AI In Retail: Optimizing Customer Experiences & Boosting Sales

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In an era where the influence of artificial intelligence is growing rapidly in our daily lives, its impact on the business landscape is nothing short of transformative. According to a recent Deloitte report, by 2025, 20% of leading global retailers will embrace distributed AI systems for comprehensive improvements across sales, marketing, supply chains, and operations. Additionally, around 45% of marketing leaders intend to invest in GenAI within the next 12-24 months.
The pivotal role of AI in shaping strategies, enhancing efficiency and fueling innovation across industries is undeniable. In this article, we will focus on how AI stands to revolutionize the retail sector, reshaping customer experiences and redefining industry standards.

AI’s Impact on Retail Experiences

In Gartner’s 2023 Annual CIO and Technology Leaders Survey, approximately 50% of retail professionals reported that they have actively utilized AI technologies in their everyday operations. AI has taken the retail sector by storm, unveiling a myriad of benefits for the industry. Let’s explore some of these AI applications and the possibilities they unlock for innovative retail businesses.

Personalized shopping experiences

AI algorithms can seamlessly sift through vast amounts of customer data—like preferences, purchase history and online browsing behavior—to offer tailor-made recommendations that resonate with individual shoppers. Some of the benefits of AI-powered personalized shopping experiences include:
  • Virtual showrooms & in-store navigation with product visualization
    AI in retail allows customers to navigate stores virtually, helping customers locate products quickly and efficiently. It facilitates seamless navigation within physical stores using augmented reality. The ability to virtually try-on products further enhances customer engagement, providing a virtual platform for customers to visually experience and test products before making purchase decisions. This immersive approach not only transforms the traditional retail setting but also contributes to a more interactive and personalized shopping journey.
    Use case: Lowe’s LoweBot is a portable assembly of cameras and sensors that captures and evaluates store-related data, guides customers to navigate the stores and also helps manage inventory.
  • Analyzing customer preferences AI-driven algorithms explore past purchases, liked products and abandoned carts, offering retailers a nuanced view of individual customer preferences. This deep understanding provides the foundation for creating a personalized and curated shopping journey.
  • Real-time personalized product recommendations
    Dynamic AI algorithms create and modify product suggestions based on customers’ real-time browsing activity, ensuring product recommendations align not only with past preferences but also with the most recent interests. According to the Twilio Growth Report 2023, 24% of participants leverage AI to automatically generate personalized product recommendations.
    Use case: Stitch Fix’s personalized styling is powered by content-based filtering. It leverages AI algorithms to curate fashion recommendations for customers.
  • Micro-segmentation
    AI can evaluate vast amounts of customer data, identify shopping patterns and create more homogeneous groups based on shared traits. This micro-segmentation enables precise targeting and helps retailers cater to the unique needs of each micro-group. This facilitates enhanced personalized customer experiences, customer satisfaction and loyalty.
  • Predictive suggestions
    By analyzing browsing behaviors, such as pages visited and time spent on each page, AI can help retailers anticipate future customer needs. It uses this data to offer proactive product suggestions that align with customers’ evolving preferences.
  • Omnichannel customer experience
    AI seamlessly integrates data from various channels—online, in-store and mobile—to provide a comprehensive view of each customer’s interaction with the brand across different touchpoints, create a unified customer profile and deliver a cohesive personalized marketing experience across all engagement nodes.
    Personalized experience platforms are specifically designed to compile data and deliver customer-centric experiences. These tools leverage advanced technologies like data analytics and automation to create tailor-made interactions for each user.

Customer service with chatbots & virtual assistants

AI-powered chatbots and virtual assistants are equipped with advanced capabilities, including natural language processing and machine learning algorithms. This enables them to deliver highly personalized customer interactions, offer real-time support, answer queries and provide guidance throughout the shopping journey. The result is a more efficient and satisfying retail experience, enhancing customer engagement and facilitating seamless interactions. AI integration in chatbots has now become a widely embraced concept, so much so that 38% of Twilio Segment Growth Report 2023 participants are either already using – or intend to use – AI-powered chatbots for their businesses.
Use case: Amazon’s AI-driven Alexa is a voice-activated virtual shopping assistant that is functional on its apps, mobile and Echo devices.

Automated check-out systems

Cashier-less stores and AI-powered processes enable customers to effortlessly scan and pay using computer vision and sensors that automatically add items to their cart. These types of automated checkout systems significantly boost retail efficiency. AI algorithms identify and track products, adjust for changes, update inventories and apply correct pricing to help deliver secure and simple transactions. With AI, customers can enjoy a frictionless, contactless and expedited checkout experience, contributing to a more efficient and modern retail environment.
Use case: Walmart’s Scan & Go ensures a seamless check-out experience through four simple steps—open the Walmart app, scan items while shopping, hit the check-out button and scan the QR code for payment.

Inventory management

AI is revolutionizing inventory management by optimizing stock levels, enhancing supply chain efficiency and minimizing waste for retailers. This transformative approach not only reduces operational costs but also enhances customer satisfaction by maintaining a consistent supply of in-demand items. Through AI algorithms and data analysis, retailers can precisely predict demand and ensure optimal inventory levels. By leveraging AI for inventory management, retailers can prevent overstocking and excess inventory, reduce unsold items, lessen the need for markdowns or clearance sales and more.

Customer loyalty programs

AI can help optimize customer loyalty programs by gathering relevant and precise customer data. Through meticulous evaluation of these data, AI helps identify individual preferences, browsing and purchase history and other behaviors. This level of insight into each customer enables retailers to craft personalized loyalty programs, offering tailored rewards and incentives. By aligning offerings with individual preferences, AI boosts the overall impact of the experience, fostering brand loyalty among the customers.
Use case: AI-driven Starbucks Rewards tailor incentives and promotions based on a customer’s specific preferences and purchase history.

Fraud detection & security

To improve fraud detection and security, AI can analyze real-time data for anomalies, seamlessly detecting, tracking and preventing fraudulent activities during transactions. It can employ adaptive machine learning models, biometric authentication and encryption to safeguard transactions, thereby protecting customer data. Additionally, AI tackles non-scans and shrinkage issues that can cost retailers an estimated $45 billion annually. With the help of computer vision and advanced algorithms, AI can evaluate video feeds to identify unscanned products, sharing real-time alerts to checkout employees.
Use case: PayPal uses machine learning to assess customer legitimacy in real-time, considering various factors like device, email and transaction data, detecting high-risk activities and anomalies before they affect the customer.

Material’s AI expertise sits at the intersection of technology and customer centricity

In today’s dynamic retail landscape, adopting an AI strategy is essential for shaping exceptional customer experiences. Still, the future of retail is not just about technology, but about how brands can use it to make every human interaction more meaningful and personalized. No matter where you stand in your AI adoption journey, Material’s experts can guide your next steps to ensure the technology is serving your customers’ human needs while delivering measurable value. Interested in learning more about how we can help you create and manage a seamless AI customer experience in your business? Reach out today.