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Artificial Intelligence (AI) Trends Shaping the Retail Industry

Today’s retail landscape is built on a digital foundation - and words like AI, data, personalization and convenience are the new competitive advantages.

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Jagrati Rakheja
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AI Trends in Retail Industry

Attributed By Samik Roy, Country Head (Dynamics), Microsoft India.

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With the rise of e-commerce titans like Amazon, today’s retail landscape is built on a digital foundation - and words like AI, data, personalization, convenience and unified commerce are the new competitive advantages.

As a consequence of this digital ecosystem, consumers have an entirely new set of behaviours and expectations when it comes to shopping. With on-demand services like Amazon Prime offering next-day delivery and 24/7 gratification, shoppers have a much higher bar than their coupon-collecting and bargain-hunting predecessors. They not only consider convenience and flexibility absolute musts but also crave personalized service and experiences.

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As if these shifts weren’t difficult enough to contend with, digital and physical retailers alike are facing unprecedented pressures on growth and a need for profitability. Retailers also must navigate this amid the harsh consequences of inventory at overcapacity, new technology investments and operational costs for expanding their e-commerce channels, which typically operate at a loss.

For retailers to succeed, they must rethink the way all their channels work together. The next retail paradigm shift will see offline and online shopping converge into a single, seamless channel. Retailers of all sizes need to be one step ahead of their customers’ needs and their competitors’ next innovation, requiring agility, adaptability and a digital transformation mindset.

AI is the backbone of digital transformation. AI-powered retail experiences will become essential for retailers to meet their customers’ needs, no matter when, where and how they choose to shop. As a blanket term, AI refers to any number of cognitive software that can act, sense and build upon stores of information.

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Although it’s been used to power backend processes, AI is becoming a more sophisticated tool to power differentiated services, curate products and even facilitate a more present, human connection between retailers and their customers.

Microsoft Introduction: Amplifying Human Ingenuity with Intelligent Technology

AI has the potential to empower us all to accomplish more, drive better business outcomes and achieve breakthroughs that redefine what’s possible. From changing the transportation landscape to discovering new ways of protecting the planet, from reinventing healthcare to connecting with customers, the opportunities are endless.

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Applying AI to The Retail Experience: Why Now?

Today’s dynamic retail industry is built on a new covenant of data-driven retail experiences and heightened consumer expectations. But delivering a personalized shopping experience at scale - that is relevant and valuable - is no easy feat for retailers. As digital and physical purchasing channels blend together, the retailers that can innovate their retail channels will set themselves apart as leaders.

Because they allow retailers to drive game-changing efficiencies and extract actionable analyses from their consumers, AI and cognitive services will be the tools of the trade in this new retail frontier. This accelerated operational pace will position brands as true customer service leaders—from the homepage to the sales floor, and back again. 

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AI Trends Shaping the Retail Industry

  1. Adaptive Homepage

Mobile and digital portals are recognizing customers and customizing the e-retail experience to reflect their current context, previous purchases and shopping behavior. AI systems constantly evolve a user’s digital experience to create hyper-relevant displays for every interaction

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  1. Dynamic Outreach

Advanced CRM and marketing systems learn a consumer’s behaviors and preferences through repeated interactions to develop a detailed shopper profile and utilize this information to deliver proactive and personalized outbound marketing - tailored recommendations, rewards or content

  1. Visual Curation
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Algorithmic engines translate real-world browsing behaviors into digital retail by allowing customers to discover new or related products using image-based search and analysis - curating recommendations based on aesthetic and similarity

  1. Guided Discovery

As customers look to build confidence in a purchase decision, automated assistants can help narrow down the selection by recommending products based on shoppers’ needs, preferences and fit

  1. Conversational Support

AI-supported conversational assistants use natural language processing to help shoppers effortlessly navigate questions, FAQs or troubleshooting and redirect to a human expert when necessary - improving the customer experience by offering on-demand, always-available support while streamlining staffing

  1. Personalized Storefront

Intelligent retail spaces recognize shoppers and adapt in-store product displays, pricing and service through biometric recognition to reflect customer profiles, loyalty accounts or unlocked rewards and promotions - creating a custom shopping experience for each visitor, at scale

  1. Emotional Response

By recognizing and interpreting facial, biometric and audio cues, AI interfaces can identify shoppers’ in-the-moment emotions, reactions or mindset and deliver appropriate products, recommendations or support - ensuring that a retail engagement doesn’t miss its mark

  1. Operational Optimization

AI-supported logistics management systems adjust a retailer’s inventory, staffing, distribution and delivery schemes in real time to create the most efficient supply and fulfillment chains, while meeting customers’ expectations for high-quality, immediate access and support

  1. Responsive R&D

Deep learning algorithms collect and interpret customer feedback and sentiment, as well as purchasing data, to support next-generation product and service designs that better satisfy customer preferences or fulfill unmet needs in the marketplace

  1. Demand Forecasting

Mining insights from marketplace, consumer and competitor data, AI business intelligence tools forecast industry shifts and make proactive changes to a company’s marketing, merchandising and business strategies

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