Digital twin in retail: technologies, use cases, and added value

Digital twin in retail is a virtual replica of physical products, processes, or systems, providing a comprehensive digital model that supports data-driven insights into product placement and availability. This technology helps retailers optimize store layouts, streamline inventory management, and enhance decision-making. However, creating accurate digital twins involves significant challenges, such as the need for large volumes of real-time data and labor-intensive manual data entry. Taking advantage of the full potential of this technology often involves collaboration with an experienced retail software development services provider. Let's explore the diverse use cases of DT in retail.

Digital twin in retail use cases

Digital twin in retail is primarily aimed at enhancing store operations, inventory management, customer experience, and strategic decision-making. Here are the main applications:

1. Store layout and design optimization Digital twins enable retailers to create virtual replicas of store layouts, allowing them to test and optimize floor plans, product placement, and traffic flow. This helps maximize space utilization, improve the customer journey, and make data-driven design adjustments without disrupting the actual store.
2. Inventory and stock management By creating a digital twin of inventory, retailers can track stock levels in real time, predict demand more accurately, and manage restocking efficiently. This reduces instances of overstocking or stockouts and ensures that products are available when and where customers need them.
3. Supply chain and logistics management Digital twins offer a complete view of the supply chain, enabling real-time tracking of product movements from suppliers to the store. This application helps retailers identify bottlenecks, optimize delivery schedules, and ensure efficient logistics operations, especially critical for perishable goods.
4. Customer experience enhancement Through AR-enabled digital twins, customers can virtually interact with products or see additional product information, such as reviews or styling tips, in-store. This can be particularly useful for complex purchases like electronics, furniture, or fashion, where customers benefit from detailed insights and personalized suggestions. A digital twin of a customer simulates and predicts customer behavior, enhancing engagement and satisfaction.
5. Predictive maintenance for store equipment For stores with complex equipment (e.g., refrigerators, HVAC systems, self-checkout kiosks), digital twins can monitor equipment health, predict potential failures, and schedule maintenance proactively, ensuring minimal disruptions and improved customer experience.
6. Personalized marketing and promotions Digital twins and data analytics allow retailers to understand customer preferences and shopping patterns. This data can inform personalized promotions, optimize product recommendations, and tailor in-store digital displays, enhancing targeted marketing and increasing sales conversions.
7. Employee training and simulation Retailers can use digital twins to create realistic training simulations for store associates, enabling them to practice customer interactions, restocking, or handling in-store processes. This provides hands-on learning in a risk-free environment, improving customer service and operational efficiency.
8. Omnichannel fulfillment and click-and-collect optimization Digital twins assist in optimizing order fulfillment strategies, especially for omnichannel models where customers order online and pick up in-store. They provide real-time insights into inventory levels and fulfillment operations, helping streamline the process and reduce customer wait times.
9. Customer behavior analysis and in-store analytics Digital twins enable retailers to analyze in-store customer behavior, such as which sections are most visited and where customers spend the most time. This insight helps adjust store layouts and merchandising strategies and enhance product visibility to improve overall sales.

By applying digital twin technology across these areas, retailers can improve operational efficiency, enhance customer experience, and make informed decisions leading to growth and competitive advantage.

Value added by digital twin in retail

The digital twin technology market is projected to expand at a CAGR of 42.1%, reaching $53B by 2028. This growth highlights the significant potential of digital twins for retailers, particularly in optimizing strategic inventory management and merchandise planning. There are following benefits of digital twins in retail:

Product twin: enhancing product lifecycle management

Retailers are constantly pressured to accelerate portfolio rotation to meet evolving consumer demands. Digital twins address this challenge by integrating customer insights and in-service data, enabling faster product development and efficient platform reuse. This technology allows retailers to simulate and monitor product performance before launch, reducing risks and enhancing customer satisfaction.

