Artificial intelligence is more than a buzzword in retail – it’s the driving force behind next-generation customer experience. From first touch to fulfillment (and everything after), rich data and predictive algorithms help deliver more personal and profitable experiences across digital, physical and blended buying channels.
How are today’s leading-edge brands and retailers taking advantage of modern AI technologies?
Discovery
Image recognition: The combination of computer vision and visual search algorithms create powerful possibilities for AI-driven product discovery. From a customer snapping a photo with their phone to find visually similar products to interactive applications showcasing products similar to past purchases in a customer’s profile, AI makes digital and physical shopping more “human.”
Facial recognition and beacons: Advancements in facial recognition technology can gauge customer sentiment when browsing and engaging with products in-store. Beacons can measure shoppers’ dwell times in various departments and interact with their mobile apps.
The ability to stitch 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, in-store insights can be applied across digital journeys, including e-shop and email merchandising.
Experience
As more mobile devices ship with native AR capabilities, augmented reality is becoming a standard offering in verticals like furniture, fashion, beauty and even B2B manufacturing. The ability to visualize a product's look and dimensions within a physical space, or virtually “try on” products help bridge the divide between digital and physical experience.
Where AR and AI collide, you get augmented intelligence. AR enables shoppers to turn 2D images to 3D to best visualize products in their homes, while AI serves visually similar products that complement their in-home style (and fit the dimensions of their empty spaces).
Conversion
Rich profiling: Today’s shopper has instant access to competitor pricing from anywhere. Showrooming (trying products in-store with intent to buy online) and webrooming (comparison shopping across digital retailers) are entrenched behaviors – and some consumers exhibit these behaviors more frequently than others.
Enriching customer profiles with “consumer genome” data across channels will help retailers identify which customers are most likely to convert at full price, versus those that would most profitably convert with a discount, and just showrooming. While cross-sell and upsell suggestions can help build bigger baskets, they can also distract and hurt conversion for shoppers less receptive to them. Predictive analytics can help retailers tailor their digital selling and pricing strategies at a 1-1 level, even matching new and unidentified buyers to “lookalike segments.”
Fulfillment
Inventory management: Omnichannel retailers can use AI to capture efficiencies in inventory and fulfillment. AI can select stock from the closest proximity to a shipping address, or from the best locations to reduce split shipments. Likewise, combining inventory with in-store sales velocity data also saves in-store sales. Fulfilling online orders from stores with excess inventory and slower turnover ensures hot products stay in store locations where they’re most popular.
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 retail chatbot interactions will reach 22 billion chats and save $439 million in support costs globally by 2023. Today’s shoppers are not only comfortable with chat-based messaging, but most prefer it for round-the-clock visibility into order tracking info, account balances, return processes and more.
Retention
Predictive loyalty: Most retail loyalty programs are one-to-many, meaning every participant collects points in the same way, and can redeem points for the same rewards. Some loyalty programs effectively segment based on customer lifetime value, loyalty “tiers” or other factors. Few provide truly one-to-one personalized perks.
Predictive analytics and consumer genome 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 and mobile apps. and even retail partners to reward more than just dollars spent.
AI will unlock the future of retail with data serving as the new capital pivoting next generation shopping experience. Data-driven, automated technologies are continuously enhancing every touchpoint in the buyer’s journey, transforming the way shoppers browse, buy, and behave over their lifetime relationship with brands and merchants.
It is imperative for companies worldwide to invest in next-gen technology across enterprise network, to ensure consumers continue to enjoy a seamless, memorable, and uninterrupted omnichannel experience regardless of how they choose to shop.
(The author is Chief Executive Officer of Infosys Equinox)
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