In many service areas, the number of tickets taken and the actual number of
people in the waiting area can differ greatly
Detailed insights into peak times and the relationship between tickets drawn and the actual number of people enable management to deploy staff more effectively. This avoids overstaffing and understaffing, and resources can be better allocated.
If people leave the waiting area due to overcrowding, this is recorded by the sensor data. Companies can therefore recognize when and why potential customers do not make use of the service, and take measures to reduce this behavior, such as reducing waiting times or increasing capacity.
With precise information about visitor flows, waiting times and customer behaviour, data-based optimization measures can be taken. This could lead to an improvement in service quality and shorter waiting times, which increases customer satisfaction.
The analysis of visitor flows and behavioral patterns can lead to the development of forecasting models. These models can help to plan staffing requirements in advance and thus avoid bottlenecks.
The integration of sensor data in cleverQ provides precise, data-based insights into visitor behavior and actual utilization. This enables companies to optimize personnel and resource management, identify lost customers and improve overall service quality.
The integration of the VC-3D Pro sensor in cleverQ enables precise recording of the actual number of people compared to the number of tickets taken. This allows companies not only to analyze exact visitor flows and peak times, but also to see how many people leave the waiting area without using the service. This enables data-driven decisions to optimize personnel management and resource allocation.
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