Case Study: Enhancing Retail Technology Performance and Decision-Making Through Data Visibility
How a Major Global Retailer Transformed Operations with Real-Time Data and Automation
A leading global retailer, operating thousands of stores worldwide, faced a critical challenge: after investing heavily in digital signage and display technology across its locations, the organization lacked insight into the effectiveness of these assets. Without clear visibility into performance metrics, the company struggled to define what success looked like, making it difficult to plan for the future, innovate, or justify further investments in technology.
The core issue centered on visibility. The retailer needed a way to monitor the status of their in-store technology and measure content effectiveness to make informed business decisions and maintain their primary communication objectives. Previously, the absence of reliable data meant decisions about display types, content strategies, and technology investments were based on assumptions rather than evidence.
To address these concerns, the retailer collaborated with American Sound to implement the Utelogy Platform across its North American stores. This deployment offered comprehensive, real-time reporting on all digital signage players, TVs, and AV infrastructure. With these tools, the company could now track the operational status of every asset at all times, analyze historical uptime data (for example, over the past 60 days), and assess the effectiveness of displayed content.
Beyond visibility, the retailer also struggled with a significant service delivery issue. Previously, when equipment failed, employees would manually report incidents, resulting in slow, reactive ticketing and repair processes. It often took weeks to resolve issues, disrupting store operations and customer experience.
The introduction of Utelogy modernized this process. Automated monitoring and alerts enabled the team to identify and resolve about 80% of incidents remotely, dramatically reducing the need for on-site service visits and cutting associated costs. Most notably, the average service level agreement (SLA) for Meantime To Resolution (MTTR) improved from approximately 3.5–4 weeks to less than two days – from incident creation (often through automated alerts) to full resolution. This remarkable reduction in downtime led to significant improvements in operational efficiency and employee satisfaction.
With this newfound data visibility and automation, the retailer gained confidence in the effectiveness of their technology investments. The company could now identify which environments, locations, and store types performed best and understand the factors contributing to their success or underperformance. These insights empowered leadership to make strategic decisions about future investments, real estate expansion, and content strategies based on reliable, actionable data, capabilities that were previously out of reach.
