online counterparts\u2014and other brick-and-mortar businesses\u2014now that customers are returning to stores? Delivering individualized service, convenience, and other engagement characteristics is necessary to encourage purchases and loyalty.<\/span>\u00a0<\/span><\/p>\n The issue is that, unlike online rivals, physical retailers severely lack a clear view of their customers’ browsing and purchasin<\/span>g<\/span> habits. That could refer to how long a customer must wait in line before purchasing the in-store path-to-purchase.<\/span>\u00a0<\/span>Technology can empower retailers<\/a> to gain data-rich insights once only available online to use their in-store environments better to meet shoppers’ needs and run their stores more efficiently and effectively. These include artificial intelligence (AI) and computer vision<\/a>.\u202f<\/span><\/p>\n First, it’s essential to understand the difference between sensor analytics\u2014commonly used today in the retail environment\u2014and computer vision. Sensor analytics is based on the use of physical sensor devices in-store. These work by converting stimuli such as movement or sound into electrical signals, which are converted to code and then processed by computers.<\/span>\u00a0<\/span><\/p>\n Computer vision is a field of AI that focuses on replicating the capacities of human vision. Computer vision takes sensor analytics a step further, as anything one’s eye can see can be analyzed. It trains computers to interpret and understand the visual world as humans do. For example, sensors may determine whether a person has walked into a store and an aisle and even identify spills that could negatively affect the shopping experience.<\/span><\/p>\n Physical retailers can use AI and computer vision with their on-site store camera infrastructure to understand their customers and how they behave while ensuring customer privacy. With these technologies, retailers can obtain real-time insights for decision-making so they can positively affect key metrics like in-store (and back-of-house) operations, labor planning and allocation, and overall consumer experiences. Retailers can do this through more effective product merchandising and marketing, staff optimization, and other efforts to drive in-store conversions, happy customers, and <\/span>sizable<\/span> cost savings.\u202f<\/span>\u00a0<\/span><\/p>\n Specifically, the following are <\/span>six applications of AI and computer vision in retail and how they can be used to impact the in-store environment positively:<\/span>\u00a0<\/span><\/p>\n With these technologies, retailers can determine metrics around the number of people walking into and out of a store and the total number of people in a store.<\/span>\u00a0<\/span><\/p>\n AI and computer vision can enable retailers to determine characteristics like customer age range, gender, and the people who made more than one trip to the store on a single day.<\/span>\u00a0<\/span><\/p>\n With this functionality, retailers can understand heatmaps\/the number of entrances into a zone. They can also determine the length of time spent in-store and the time spent in a specific store zone.<\/span>\u00a0<\/span><\/p>\nSensor Analytics Versus AI and Computer Vision<\/span><\/b>\u00a0<\/span><\/h3>\n
The Use of AI and Computer Vision In-Store<\/span><\/b>\u00a0<\/span><\/h3>\n
Footfall Analytics<\/strong><\/h4>\n
Customer Demographics and Repeat Visitors<\/strong><\/h4>\n
Customer Journey<\/strong><\/h4>\n
Queue Management<\/strong><\/h4>\n
![](\"https:\/\/solutionsreview.com\/marketing-automation\/files\/2019\/02\/marketing-automation-bg-speedbump.jpg\" "\\"Marketing")
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