2024 Retail Trends: Adapting to the Shifting Data and Analytics Landscape

Author: Andrew Simmons

As we step into 2024, the retail industry finds itself at the cusp of transformation. From the challenges of adjusting to a new world post-pandemic to the profound reshaping of supply chains and evolving customer expectations, the retail industry has been on a roller coaster ride in recent years. However, new technologies and AI options offer retailers opportunities to adapt, innovate, and thrive.


In this 2024 trends blog, we’ll explore the multifaceted changes that are shaping the retail industry and how retailers are harnessing data, analytics, and AI to meet the demands of today’s customers while establishing a competitive edge.


Explore the major trends impacting retailers this year and the strategies to navigate change. 


Trend #1: Setting a data foundation for analytics/AI readiness 

In 2024, a prominent trend in the retail industry will be the modernization of existing data infrastructure to prepare for analytics and AI use cases.


There are a multitude of driving factors. First, in the competitive environment, retailers are pursuing operational efficiency, cost reduction, and enhanced collaboration with partners – all of which require detailed data tracking and analytics. At the same time, they are increasingly looking to leverage data-driven insights and automation to elevate customer experiences, fine-tune marketing strategies, and make informed decisions. 


In addition, current economic challenges have intensified the importance of strategic cost decisions. To do so, retailers need a comprehensive understanding of the ROI of each initiative, which requires a strong data foundation to track and evaluate.


As a result, retailers are expected to make substantial investments in modernizing their data strategies, instilling robust data governance practices, and adopting more collaborative and decentralized data mesh frameworks. These investments are expected to deliver the following benefits:


  • Modern data architectures fuel faster, more accurate, and more comprehensive analytics that allow retail leaders to better understand their own business operations and respond dynamically to changing market conditions.   
  • Strong data foundations position retailers for success in analytics and AI, ensuring they have the essential infrastructure and data needed to fuel data exploration and train AI/ML models, ultimately enhancing their competitiveness and ability to serve their customers.  


Trend #2: Harnessing opportunities from generative AI 

Another significant trend in the 2024 retail landscape will be the increasing focus on generative AI. This trend is expected to gain momentum because it addresses several pressing retail challenges. 


Many retailers feeling the impact of rising labor costs are exploring cost-effective ways to increase automation and reduce the burdens of routine tasks on their workers. There are a variety of applications for generative AI in alleviating the labor shortage, from IT to customer support. In addition, ongoing supply chain disruptions have underscored the urgency for resilient and adaptable supply chain solutions, which can be achieved with generative AI.


In 2024, we will see an increasing number of retailers turning to generative AI for solutions across many different functions and operations. With generative AI, retailers will be able to:


  • Provide quick and accurate responses without human intervention to customer queries through AI-powered chatbots and call centers. 
  • Optimize product assortments, pricing strategies, and inventory management to augment merchandising and planning.  
  • Speed up the coding and development of applications and data solutions to improve operational efficiency.  
  • Enhance supply chain tracking, scheduling, and optimization to improve logistics and supply chain management. 


Trend #3: Increasing customer lifetime value with hyper-personalization 

In response to customer demands for seamless and personalized experiences, retailers are actively pursuing innovative approaches to scale and automate personalization and customer segmentation. Next year, we will see many retailers focusing on improving customer lifetime value (CLV) through hyper-personalization because tailoring experiences to individual preferences satisfies these demands and creates happy customers who keep coming back for more. 


Retailers will lean on hyper-personalization strategies to improve experiences for their customers and better target them with tailored marketing and advertising strategies. In doing so, retailers will rely on their data and analytics teams to build accurate, comprehensive, and scalable systems. This emphasizes the pivotal role of data and automation teams and the collaboration between technology, analytics, and customer engagement in driving revenue growth and customer loyalty.


These efforts enable retailers to:


  • Deliver highly individualized and relevant shopping experiences that create deeper, lasting connections with customers and meet their expectations. 
  • Generate personalized content and recommendations that resonate with diverse customers, enhancing revenue streams using generative AI.  
  • Maximize ROI on marketing and advertising investments to improve conversion rates and yield higher revenue through micro-segmentation and highly targeted messages and offers.   


Trend #4: Setting a new standard for demand forecasting 

The retail landscape is gradually returning to some pre-pandemic norms. However, the years following the global catastrophe are uncharted territory, making the data many retailers are currently using for demand forecasting unreliable and untrustworthy. In 2024, the retail industry will establish new standards for demand forecasting to optimize inventory, streamline supply chain management, and maintain cost controls.


To address the challenges and uncertainties of old forecasting models, retailers are looking for new ways to increase prediction accuracy. Adopting stochastic demand forecasting models will be a prime way to improve retail forecasts. Stochastic models enable a more comprehensive forecasting approach by providing a likelihood of each potential outcome. This offers retailers more information to make business decisions in an educated way and understand the broad array of possibilities – and their likelihood – before moving forward.


This new standard for forecasts will help retail businesses to:


  • Address uncertainty in demand by considering a range of possible outcomes rather than a single fixed forecast.  
  • Optimize inventory management by reducing carrying costs while ensuring products are available when needed.  
  • Improve supply chains by adjusting production, procurement, and transportation plans dynamically.  
  • Control costs by understanding the range of potential demand scenarios and making informed decisions regarding investments, staffing, and marketing strategies.  
  • Meet customer expectations more accurately by providing the right products at the right time.  


Charting the path forward: Navigating retail’s dynamic future

The data and analytics trends shaping the retail industry in 2024 represent a dynamic response to the changing landscape. These trends highlight the industry’s determination to adapt, innovate, and remain competitive in a post-COVID world.


From overhauling data strategies to adopting smarter forecasting models, retailers will embrace the possibilities of their data. The retail industry’s future hinges on its ability to leverage analytics and harness the full potential of data-driven insights and new technologies to meet evolving consumer demands and a dynamic market.


In pursuit of these trends, it is critical for retailers to recognize the invaluable role of data analytics experts as they will guide you through the intricacies of these trends. To learn more and receive tailored guidance on implementing the right data and analytics strategy for your business, get in touch with Wavicle’s data and analytics experts.