In the era of ‘phygital’ retail – with physical and digital channels interacting in new and complex ways – omni-channel integration ensures customers receive a consistent experience across all touchpoints, whether online, in-store or via mobile apps. Retailers must unify their data models and communication platforms to allow customers to start interacting in one channel and finish it in another without friction.

For example, Walmart^[2] employs an integrated inventory management system that monitors inventory in real-time across all its stores, enabling strategies such as Buy Online, Pick Up In-Store (BOPIS) and providing customers with convenient and flexible shopping options. Similarly, Sephora^[3] offers customers the option to try on makeup in-store or through the Sephora Virtual Artist app, blending online and offline experiences.

A leading UK retailer aiming to bridge in-store and e-commerce experiences collaborated with WNS to leverage a cloud-based Customer Data Platform (CDP). The CDP enabled a unified customer view by integrating online and offline interactions, significantly improving omni-channel experiences.

Augmented Reality (AR) represents a transformative form of hybrid customer interaction. It enriches the shopping experience by providing additional information and interactivity through devices or smart glasses. This bridges the gap between online and in-store experiences with product demonstrations, virtual try-ons and immersive brand storytelling.

For example, IKEA uses its IKEA Place app^[4] to allow customers to visualize furniture and other items appearing in their homes before purchasing. The app leverages 3D and AR technologies, allowing customers to virtually position furniture in various areas of their homes, including living rooms and bedrooms. This creates a realistic and interactive shopping experience. Warby Parker offers a Virtual Try-on feature^[5] that uses AR to show customers how different glass frames will look on their faces. This helps customers make better purchasing decisions without visiting a physical store.

AI-led chatbots and virtual assistants can manage customer inquiries, from answering common questions to offering detailed product information. These systems utilize Natural Language Processing (NLP) to grasp and respond to customer queries conversationally, improving the overall customer experience. The latest deployments of digital agents, working alongside the human team, are performing at a level that was not achievable in the past – faster, cheaper and better.

For example, Walmart’s AI-enabled voice shopping feature^[6] allows customers to link their mobile devices and home smart speakers to their Walmart account. Customers can then verbally state their desired items, and the system will recognize the request, identify the preferred brand based on previous purchases and add the item to the cart. Similarly, Sephora uses AI-powered chatbots^[7] to assist customers with product recommendations and answers to common questions, enhancing the shopping experience both online and in-store.

Moreover, Gen AI-powered knowledge assistants are revolutionizing the customer care landscape, enabling agents to deliver exceptional experiences with remarkable speed and efficiency. These intelligent assistants rapidly retrieve information from trusted sources such as internal documents, knowledge bases and past transactions, synthesizing accurate and coherent responses tailored to customers' queries. This capability enhances the quality of customer interactions while significantly improving operational efficiency by reducing response times.

Hyperpersonalization has become a cornerstone of modern retail as customers increasingly expect unique, relatable experiences that address their needs and preferences. Utilizing data analytics, automation and AI, retailers are offering personalized recommendations, targeted promotions and individualized customer service – on a scale and at a speed previously impossible.

Amazon, in many ways, defined this era of personalized shopping by leveraging advanced algorithms to recommend products based on customers' previous purchases and browsing behavior. However, Amazon goes beyond traditional personalization by utilizing its vast data resources to predict and pre-stock items in nearby warehouses even before customers place an order. This anticipatory shipping model enables faster delivery times and enhances customer satisfaction by reducing the wait time for popular items.

Similarly, a leading US retailer collaborated with WNS to harness a data science center of excellence to drive hyperpersonalization by predicting the next-best product a customer is most likely to engage with or purchase. By leveraging ML models and real-time customer behavior tracking, the retailer significantly enhanced customer engagement – improving marketing effectiveness and boosting profitability through personalized and timely offers.

Collaborating with a prominent grocery client, WNS utilized advanced analytics-driven customer segmentation, a customized hybrid recommender system and Gen AI-powered marketing to achieve hyperpersonalization. This strategic approach resulted in a remarkable fourfold increase in click-through rates and customer engagement.

Loyalty management programs are far from new. However, the strongest performers in retail have turned them into the heart of the customer experience, providing insights, enabling personalization, and driving retention and customer advocacy.

Running a next-gen loyalty capability is at the leading edge of CX, data, AI and analytics – increasingly connected with and turbocharged by the developments in hyperpersonalization. The best programs are the result of finely tuned and evolved strategy and design. For example, they involve sophisticated content strategies, move beyond simpler points-based systems to cash / checkout redemption, use gamification and expand into business-to-business despite the data challenges. Loyalty management implementation and operations lean on diverse best practices such as master data management optimization, CDP and campaign operations.

For instance, when a duty-free retailer saw its discount-based loyalty program eroding margins, WNS designed a new, cashback-based loyalty program to unlock immense revenue potential. This analytics-driven solution provided the retailer with a comprehensive view of its members’ demographic and psychographic profiles, enabling them to utilize a customer behavior framework to better plan and design campaigns. This approach drove active engagement and effectively monetized the program.

Digitization empowers but can also isolate. The human touch remains incredibly important for many memorable retail interactions, particularly for more complex and / or sensitive cases. As technology advances, balancing this becomes both easier and harder. It is easier because analytics and AI-powered functionality will become ever stronger – think Gen AI chatbots that will be nearly indistinguishable from human agents. It is more complex because customers may feel increasingly relegated to interacting with robots – particularly those who need empathy and authenticity. Every digital CX success story risks being derailed by a customer who feels cut off.

Retailers must balance ‘high tech’ with ‘high touch,’ incorporating new techniques and technologies without sacrificing personal interactions where they matter the most – in-store, over the phone or through other channels. Fortunately, leading retail CX providers are striking the right balance between change and innovation, aligning technology-driven change with their brand and values.

For example, WNS' EXPIRIUS CX model combines digital-first solutions with human-assisted services to improve customer experiences across direct-to-consumer channels like social media, apps, e-mail and web chat. This human-in-the-loop approach enhances customer satisfaction, loyalty and revenue.