Retail

How-AI-Slashed-Checkout-Wait-Times-by-57.66_-The-Case-Study

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

Retail, Case Studies / By /

The platform helped to reduce cashier idle time by 57.66% when measuring against the baseline, equaling to more than 2.5 man hours per store per day. The software also prevented 237 queue forming incidents, saving an average of 2.25 hours in customer wait time per day. The experiment was conducted for two months at two store locations of one of the largest retailers in Central and Eastern Europe with 18 manned checkout counters at both trial locations.

Shoplifters Target Self-Checkout Registers Amid Soaring Inflation

Shoplifters Target Self-Checkout Registers Amid Soaring Inflation

Business, Customers, Finance, Retail / By /

The platform helped to reduce cashier idle time by 57.66% when measuring against the baseline, equaling to more than 2.5 man hours per store per day. The software also prevented 237 queue forming incidents, saving an average of 2.25 hours in customer wait time per day. The experiment was conducted for two months at two store locations of one of the largest retailers in Central and Eastern Europe with 18 manned checkout counters at both trial locations.

Clean Up Your Marketplace: How AI Content Moderation Helps To Deliver Excellent Shopping Experience

Clean Up Your Marketplace: How AI Content Moderation Helps To Deliver Excellent Shopping Experience

Management, Retail / By /

The platform helped to reduce cashier idle time by 57.66% when measuring against the baseline, equaling to more than 2.5 man hours per store per day. The software also prevented 237 queue forming incidents, saving an average of 2.25 hours in customer wait time per day. The experiment was conducted for two months at two store locations of one of the largest retailers in Central and Eastern Europe with 18 manned checkout counters at both trial locations.

EasyFlow and Agmis partners with NXGen Technology to build the store of the future

EasyFlow and Agmis partner with NXGEN Technology to build the store of the future

Business, Retail / By /

The platform helped to reduce cashier idle time by 57.66% when measuring against the baseline, equaling to more than 2.5 man hours per store per day. The software also prevented 237 queue forming incidents, saving an average of 2.25 hours in customer wait time per day. The experiment was conducted for two months at two store locations of one of the largest retailers in Central and Eastern Europe with 18 manned checkout counters at both trial locations.

The future of offline retail

Will AI shape the future of offline retail?

Business, Management, Retail / By /

The platform helped to reduce cashier idle time by 57.66% when measuring against the baseline, equaling to more than 2.5 man hours per store per day. The software also prevented 237 queue forming incidents, saving an average of 2.25 hours in customer wait time per day. The experiment was conducted for two months at two store locations of one of the largest retailers in Central and Eastern Europe with 18 manned checkout counters at both trial locations.

EasyFlow smart queue management system provides customer checkout analytics.

Latest trends in Retail Queue Management

Customers, Management, Retail / By /

Customers are gearing towards e-commerce. COVID-19 once again highlighted this experience. Brick and mortar retailers have some catching up to do – latest research shows that nearly 90% of customers have left the store as a result of long queues.
However, queues regarded as a necessary evil of brick and mortar retailing, can be efficiently managed by harnessing Computer Vision and AI technologies.

EasyFlow out-of-shelf analytics provide near real time information on product stock levels and can alert employees when restocking is required.

5 Ways How Retail Shelf Monitoring Solutions Improve Business Performance

Customers, Management, Retail / By /

When e-commerce is taking over the world, high street retailers are still searching for ways to up their data analytics efforts. AI retail shelf monitoring solutions provide retailers an opportunity to make smarter decisions about sales, marketing, staffing, security and many more.
AI shelf monitoring solutions provide real time information based on in-store camera footage. Real time item availability information can significantly reduce out of stock rates. Additionally here are five ways AI shelf monitoring analytics can boost business performance.

Check-out Picklist Assistant is an AI image recognition software which automates the selection of unwrapped products

Improve retail self-checkout experience with Picklist Assistant

Customers, Management, Retail / By /

Self-checkout counters are a part of the contemporary retail landscape. Researchers forecast that their utilization rate in retail stores will grow at least 10% year on year for the next 5 years. Self-checkout was envisioned as a frictionless way for customers to conduct their shopping without any human intervention. Yet customers still spend more time …

Improve retail self-checkout experience with Picklist Assistant Read More »

In the midst of the COVID pandemic, retail changed in a fortnight.

How AI Video Analytics Help Manage Retail Operations During the COVID-19 Outbreak?

Customers, Management, Retail / By /

In the midst of the COVID pandemic, retail changed in a fortnight. Extra safety precautions, panic buying, fights over the last toilet paper rolls and understaffed stores – this is the new grocer reality!

In these difficult times retailers are turning to AI solutions to support operational continuity. Here are 5 tips how AI video analytics can support your retail operations in these difficult times.

solutions that help retailers to increase efficiency, reduce redundancies, optimize processes and identify business bottlenecks

AI Service for Retailers Aims to Limit Checkout Fraud

Customers, Management, Retail / By /

According to Leicester University research, in 2.88% of self-checkout transactions at least one of the items is mis-scanned. In total approx. 0.52% of all items are mis-scanned via self-checkout resulting in heavy losses for retailers. The research analyzed 140 million self-checkout transactions. 17 million post checkout audits were performed finding 486.000 items not being scanned at all.

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