E-commerce is becoming more popular among customers. This was brought to light once again during COVID-19. Queues, long considered an unavoidable part of brick-and-mortar shopping, may be effectively controlled with the use of Computer Vision and AI.
Smart queue management technologies are being used by merchants to enhance the physical shopping experience. Queue management systems may reduce wait times, reduce cart abandonment rates, and improve customer satisfaction. So, how does it work, and why should you give it a go at your company?
In-store CCTV cameras monitor the queueing areas as part of the Link Retail Queue Management system. As a result, our property video analytic software processes real-time video material from the cash desk cameras. Shopper activity in a predefined wait location is also observed and examined promptly to assess customer service performance. The AI-based prediction engine in Link Retail’s queue monitoring cameras can track a wide range of variables.
The following are some of the metrics that it can track:
● Number of entries to the queue area
● Average service time
● Average dwell time
● Abandonment rate
● Cashier presence
Building long-term connections with customers are all about making them happy. Every company owner’s goal is to give their consumers high-quality service in this way. Time, on the other hand, is the most valuable and irreplaceable resource we have. Customers’ desire to purchase is lessened when they are forced to wait in long queues. As a result, queue desertion rates will be surprisingly high. How many people wait in line at the checkout counter is a critical part of queue management. To guarantee that customers in line are receiving quality service, this queue management system monitors customer service levels in real-time. The key to a successful queue management implementation is timely and accurate communication of backlog levels. Because of this, staff should be notified and cautioned of severe queuing occurrences, such as when there are too many or too few individuals present in wait areas.
Our queue analytics are predicting the outcomes of customers’ wait times! AI-powered monitoring alert retailers about wait line bottlenecks before they occur.
2. Dwell & Service Time
Our powerful video processing techniques enable us to assess both client dwell time and the average service time of the cashier.
3. Cashier Detection
The cameras automatically identify the presence of checkout staff. The store owners will appreciate this information, as would use for our forecasting.
4. Abandonment Rate
Retail queue monitoring cameras can instantly identify when a consumer exits the queue line from the rear.
Using the Link Retail Queue Management System, you can see exactly how many people are waiting in line and how long they’ve been there. Assigning new cashiers in real-time is made possible by the system’s predictive alerts. Customer happiness and employee efficiency may both be enhanced via our system’s use of real-time technologies. With the aid of our queue management technology, the company owners may fast optimize service quality at the same time minimizing personnel expenses.
● With the aid of queue management technologies, businesses can effortlessly match current resources with customer demand.
● The average service time statistic measured by retail queue management systems may be used to determine service performance.
● Real-time operational advice, such as assigning new cashiers or shutting down unused ones, is made available to store owners.
● The prediction system sends alerts quickly.
● Retailers may compare historical queue records to identify service bottlenecks throughout the whole chain.
Queuing issues are prevented before they occur thanks to our queue management technology! In addition to detecting incidences of queuing as early as 30 minutes in advance using Link Retail’s people counting and sector analysis data, the queue management system also allows for the early detection of delays. Queue and counter cameras are used by Link Retail’s queue prediction program to evaluate whether or not high or low queue density occurrences are likely shortly.
Additionally, the algorithm may also generate longer range forecasts such as daily or weekly. Our queue prediction engine is built on a property AI model that has been honed using real-world queueing situations as examples. The alerts created by the system are immediately transmitted to the merchants. In this manner, providing an appropriate number of cashiers will maintain the queue occupancy levels in an ideal stage.
To know more about Link Queue Management, contact us here.