For the best experience, try the new Microsoft Edge browser recommended by Microsoft (version 87 or above) or switch to another browser � Google Chrome / Firefox / Safari

We all agree that consumer behavior changes often. This has made it extremely challenging for retailers to keep pace. Though management's focus has shifted to delivering cutting-edge online shopping experiences, creating rich, multichannel, hyper-personalized, and convenient buying experiences is certainly not child's play.

The narrative is further complicated by the evolution of customers into truly omnichannel shoppers. Most buyer journeys now traverse multiple channels, modes, and media. Even a single transaction could include small but crucial stops in mobile apps, websites, portals, and physical stores, with each helping move the buying decision forward.

In this dynamic era, retaining customers, staying relevant, and driving growth can be grueling, but not if you have the right technology in place. Read on as we shed light on how the retail industries can enhance customer lifetime value using Artificial Intelligence (AI) and Machine Learning (ML).

4 Most Shared Struggles of Customer Retention in Retail

Retaining customers has been a perpetual challenge. Let's look at the top struggles of customer retention in the retail industry. 

Brand Switching
Instant access to product and service information and competitive price points makes it so easy for customers to switch brands – with a simple mouse click. In fact, about 71% of consumers worldwide switched brands at least once in the past year.


The Balance - Acquire or Retain
The increasing focus on acquiring new customers causes most retailers to spend time revamping their acquisition strategies but not on their retention strategies. Despite the harsh reality that investing in new customers is 5-25 times more expensive than retaining existing ones.


Customer Segmentation
Improper customer segmentation makes it difficult for retailers to understand individual needs, wants, and preferences. And almost 63% of consumers expect businesses to know their unique needs and expectations.


Customer Service
Inefficient customer service is also a major cause of poor retention, with 58% of American consumers switching companies because of poor customer service.


5 Strong Reasons Why Customer Lifetime Value is Important

Today, the customer competition is harsh and expectations are changing. Customer lifetime value helps in assessing how much a customer is likely to spend over the lifetime of the customer relationship. Such insight helps retailers in:

The Right Strategic Mix 
Find the right balance in terms of the right mix of short-term and long-term marketing strategies. This helps in retaining customers and ensuring they get the most value out of each customer.

The ROI Impact 
Calculate the financial impact of marketing campaigns, initiatives, and other activities and assess their alignment with company goals.

The Value
Focus on customers that are more valuable than spending time acquiring or retaining customers with a lower value.

The Loyalty
Measure customer loyalty while effectively managing relationships that lead to increased profitability.

The Steady Cash Flow
Ensure repeat orders from customers already acquired. Curtail the costs of new customer acquisition and enable a steady cash flow. 

Data Collection Through Customer Journey - Where AI/ML Comes Into Play

For any retail business, it is essential to capture data at every touchpoint of the customer journey. Not just to deliver personalized products and services but also to drive higher retention rates and boost customer lifetime value. 

The retail ecosystem has become extremely complex. Customers rely on different devices and mediums to communicate with brands, engage in conversations, and make purchases. To that end, ensuring timely data collection throughout the customer journey helps build a 360-degree view of the customer - right from past purchases to current needs and future aspirations.

Technologies like AI/ML are reinventing the retail landscape by setting the stage for effective customer journey analytics. By analyzing customer behavior across touchpoints and over time, they help measure the impact of customer behavior on business outcomes.

How AI/ML Assists Customer Lifetime Value in Retail?

Using AI/ML and associated technologies like NLP, chatbots, RPA, image recognition, and reinforcement learning, retailers can:

  • Kickstart the right conversations, curate the right campaigns, and offer the right products – thus improving CSAT scores
  • Optimize inventory levels and ensure products meet expectations and are delivered at the right place and at the right time
  • Capture subtle changes in customer behavior, preferences, and satisfaction and use intelligence to bring order to retail processes 
  • Improve demand forecasting while also making accurate pricing decisions and optimizing product placement
  • Track data continuously from multiple online and offline channels, leading to more informed strategies 
  • Gain a comprehensive real-time view of stores, shoppers, and products and make data-driven supply chain and inventory decisions
  • Power chatbots to interact with customers and provide quick answers to simple queries and questions 

Xoriant's Digital Expertise in Retail

Retailers need to stay relevant and grow in this dynamic scenario. Companies need to adopt cutting-edge retail technology solutions to get deeper insights into their customers, deliver delightful shopping experiences, and discover expanded business models along the way. 