Logistics twin: streamlining the supply chain

Retailers face the challenge of shortening lead times and enhancing operational effectiveness in their warehouse and distribution systems. Digital twins address these issues by enabling demand- and event-driven operations, optimizing efficiency, and streamlining processes. By integrating processes and resources, this technology helps reduce bottlenecks and improve inventory management, ensuring smoother operations.

Asset twin: optimizing asset utilization

Retailers face the challenge of optimizing output and total cost of ownership (TCO) while ensuring high asset availability and flexibility. Digital twin in retail industry addresses these needs by serving as a single source of truth, facilitating data-centric collaboration for enhanced asset management. This technology improves infrastructure utilization, minimizes maintenance costs, and increases uptime, enabling retailers to achieve greater operational efficiency.

Implementing digital twins in retail benefits businesses by enhancing operational efficiency, improving customer experiences through personalized insights, optimizing supply chain management, and reducing costs through predictive analytics and real-time monitoring.

Read more: Digital twins in manufacturing: benefits, technologies and use cases

Technologies utilized by DT in retail

Implementing digital twins in retail requires a blend of advanced technologies to create, maintain, and visualize a synchronized digital replica of physical stores, products, and operations. Here are the key technologies commonly used:

1. IoT sensors and devices Real-time data from store assets, such as inventory, environmental conditions (temperature, humidity), and customer foot traffic, is collected by Internet of Things sensors. These devices enable continuous data flow between the physical and digital counterparts, helping ensure the digital twin reflects the store's current state.
2. Artificial intelligence and machine learning Data from digital twins is analyzed by AI and ML algorithms to generate actionable insights, forecast demand, optimize layouts, and enhance inventory management. In retail, computer vision models, like object detection and recognition, help identify products on shelves and monitor stock levels.
3. Augmented reality and virtual reality Interactive visualizations of digital twins are provided by AR and VR. In retail, AR enables in-store overlays for product information, while VR creates immersive virtual simulations of store layouts or inventory that employees or stakeholders can explore for training and optimization purposes.
4. Computer vision Often powered by deep learning models, computer vision enables real-time automated product detection, tracking, and recognition. It's critical to identify stock on shelves, monitor product placement, and create accurate virtual representations of store sections or displays.
5. 3D modeling and spatial mapping A virtual replica of the physical store, including its layout, aisles, and product shelves, is created using 3D modeling tools. Spatial mapping technologies, often found in advanced mobile devices, help convert 2D images into 3D representations and accurately locate objects in physical space.
6. Cloud computing and edge computing Cloud computing offers scalable storage and processing capabilities for the vast amount of data generated by digital twins. Edge computing enables real-time data processing closer to the store location, reducing latency and ensuring faster response times for critical applications.
7. Data analytics and big data platforms These platforms collect, process, and analyze the large volumes of data produced by digital twins, providing insights into inventory trends, customer behavior, and operational efficiencies. Big data platforms enable comprehensive data analysis, while analytics tools visualize these insights.
8. Simulation software Simulation tools allow retailers to test different scenarios in a virtual environment, such as optimizing store layout or assessing customer traffic patterns. These tools are particularly valuable in evaluating operational changes before implementing them in real life.
9. Geospatial technology and GPS Location tracking within the store for both products and customers is enabled by geospatial tools and GPS. This is useful for applications like customer navigation, wayfinding, and precise tracking of items within large stores or warehouses.

These technologies enable retail digital twins to deliver accurate, up-to-date insights and simulations, driving more efficient, data-informed decision-making across store operations, inventory management, and customer engagement.

Read more: Digital twins in healthcare: transforming patient care and operations

Wrap-up

For retailers, the unpredictability of shifting consumer behaviors and supply chain disruptions makes strategic planning more challenging and essential-this is where digital twins can provide a transformative solution. As digital twins gain traction, they offer tools to mitigate challenges like the bullwhip effect by turning vast data-such as past transactions, demand patterns, and external trends-into actionable insights. To make full use of this technology, collaborating with a skilled retail software development services provider is a must.