How modern retailers are leveraging AI at every stage of the buyer’s journey

How modern retailers are leveraging AI at every stage of the buyer’s journey

Artificial intelligence is more than a buzzword in retail – it’s the driving force behind the next generation of customer experience. From first touch to fulfillment (and everything after), rich data and predictive algorithms help deliver more personalized and profitable experiences across digital, physical and blended purchase channels.

How are today’s leading brands and retailers leveraging modern AI technologies?


Image recognition: The combination of computer vision and visual search algorithms creates powerful opportunities for AI-powered product discovery. From a customer snapping a photo with their phone to find visually similar products to interactive applications that showcase products similar to previous purchases in a customer’s profile, AI is making digital and brick-and-mortar shopping more “human.”

Facial recognition and beacons: Advances in facial recognition technology can measure customers’ emotions as they browse and engage with products in-store. Beacons can measure customers’ time spent in various departments and interact with their mobile apps.

The ability to aggregate data across engagement channels provides a rich opportunity to personalize in-store experiences. Digital displays can offer one-to-one product recommendations and offers. In turn, store insights can be applied across digital journeys, including e-commerce and e-commerce.


As more mobile devices come with built-in AR capabilities, augmented reality is becoming a standard offering in verticals such as furniture, fashion, beauty and even B2B manufacturing. The ability to visualize a product’s appearance and dimensions in a physical space, or practically “try on” products helps to bridge the gap between digital and physical experience.

Where AR and AI collide, you get augmented intelligence. AR enables buyers to turn 2D images into 3D to best visualize products in their homes, while AI serves up visually similar products that complement their home style (and fit the dimensions of their empty spaces).

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Rich profiling: Today’s shopper has immediate access to competitor prices from anywhere. Showrooming (trying on products in store with the intention of buying online) and webrooming (comparison shopping across digital retailers) are entrenched behaviors—and some consumers exhibit these behaviors more often than others.

Enriching customer profiles with cross-channel “consumer genome” data will help retailers identify which customers are most likely to convert at full price, versus those that will convert most profitably at a discount, and showroom only. While cross-selling and upselling suggestions can help build bigger baskets, they can also distract and hurt conversions for customers who are less receptive to them. Predictive analytics can help retailers tailor their digital sales and pricing strategies on a 1-1 level, even matching new and unidentified buyers to “lookalike segments.”


Inventory management: Omnichannel retailers can use artificial intelligence to capture efficiencies in inventory and fulfillment. AI can select warehouses from the closest proximity to a delivery address, or from the best locations to reduce split shipments. In the same way, you save sales in store by combining inventory with data about speed in store. Fulfilling online orders from stores with excess inventory and slower turnover ensures that hot products remain in store locations where they are most popular.

User support

Chatbots and virtual agents: Advances in natural language programming (NLP), machine learning and computer vision are helping chatbots evolve into near-human assistants. A recent study by Juniper Research showed that chatbot interactions in retail will reach 22 billion chats and save $439 million in support costs globally by 2023. Today’s customers are not only comfortable with chat-based messaging, but most prefer it for 24/7 visibility . to order tracking information, account balances, return processes and more.

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Predictive Loyalty: Most retail loyalty programs are one-to-many, meaning each participant accumulates points the same way and can redeem points for the same rewards. Some loyalty programs effectively segment based on customer lifetime value, loyalty levels or other factors. Few offer truly one-to-one personal benefits.

Predictive analytics and consumer genomic data enable next-level loyalty experiences. Retailers can not only offer more attractive incentives to individuals, but also track non-transactional engagement across physical and digital journeys, third-party social apps and mobile apps. and even retail partners to reward more than just dollars spent.

AI will unlock the future of retail with data acting as the new capital driving the next generation shopping experience. Data-driven, automated technologies continuously improve every touchpoint in the buyer’s journey, transforming the way shoppers browse, buy and behave throughout their lifetime relationships with brands and merchants.

It is critical for companies worldwide to invest in next-generation technology across enterprise networks to ensure consumers continue to enjoy a seamless, memorable and uninterrupted omnichannel experience regardless of how they choose to shop.

(The author is the CEO of Infosys Equinox)

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