How computer vision and artificial intelligence can help the retail industry maximize the value of their brick – Times of India

The lockdown generated a wave of disruption across the retail industry, leaving many physical retailers scrambling to meet public demand. They had to pivot their focus on creating highly optimized digital shopping experiences and supply chains to compete against the e-commerce giants. This period of heightened competition led retailers to focus a disproportionate amount of their innovation budgets on refining their online shopping experiences. Now that footfall levels at their brick & mortar stores have recovered to pre-pandemic levels, we are seeing that the customer returning to the store is finding a large variance in the shopping experience between the brands physical and online shopping channels. In an era of commoditization, the consumer has made it clear that the in-person shopping experience of engaging with a brands physical footprint is still critical for them to remain loyal to the brand. However, retailers will struggle to retain their customer base unless they start delivering an equally frictionless shopping experience in their stores. To catalyze this journey of transformation, retail must embrace the benefits of data-driven artificial intelligence (AI).

Unlocking in-store analytics data with computer vision

To deliver an optimized in-store shopping experience, retailers need to radically transform the way they operate their stores. To do this effectively, they need to adopt a data-driven approach where they micro analyze the customer conversion funnel to learn what bottlenecks are present in each of their stores. The only way to do this in a scalable manner is by adopting AI. There are several AI tools that an organization can adopt, but the most promising one that can deliver near term value for retailers is computer vision. This field of computer science focuses on replicating parts of the human vision system by enabling computers to identify and process objects, images, and videos in the same way that humans do. Vendors use a combination of proprietary algorithms and a real-time inference pipeline with deep learning to identify objects in a physical space and analyze their behavior and movement to predict outcomes and drive success. With the AI engine continuously analyzing these variables, it empowers both store managers and executives with insights on how they can make their retail business more efficient and profitable.

Decentralized data-drive decision making

Large retailers have struggled to objectively assist their store managers with granular insights on how they should manage each of their stores. This happens as executives drive most of their strategic decisions on a centralized level based on one dimensional data set such as point-of-sale and loyalty data. However, now with computer vision the retailers can get access to a much deeper set of shopper insights. By leveraging the video footage from their existing CCTV cameras, they can measure store visitor counts, traffic flow patterns throughout the store, segment visitors by their shopping duration, time of day and even demographics. The AI engine then analyses which of these variables corelate to maximized conversion rates and then provides suggestions on how operators should optimize everything from merchandising, store layouts, operations, and labor scheduling.

To compete with the online shopping experience effectively, retailers can longer afford to implement regional or district level strategies. They need to understand the interplay of these variables on a micro store level. Once they have visibility of what is and what isnt working in each of their stores, the AI engine will provide a combination of real-time and prescriptive analytics on how each store needs to be run. The engine will continue to consistently A/B test store level strategies and will empower every store manager by simplifying their store operations and providing an enhanced in-store shopping experience.

Embracing AI to sweat your physical assets

With the continued growth of e-commerce, retailers are sitting at a crossroad where they need to decide if they will skew their balance sheet towards their online of offline retail strategies. The retailers that continue to operate their stores as they have in the past will face a slow death as they lose the loyalty of their customers. On the other hand, operators that adopt a culture of agile innovation for their physical assets in a similar manner to their online strategies will emerge as the dominant players in the retail landscape. Customers continue to remain loyal only to convenience and the brands that deliver the most frictionless shopping experience by leveraging tools such as computer vision will be able to effectively maximize the value of every square footage of their brick-and-mortar footprints.

Views expressed above are the author's own.

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How computer vision and artificial intelligence can help the retail industry maximize the value of their brick - Times of India