AI in Retail: Redefining Customer Segmentation and Personalization at Scale 

AI is revolutionizing the retail buyer journey by placing the customers in the driver’s seat. AI is quietly rewiring how people shop, enhancing experiences, and reshaping the entire retail playbook. 

According to a McKinsey report, companies that excel in customer personalization generate 40% more revenue from these activities, compared to the average players. Artificial Intelligence helps you decode customer behavior and sentiment at the micro-level, enabling personalization at scale.  

In this blog, we will delve deeper into how brands are utilizing AI to optimize processes and create personalized customer experiences. We will also see how InXiteOut, a trusted AI and data analytics partner, is helping top-tier retailers transform customer journeys with AI.  

AI in retail personalization    

Personalization begins with one critical step: effective customer segmentation.  

There are different segmentation models for grouping customers by distinct features. From basic demographic segmentation to RFM segmentation to more advanced behavioral segmentation, these models help target customers with tailored services and targeted communications.  

AI-powered customer segmentation uses sophisticated algorithms to identify patterns in data and cluster customers into distinct groups.  

By using machine learning, predictive analytics, and real-time data processing, AI can create precise retail customer segments that evolve with changing customer behavior.   

There are several machine learning algorithms, like K-Means clustering, DBSCAN, BIRCH, SOM, etc., which are used for different types of customer segmentation problems.   

Why use AI for customer segmentation?     

Conventional methods for customer segmentation often involve:  

• Manual steps, and are limited in the data type and volume they can process.   
• They are typically not designed for real-time analysis, which is required in omnichannel retail services such as session-based targeting, in-store digital integration, dynamic loyalty programs based on live actions, immediate retargeting, etc.  
• Traditional analytical methods are time-consuming and have a high chance of error. 

In addition, legacy systems are not designed for predictive customer segmentation, which limits their ability to deliver actionable insights.  

AI segmentation, on the other hand, has made it possible to: 

• Get comprehensive insights into the customers by efficiently using a combination of different segmentation models with high precision in minimal time.     
• Leverage advanced predictive analytics along with real-time data to identify and acquire new customers, while forecasting future behaviors and recommending actions based on historical insights for existing customers.  

This enables the creation of more accurate customer segments, leading to stronger engagement through personalized experiences and targeted messaging, ultimately driving higher ROI of marketing spends. 

Application of AI in retail 

Many global retail brands have already integrated AI into their system to optimize processes and deliver a personalized buying journey.  

Here’s how AI is transforming retail:   

• Personalized product recommendations 
• AI chatbots and virtual shopping assistants 
• Smart in-store experiences 
• Marketing and promotions 
• Demand forecasting 
• Supply chain optimization 

Personalized product recommendations  

AI algorithms can analyze customer preferences, purchase history, and behavior from both online and offline touchpoints, along with more granular data points like the season and real-time behavior for accurate product recommendations.  

Take Amazon for example. The global retail giant has actively enhanced its recommendation engine with generative AI. In September 2024, the company announced that AI now refines product suggestions on its site and in marketing emails.  

AI chatbots and virtual shopping assistants  

Natural Language Processing-based AI chatbots and virtual shopping assistants are changing retail shopping experiences by providing instant support, streamlining orders, and grievance processing. These virtual assistants guide customers through their purchase journeys, ensuring an end-to-end personalized experience.  

Mastercard’s “Shopping Muse”, a generative AI chatbot for fashion shopping, is a perfect example. Michael Kors deployed it in mid-2024 to recreate the ‘in-store shopping experience’ on their website. The shopping assistant translates customers’ everyday language into tailored product recommendations from Michael Kors’ catalog.    

Smart in-store experiences  

AI-enhanced Augmented Reality (AR) is transforming in-store shopping by offering virtual ‘try-on’ mirrors.  Brands are using these smart mirrors in-store for an immersive shopping experience without the hassle of actually trying the product.  

Sephora’s smart mirror lets customers try makeup shades virtually, in their Times Square store. Smart mirrors installed in JD Sports’ flagship stores allow shoppers to virtually try on the Nike collection. Smart mirrors exemplify how AI is enhancing real-world retail.  

Marketing and promotions  

From targeted content to promotional campaigns and offer recommendations, Artificial intelligence can optimize all retail marketing communications according to customer preferences, delivering a hyper-personalized customer journey with maximum return on marketing spend.   

Target, the US-based retail chain, uses AI to personalize loyalty offers. It developed a “Contextual Offer Recommendation Engine” (CORE) for its Target Circle program. CORE employs machine learning (contextual multi-armed bandit models) to analyze customer transactions and behavior data and then generate customized spend-based bonus deals for each member.  

Demand forecasting  

By analyzing sales data, customer behavior, market trends, and other dynamic factors, AI models can accurately predict demand for a single or multiple products across one or several points of sale. This helps retailers optimize inventory according to the predicted demand and prevent stockouts or overstocking.  

Learn how IXO helped a global retailer develop and implement a cutting-edge AI-based demand forecasting solution to optimize their Direct-to-Retail business model.  

Supply chain optimization  

AI can efficiently optimize supply chains through inventory monitoring, shipment tracking, and supplier management. It can help identify bottlenecks by providing an end-to-end view of the process.  

Increased visibility reduces cost through process optimization and any chance for errors, helping in better management and seamless operations. AI enables retailers to anticipate disruptions, adapt to shifting demand, and build more resilient, responsive supply chains. 

Case in point

How IXO helped a global retailer deliver a hyper-personalized customer journey with AI 

 One of our clients, a global retail brand, was facing a common problem. Their marketing messages and spending didn’t deliver the expected results. With customers spread across different regions, they needed to create campaigns that better matched customer preferences. 

We helped them build and deploy a powerful AI recommendation engine. It made customer communication more relevant and helped them spend their marketing budget more effectively, delivering quick and visible results. 

Here’s a glimpse into our solution:  

Here are some of the benefits delivered by the solution within 2 months of deployment:  

• More than ~10% increase in content engagement rates across multiple markets. 
• ~12% cost savings through optimized and targeted discounts.  
• ~30% boost in email engagement rates over existing solutions.   
• 2X uplift in email click-to-open rate 
• A steep increase in customer satisfaction is projected by third-party customer reviews. 
• Increased sales performance across key markets.  

Wrapping it up   

Artificial Intelligence holds huge possibilities in retail hyper-personalization, and the transformation has just begun. AI is evolving, and so are the opportunities to use it.  

With the ability to analyze vast datasets, adapt in real time, and anticipate customer needs, AI is setting a new retail standard.  

Author

InXiteOut