Nobody likes waiting in lines. According to research, people spend from 3 to 5 days per year queuing up. That might add up to 6 months of waiting for things during a person’s lifetime!
Long queues at the supermarket cause shopper fatigue, decrease customer experience and result in shopping cart abandonment.
Although retailers turned so many business processes into exact science, queue management remains a mystery.
Just ask a store manager what is the average number of items scanned by cashier per minute and you will get a precise number.
Ask the manager how much time customers wait in line during peak hours on weekdays or what is the average size of the queue – and you will get a puzzled look in return.
Introducing Computer Vision Powered Queue Management Platform
Time to checkout is fundamental in optimizing retail store performance, as it affects so many performance indicators.
Token based queue management platforms can help quantify the wait times and customer numbers. However, they are sometimes ineffective in retail environments such as line management in grocery stores, reinforcing the importance of implementing effective queue management in supermarkets. These crowded retail environments require a different approach.
Enter the world of computer vision powered queue management software. Computer vision turns video footage into actionable business analytics.
The platform uses video surveillance cameras already installed at the checkout location and requires no extra hardware investment, as usually the checkout area is well surveyed.
The platform uses AI and machine learning algorithms to track individual customers until they checkout, identifying their wait time as well as the size of the queue at any given time. It can also identify cart abandonment actions, giving an exact estimate of revenue lost due to long lines.
The smart queue management platform brings numerous benefits for retailers.
Improve retail performance analytics
Video analytics driven queue management platform will help to estimate time-to-checkout at any given time.
The platform will automatically calculate the wait during peak hours, identify service bottlenecks when customer wait is the longest. The queue data will help establish a baseline for normal checkout operations, which will improve customer experience and promote customer loyalty.
Using effective queue management, a store manager can filter these queue results by time of day or day of the week, holiday periods, or filter events by the wait time. show all events when customer wait was longer than 5 minutes).
Implementing an effective queue system helps to identify outlier events and analyze them with corresponding video footage, it can greatly reduce customer wait times. By combining queue size with sales data, conclusions can be made on revenue lost due to long wait times.
Accurately identify shopping cart abandonment
Using video analytics, the queue management platform can accurately identify shopping cart abandonment actions.
The queue data can be correlated with average wait time and size of the queue line. if wait time is longer than 5 minutes, 10 carts will be abandoned per hour).
By adding sales data to the mix, the value of revenue lost can be estimated.
Improve employee shift scheduling
Cart abandonment numbers and longest wait to checkout analytics, gathered through our queue system, will provide insights on employee shift planning and ways to reduce customer wait times.
Maybe your retail store does not follow a simple pattern of peak hours. Perhaps a sell-out campaign resulted in increase of customer influx. Or maybe too many checkout counters are open when few customers are present.
AI queue management software will help to align your employee resources with the customer flow.
Improve customer experience
Customer service standards look great on paper. But to ensure that queue system protocols are followed to the letter in the real world is a different matter.
By improving employee resource planning and ensuring a quick checkout will result in better customer experience. Less time waiting for things – more time to enjoy them!
What’s next?
Harnessing Advanced Predictive Analytics
Advanced predictive analytics utilizing past traffic data are now a key component in the evolution of AI queue management systems.
These systems analyze historical customer traffic to predict future trends. This enables better preparation for peak times and optimal staff deployment during quieter periods, ensuring a consistent customer experience.
Integration with Omnichannel Retail Strategies
As retail increasingly adopts omnichannel strategies, AI queue management systems play a crucial role in linking online and offline experiences.
Customers can use a store’s app to view real-time queue lengths, helping them decide whether to visit or even book a slot to minimize waiting. This seamless integration boosts customer satisfaction and loyalty.
Enhanced Customer Journey Mapping
These systems now monitor the entire customer journey within a store, not just at the checkout.
By analyzing traffic flow through various sections, retailers can fine-tune store layouts, product placements, and promotional displays, leading to increased sales and improved shopping experiences.
Real-Time Alerts and Automated Adjustments
Store managers receive instant alerts about queue dynamics, facilitating swift adjustments.
For example, if a surge in customer numbers is detected, additional checkouts can open automatically, or staff can be reassigned to busier areas, ensuring efficient resource management.
Empowering Employees with Data
Employees now have access to real-time data via wearable devices or mobile apps, allowing them to respond promptly to shifts in store dynamics.
This empowerment that comes from implementing the smart queue system not only enhances efficiency but also boosts job satisfaction, as staff are better equipped to meet customer needs and improve the customer experience.
Customizable Customer Feedback Integration
The system includes customizable feedback options, enabling customers to provide immediate input about their shopping experience.
This instant feedback is invaluable for stores to continually refine their services and address issues promptly.
Enhanced Security and Privacy Compliance
Given the heavy reliance on video footage and customer data, advancements in data security and privacy compliance have been made.
Through an effective queue management system, retailers can now not only safeguard customer information but still gain valuable insights that improve customer loyalty.
Sustainable Queue Management
Modern AI queue management systems also emphasize sustainability. By managing customer flow more efficiently during less busy periods, stores can reduce energy consumption for lighting, heating, and cooling, contributing to a greener retail environment.
Future Trends and Developments
Looking ahead, AI technology is expected to integrate further with emerging technologies like augmented reality (AR) for virtual queuing experiences and more sophisticated predictive models using big data. The ongoing evolution of AI offers endless possibilities for enhancing retail operations and customer experiences.
Frequently Asked Questions
Conclusion
AI-powered queue management systems have evolved significantly from their initial purpose of managing lines.
They now serve as comprehensive tools that enhance every aspect of the retail experience, from predictive analytics to real-time operational adjustments, shaping the future of retail management and ensuring customers enjoy their shopping experiences with minimal time spent in queues.
Curious About The Above Solution?
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Vėjūnė Krašinskienė
Chief Operating Officer
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