We live in an age where one-size-fits-all is a thing of the past. Customers now expect companies to understand their preferences, anticipate their needs and create experiences that feel uniquely theirs. According to a recent survey, 73 percent of respondents expect enterprises to understand their unique needs, and over 50 percent believe companies should anticipate them.1 Personalization, when done right, allows brands to connect with people as individuals. It’s no longer just about products; it’s about how these products fit into a customer’s life.
Personalization has shifted from a "nice-to-have" to a core strategy for engaging customers and building lasting relationships. At the heart of this shift is Artificial Intelligence (AI), which is enabling retailers to deliver experiences that surpass customer expectations. A recent survey revealed that more than 70 percent of US digital retailers believed that AI-led personalization and Generative AI (Gen AI) will impact their business in 2024 and beyond.2 In another retail survey, 91 percent of executives voted AI to be the top game-changing retail technology over the next three years.3
This article explores how retailers can unlock the potential of AI-driven personalization. It dives into a real-world example and underscores why the technology is quickly becoming the cornerstone of the modern retail experience.
Understanding Hyperpersonalization
With consumers constantly bombarded with offers and recommendations, cutting through the noise is challenging. Hyperpersonalization, powered by AI and Machine Learning (ML), addresses the challenge by taking personalization to the next level. Rather than targeting broad customer segments, hyperpersonalization allows brands to craft experiences tailored to the unique preferences and behaviors of each individual. Nike's 'Nike By You' platform is a prime example of how brands can offer AI-based hyperpersonalized experiences.4 By empowering customers to design and customize their footwear and sportswear, Nike taps into individual style preferences, enhancing customer engagement and delivering a unique shopping experience.
Imagine walking into a store where everything seems curated just for you. Your favorite colors, preferred styles and even items you’ve admired online are seamlessly brought to your attention. This is the promise of hyperpersonalization – the ability to create moments that feel personal and relevant at every touchpoint. Through real-time data analysis and predictive algorithms, retailers can now engage with customers on an entirely new level.
Hyperpersonalizing the Customer Journey
Today, customers want more than a transactional experience; they want a journey. With AI, retailers can enhance that journey by guiding customers toward products that match their preferences, making the shopping process feel effortless and intuitive.
For example, AI-driven tools like WNS’ Hybrid Recommendation Engine powered by AI and analytics suggest products that a customer might like based on their browsing history while anticipating what they might need next. By understanding their preferences and patterns, these systems create a more fluid, enjoyable shopping experience, whether the customer is online, in a mobile app or in a physical store.
Similarly, Sephora leverages AI through its 'Color iQ' technology to hyperpersonalize beauty recommendations.5 By using customer data to match skin tones with specific products and recommending makeup and skincare based on individual preferences and purchase history, Sephora creates a highly personalized shopping experience.
The benefits of hyperpersonalization are compelling:
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Deeper Customer Connections
Tailored recommendations help build stronger relationships, making customers feel understood and valued.
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Higher Conversion Rates
Personalized interactions translate to better engagement and higher sales.
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Increased Loyalty
When customers feel a brand understands them, they are more likely to return, fostering long-term loyalty.
Case in Point: How a Retailer Personalized Customer Engagement with AI & Gen AI
Let’s take a real-world example. One of our clients, a prominent retailer, faced a common challenge – while their overall sales were growing, they struggled to connect with customers on a personal level. While their marketing campaigns were reaching a broad audience, there was significant potential to better align with the unique preferences of their diverse customer base.
By harnessing the power of AI and Gen AI, we helped them develop a sophisticated recommender system that transformed their customer interactions. Here’s how we did it:
This solution powered key tangible outcomes for the retailer, including:
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Enhanced Engagement
Gen AI transformed e-mail campaigns, driving a 4x increase in Click-through Rates (CTR).
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Incremental Revenue
Generated USD 2 Million in sales.
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Operational Efficiency
Gen AI dramatically streamlined the content preparation process for marketing communications, reducing turnaround time by 96 percent – from one month to less than a day.
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Customer Satisfaction
Feedback from third-party customer surveys was overwhelmingly positive:
- 87 percent of respondents found the content easy to read.
- 85 percent trusted the recommendations, and 80 percent rated the content quality as good.
- 74 percent of customers found the recommendations highly relevant, highlighting the success of the personalized approach.
The Future of Personalization in Retail
As we look to the future, the possibilities for AI-driven personalization are vast. AI is constantly evolving, and so are the opportunities for retailers to connect with their customers more meaningfully. Here are a few trends that will shape the future of hyperpersonalization:
Language AI
With advancements in language processing capabilities, AI systems will gain a deeper understanding of customer needs, enhancing the responsiveness and efficacy of chatbots and virtual assistants in addressing inquiries and delivering support.
Hyperpersonalization
Leveraging advanced data analytics and AI, retailers will provide highly tailored recommendations based on individual preferences, behaviors and purchase history.
Enhanced Customer Journeys
As AI becomes more sophisticated, the ability to deliver highly personalized, contextually relevant experiences across all channels will become the new standard.
The journey toward hyperpersonalization is just beginning. As AI advances, the ability to create personalized, human-centric retail experiences will be the key to unlocking deeper customer relationships and driving long-term growth.
About the Author(s)
Paul Morrison is a Practice Lead for Manufacturing, Retail and Consumer Goods in Europe. He has over 25 years of experience working with clients to achieve their long-term transformational goals, particularly covering the outsourcing and GBS strategy, operating model design and technology-led change. Paul is an expert in digital strategy, adept at harnessing the full potential of automation, analytics and AI.
Aseem Nagar is a Senior Consultant at WNS, specializing in Retail and Consumer Goods. With over a decade of experience in customer experience and outsourcing, Aseem's expertise lies in delivering solutions that help clients reduce costs, enhance operational efficiencies and drive improvements in customer satisfaction, service quality and profitability.
Prashanth Chalapathy is a seasoned Retail Analytics leader with over 19 years of experience. He brings extensive expertise in harnessing data to inform strategic decision-making, specializing in loyalty analytics, customer insights, digital analytics and data-driven strategies. His work focuses on transforming retail operations, enhancing customer experiences and delivering measurable business outcomes.
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References
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E-commerce 3.0: The future of retail is hyper-personalized | Forbes
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How AI-powered personalization is transforming digital retail | GlobeNewswire
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Future of retail: Profitable growth through technology and AI | Deloitte
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How Nike is using AI to transform product design | Aim Research
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Sephora’s Color IQ shade matching technology inspires new immersive installation | Cision
Disclaimer: WNS has sourced the data from various publicly available websites. WNS is not responsible for the content or accuracy of any linked sites.