RetailNext, the leading in-store traffic analytics provider used by 450+ of the world’s most loved retail brands, today released its comprehensive list of product updates from the past year, designed to enhance in-store analytics for retailers globally. The latest upgrades mark a significant milestone for RetailNext, empowering retailers with cutting-edge tools to elevate their in-store performance and optimize the shopping experience.

“2023 brought a wave of challenges for retailers, from rising theft to the evolving tastes of consumers driven by new spending habits and online shopping preferences," said Jason Luther, CTO of RetailNext. "Our mission this year was clear: keep our finger on the pulse of retail so we can better equip brick-and-mortar stores with tech and analytics just like their online counterparts—helping them do more with less."

Among the key enhancements, RetailNext:

• Overhauled its mobile app to expand data availability and accessibility for store teams. Available on both iOS and Android, the RetailNext app now provides a regional (multi-store) roll-up view, enabling corporate heads, district/region managers, and store managers to instantly monitor performance in their regions. This feature also offers insight into which stores and regions are performing well or need improvement compared to their peers, enabling targeted development and application of learnings across the fleet.
• Reinvented its asset protection offering with state-of-the-art video analysis tools. Intelligent PTZ (pan, tilt, zoom) controls, coupled with 360° views, ensure that employees can meticulously investigate incidents from every angle. Further advancements to the video player – including improved adaptive streaming, time localization, increased stability, and optimized playback capabilities – help retailers respond and recover faster from theft and other in-store incidents. 
• Expanded machine learning capabilities for Aurora, RetailNext’s proprietary AI sensor. Aurora fuses 3D imagery with deep learning for the most accurate people counting insights. With our most recent enhancement, retailers can now see analytics for foot traffic passing by the store with Aurora installed at a tilt, allowing them to understand capture rate and evaluate the effectiveness of window displays and greeters. 
• Introduced a traffic counting option which accounts for groups of people shopping together. This method utilizes RetailNext’s Aurora sensors to count groups of shoppers who enter or exit a store together within a specified time and distance as a single traffic event. This feature is particularly useful for retailers that define a group of shoppers, such as a family, as a single transaction opportunity, helping them to better assess conversion rates and other metrics. 

"Mizzen+Main created the first performance fabric dress shirt over a decade ago, and we're still growing as we offer a range of products that provide our customers with the comfort, style, and confidence they need,” said Bethany Muths, CMO at Mizzen+Main. “It’s important for people to experience the best Mizzen+Main has to offer when they visit our retail locations. With RetailNext, we can leverage in-store analytics to give that customer experience the full look and feel of our unique brand." 

"RetailNext has been an invaluable partner, helping us better understand consumer behavior,” said Joshua Tiedemann, Director of Retail Technology & Support at Trek. “Armed with RetailNext’s data, we have been able to make data-driven decisions that help guide the success of the business. In a rapidly changing retail landscape, RetailNext's agility has been a game-changer for our teams." 

In response to industry-wide challenges and customer demand, RetailNext's advancements over the past year directly tackle pressing issues faced by retailers—from rising theft and staffing challenges to tighter budgets driving the need for operational efficiency. In some instances, the learnings derived from RetailNext’s analytics helped retailers cut marketing expenses by 30% by trimming ineffective displays and materials. Its insights were also responsible for reducing labor spend by 30% across some stores by allowing detailed traffic analytics to guide staffing needs. Its enhancements to surveillance measures reduced investigation time by 75% and retail shrink by 10%.