Xoriant enables retailers to reimagine the modern retail experience. Leveraging modern digital technologies like AI/ML and through continuous efforts toward multi-cloud adoption and application modernization, Xoriant's digital expertise in retail and long-standing experience with leading retail solutions empower retailers to: 

  • Unlock key insights hidden in raw business data originating from multiple sources, including CRM, ERP, and other enterprise applications, real-time inventory, shop and warehouse sensors, and more. 
  • Leverage proprietary accelerators and deep relations with leading technology partners to capture, analyze, and transform data into insights at digital business speed.
  • Connect business processes to customer touchpoints and enable a holistic view of the business to drive deeper customer engagements, and make better, data-driven decisions. 
  • Make the most of technology advancements to drive operational agility and enable business innovations like intelligent price management, hyper-personalization, inventory management, expansion of shopping channels, customer loyalty programs, and more. 
  • Enable rapid access to fact-based insights for maximizing customer lifetime value along with transforming business performance, optimizing inventory, and boosting customer experience. 
  • Build omnichannel customer experiences and offer products, content, and campaigns that are carefully curated for different devices, channels, and touchpoints.  
  • Deliver superior customer experience with more efficient retail operations and a better understanding of customer behavior via real-time cognitive analysis that is integrated with data from ERP systems.

A Retail Customer Success Story

For a top US-based luxury fashion retailer, Xoriant recently built tailored AI/ML-based customer lifetime value models to enable actionable insights. The retailer, with 6 million+ customers and 4.5 billion+ USD in annual sales, was looking to apply a systematic data-driven approach, demonstrating the value the business can generate from their sales and marketing efforts. 

Xoriant, with its strong domain knowledge and expertise, proposed a solution that leveraged industry-recognized and widely accepted statistical and AI/ML modeling methods in the development, validation, and deployment of the solution to enable the customer's end goals. Xoriant's CLV models enabled the luxury fashion retailer to:

  • Design and evaluate sales strategies that create sustainable value for the long-term
  • Segment premium, loyal, and various other customer segments on metrics such as revenue per customer, brand affinity, acquisition cost, and more.
  • Predict customers' future purchasing power, transactional behaviors, and likely actions accurately.
  • Enable personalized targeting of customers in marketing campaigns, leading to increased overall sales and better customer retention.
  • Forecast customer spend for the next fiscal, resulting in increased accuracy in future revenue generation estimation.

Read The Customer Success Story

Way Forward for Retail Industry

AI and ML is the way forward to deliver a seamless, intuitive, and consistent ​user experience across every device in retail business. Investing in these next-gen technologies can help your retail organization to constantly collect and analyze customer data from different sources, dig deeper into customer needs, and deliver personalized experiences – all while exceeding customer and market expectations. 

By ensuring incredible customer experiences, AI/ML offers several opportunities to grow revenue, accelerate innovation, and build smart operations — all of which can help differentiate you from your competitors.

Check out our related PDF: CLV Models

Looking to elevate and improve customer lifetime value with Xoriant?

We're Here to Help

Get Started

arrow arrow
Think Tomorrow
With Xoriant
triangle triangle triangle triangle triangle
Is your digital roadmap adaptive to Generative AI, Hyper cloud, and Intelligent Automation?
Are your people optimally leveraging AI, cloud apps, and analytics to drive enterprise future states?
Which legacy challenge worries you most when accelerating digital and adopting new products?

Your Information

6 + 4 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.

Your Information

1 + 3 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.

Your Information

13 + 3 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.