Leveraging Predictive Analytics for Flawless In-Store Journeys

According to Gensler's 2024 Design Forecast, experiences are no longer either/or; they're AND. Blending convenience and engagement during every touchpoint is critical, which is why over 60 percent of customers switch to a different brand following a poor experience.

Engaging displays and immersive audio capture shoppers' attention, with 42 percent reporting that they pay attention to video and audio messages delivered in-store, leading 37 percent to purchase. By harnessing predictive analytics and proactive maintenance, retailers can ensure flawless retail experiences that keep customers returning.

Predictive Maintenance in Action

According to Salesforce data, 70 percent of customers switch to a competitor when encountering technical issues or dissatisfaction, highlighting technology's critical role in influencing consumer choices. With so much at stake, retailers need solutions to keep in-store tech running smoothly.

Predictive maintenance, essential for preempting disruptions in the customer experience, relies on proactive data collection, analysis and monitoring. Without enough data, predictive maintenance lacks the insights to accurately anticipate equipment failures and schedule preventative measures.

To gather more data, retailers should incorporate sensors on in-store assets such as digital signage, audio systems and interactive kiosks to monitor parameters like runtime hours, temperature changes, error codes and maintenance history. Another solution is adopting a centralized CMS with the software infrastructure to monitor all these devices simultaneously. This continuous stream of performance data is then fed into advanced analytics systems.

Sophisticated analytics software plays a pivotal role in deciphering this influx of data, uncovering patterns and flagging emerging issues. For instance, analytics may reveal that a specific projector model’s bulb fails approximately every 3,000 hours or that certain store locations encounter significantly more audiovisual errors than others. These insights construct predictive models that accurately forecast when devices require service, rather than adhering to generic time-based maintenance schedules.

Retailers can use real-time equipment monitoring and remote diagnostics to detect early performance degradation, while analytics-driven insights can help streamline maintenance workflow and anticipate workforce requirements. Managed services providers can also offer peace of mind and additional support in implementing and managing these predictive maintenance systems through expertise in integration, ongoing monitoring, maintenance and tailored training for optimal use.

Unlocking the Value of Predictive Maintenance

Retailers that adopt predictive maintenance strategies can reap significant cost savings and efficiency gains with the support of managed services providers. Predictive insights can optimize maintenance technician hours, and proactively addressing issues minimizes downtime and expenses related to equipment failures. Additionally, leveraging predictive analytics for preventative maintenance can extend equipment’s lifetime, reducing capital outlays on new purchases. Early identification of inefficient energy usage allows retailers to make changes that decrease utility bills and enhance overall energy efficiency.

Moreover, predictive strategies enhance the customer experience by ensuring seamless, uninterrupted in-store interactions. To leverage these advantages, retailers can take the following steps:

• Install sensors on in-store equipment to gather comprehensive performance data.
• Deploy analytics systems to detect patterns and emerging issues.
• Develop or collaborate with a trusted provider to create data-driven predictive models that accurately forecast maintenance needs.
• Enable real-time monitoring and automated alerts to address potential failures proactively.
• Use insights from analytics to optimize the allocation of maintenance resources.
• Continuously refine predictive models as additional data becomes accessible.

With seamless systems, retailers can provide immersive brand experiences that captivate customers and foster lasting brand loyalty. Adopting a data-driven approach empowers retailers to transform maintenance into a strategic function that optimizes operations, keeping your desired retail experience frictionless and memorable.

Jaime Bettencourt is senior vice president, global account management and marketing at Mood Media, an in-store media solutions company dedicated to elevating the customer experience.