Brick-and-mortar retailers have faced immense pressure over the years—from the disruptive rise of e-commerce to the accelerated changes brought by the pandemic. However, a fresh wave of technological innovation is now reinvigorating physical stores. One of the key drivers of this resurgence is the increasing adoption of retail analytics, which is unlocking new opportunities for in-person shopping experiences.
If you're eager to explore how data is reshaping the retail landscape, read on as we break down five high-value use cases for retail analytics.
Retail analytics involves converting real-world business activities into measurable data to guide strategic decision-making. This encompasses insights into consumer behavior, supply chain dynamics, inventory status, and more. Retailers can put this data to work in various ways, such as:
While data can come from many sources, real-time information—often gathered through mobile apps and sensor technology—has proven especially powerful.
Adopting data-driven strategies can lead to remarkable improvements in performance. A survey spanning nearly 300 supermarkets, department stores, and e-commerce businesses revealed that:
These figures underscore how leveraging retail analytics can directly boost business outcomes.
Optimizing the in-store experience starts with understanding customer movement and interaction within the retail space. By leveraging behavioral analytics tools—such as those provided by platforms like Vera—retailers can:
This granular insight into customer behavior allows for a level of experiential design that was once only possible in digital environments, transforming the in-store experience into one that is highly responsive and personalized.
Online retailers have long benefited from personalized recommendations, and now, emerging technologies like augmented reality (AR) are extending this capability to physical stores. By analyzing historical purchasing data and real-time customer behavior:
For example, global brands such as Auchan have used simplified versions of these systems to successfully boost in-store foot traffic.
Effective inventory management hinges on striking the right balance between supply and demand. Today, advanced analytics empower managers to move beyond guesswork by:
Retailers like Kroger have harnessed in-house analytics to refine their inventory processes, illustrating the potential of data-driven stocking strategies.
Price remains one of the most influential levers in retail. Modern analytics tools can process a variety of inputs—ranging from cost of goods and competitor pricing to weather forecasts and real-time behavior—to:
Such predictive pricing strategies help ensure that retailers remain competitive while maximizing profitability.
Merchandising, which encompasses everything from promotional campaigns to product display optimization, directly impacts sales. By combining store-level data with machine learning:
This approach allows for rapid iteration on merchandising strategies, ensuring that investments in in-store promotions yield the best possible returns.
In today's competitive landscape, information is power. While digital-first retailers have long reaped the benefits of data analytics, advancements like AR are now leveling the playing field for brick-and-mortar businesses. Retailers can access up-to-the-minute data to refine store layouts, test marketing campaigns, optimize inventory, and much more.
For those ready to embrace the future, implementing retail analytics means leveraging platforms that integrate real-time data collection with actionable insights. Our cutting-edge AR platform is one such tool, driving the next generation of in-store data innovation and offering tangible growth opportunities.
By tapping into these high-value use cases, retailers can not only enhance the in-store experience but also drive significant business growth. Interested in learning how retail analytics can transform your operations? Reach out today to discover how our technology can help you unlock new levels of efficiency and customer engagement.