实例探究 > How A Digitally Native Brand Drives Conversion In Its Physical Stores With RetailNext

How A Digitally Native Brand Drives Conversion In Its Physical Stores With RetailNext

公司规模
1,000+
地区
  • America
国家
  • United States
产品
  • RetailNext
  • Aurora IoT Sensor
技术栈
  • IoT Sensors
  • AI for Predicted Traffic Trends
  • APIs
实施规模
  • Enterprise-wide Deployment
影响指标
  • Cost Savings
  • Customer Satisfaction
  • Productivity Improvements
技术
  • 分析与建模 - 预测分析
  • 功能应用 - 远程监控系统
适用行业
  • 零售
适用功能
  • 商业运营
  • 销售与市场营销
用例
  • 零售店自动化
服务
  • 数据科学服务
  • 系统集成
关于客户
UNTUCKit is a men's retail brand founded by Chris Riccobono and Aaron Sanandres. The brand is known for its perfectly fitting untucked shirts that cater to all shapes and sizes. Initially starting as an e-commerce business, UNTUCKit expanded to physical stores due to high customer demand. Since opening its first store in SoHo, New York, in 2015, the brand has grown to 86 stores and plans to expand further. UNTUCKit is a data-driven company that values accurate and actionable insights to drive its business decisions.
挑战
Originally a direct-to-consumer brand, UNTUCKit faced challenges in obtaining comprehensive data for its physical stores. The data points were anecdotal and based on store managers' experiences, lacking baseline metrics to measure traffic and conversion accurately. This made it difficult to verify traffic and conversion rates reported by store managers, who often counted multiple groups of shoppers as one.
解决方案
UNTUCKit implemented the RetailNext platform to address its data challenges. RetailNext offers industry-leading accuracy in traffic data through its Aurora IoT sensor, which detects people ten times each second. The platform provides real-time data accessible via user interfaces and APIs, enabling store associates to make immediate decisions. RetailNext's actionable data allows users to access multiple dashboards for visibility into KPIs, leveraging AI for predicted traffic trends and automatic recommendations. The platform also offers high-resolution recorded video for independent audits and integrates seamlessly with existing systems like POS data and Workforce Management Systems.
运营影响
  • UNTUCKit established accurate baseline metrics for traffic, helping to identify and forecast peak periods. This allowed store managers to plan tasks during off-peak hours and optimize staff schedules.
  • The platform provided recommendations on staffing, enabling UNTUCKit to add or remove staff based on traffic data, thus maintaining stable conversion rates.
  • UNTUCKit adjusted store hours based on traffic data, extending hours in some locations to capture late sales and reducing labor hours in others to realize cost savings.
  • The RetailNext platform allowed UNTUCKit to benchmark store performance against industry trends and internal goals, identifying top performers for reward and recognition.
  • Store managers gained key insights into performance metrics, enabling them to implement recommended actions to improve results.
数量效益
  • UNTUCKit opened 86 stores since its first brick-and-mortar location in 2015.
  • The RetailNext platform detects people ten times each second for maximum tracking accuracy.
  • UNTUCKit realized significant cost savings by adjusting labor hours based on traffic data.

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