How AI Slashed Checkout Wait Times by 57.66%: The Case Study

In an ever-evolving retail landscape, customer satisfaction and operational efficiency are paramount.

EasyFlow, a queue management and MLOps solutions provider, embarked on a trial to determine if their AI-powered platform could fine-tune the efficiency of checkout processes at two store locations of one of the largest retailers in Central and Eastern Europe.

The trial aimed to gauge whether AI technology could elevate an already efficient operation to even greater heights of excellence.

The Challenge

The retail chain already boasted highly efficient staff allocation and queue management practices, yet they aimed to explore the potential of AI to optimize these processes further. Specifically, they sought to:

Minimize cashier idle time
Prevent queue formation incidents
Enhance customer wait times
Improve staff resource allocation during COVID-19 safety measures
“The retailer already had highly efficient processes for in-store staff resource allocation and queue management practices. The trial was aimed at discovering whether AI software can tune up the efficiency from ‘very good’ to ‘perfect’”
Simas-Jokubauskas CEOSimas Jokubauskas – CEO of EasyFlow

The Solution

EasyFlow’s AI-powered Queue Management platform leveraged Computer Vision and real-time video data from in-store security cameras to bring about these optimizations.

The solution encompassed several key features:

Real-Time Queue Measurement:
EasyFlow’s advanced platform automatically identified products through scanning, eliminating the need for manual selection from customer pick lists.
Predictive Footfall Analysis:
The system promptly alerted store employees about potential scanning discrepancies during the checkout process.
Automated Queue Notifications:
The platform sent proactive notifications to employees based on potential queue formations or checkout closures due to traffic fluctuations.
Efficient Staffing Optimization:
The platform balanced out overstaffing and understaffing situations by reallocating staff resources across the store.

Implementation and Results

The trial was conducted over two months at two store locations, with 18 manned checkout counters at both sites.

During the trial:

Cashier Idle Time Reduction:
AI reduced cashier idle time by an impressive 57.66%, equivalent to over 2.5 man hours per store per day;
Queue Formation Prevention:
The software prevented 237 queue formation incidents, saving an average of 2.25 hours in customer wait time per day;
COVID-19 Operational Support:
The trial’s timing during the pandemic ensured smooth operations with lower employee headcount, in line with safety measures;
Future Forecasting:
EasyFlow’s solution provided not only real-time data but also future visitor traffic and staffing requirement forecasts, enhancing operational planning.
Extended Applications:
The platform’s capabilities extended beyond queue management, including real-time shelf stock level monitoring, planogram compliance monitoring, and automated product identification at self-checkout counters.
Say the software detects that 50 shoppers entered the store in the last few minutes. Yet only two checkout counters are opened. It is very likely that the queues will begin to form in a couple of minutes. The platform then sends an notification to head cashier and employees on duty that additional checkout counters should be opened, giving staff enough time to react before the shoppers head to the checkout”
Simas-Jokubauskas CEOSimas Jokubauskas – CEO of EasyFlow
Queue Management Analytics 1
Queue management analytics dashboard


The trial validated EasyFlow’s AI-powered Queue Management platform’s ability to optimize an already highly efficient retail operation.

The results showcased substantial reductions in cashier idle time, prevented queue formations, and improved customer satisfaction.

“The software helps to balance out overstaffing and understaffing situations allocating the available staff resources throughout the store. As the trial was conducted during April and May when additional safety measures were in-place due to COVID-19, this helped to ensure smooth operations with lower employee headcount”
Simas-Jokubauskas CEOSimas Jokubauskas – CEO of EasyFlow

The platform’s capacity to provide real-time and future forecasting data highlighted its potential to drive operational efficiency and enhance customer experience across various facets of retail.

As the retail industry continuously seeks innovative solutions to enhance operations, EasyFlow’s platform stands as a testament to the transformative power of AI-driven technologies.

By harnessing the insights derived from in-store security cameras, retailers can achieve operational excellence while maintaining customer satisfaction even in challenging times.

“Retailers have abundant video data from in-store security cameras. This information can be harnessed to drive operational efficiency. Most importantly, Computer Vision solutions are simple to integrate, do not require any additional hardware investment, they do not rely on additional data from ERPs or other business software, and can quantify real world in-store intelligence in similar fashion as Google Analytics does for the digital realm”
Simas-Jokubauskas CEOSimas Jokubauskas – CEO of EasyFlow

For more information on how EasyFlow’s Queue Management Solutions can revolutionize your retail operations, contact us today. Experience the future of retail efficiency and customer satisfaction with EasyFlow.

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