This document describes a Queue Management System (QMS) that can provide various benefits to retailers. The QMS uses computer vision to count customers, analyze customer behavior and flows, monitor queues, and provide queue forecasts. It aims to improve the customer experience, optimize staffing and resource allocation, increase sales by reducing queues, and help prevent shoplifting. Retailers can use data from the QMS to better understand customer traffic patterns, hot/dead zones, and peak times to improve merchandising and space layouts. The document outlines the QMS's capabilities and provides examples of reports it can generate on key metrics like queue lengths, wait times, and efficiency by department.

1. Queue Management System
Add value to your retail business with QMS
July 2015

2. Prospects
Key opportunities
 Customers counting
 Customer behavior analysis
 Queue analysis
 Customer experience analysis
 Security
Goals
 Goods display improvement
 Measurable KPIs for administrative, management and
sales staff
 Customer experience improvement and cutting
queues
 Justification for a shelf cost rate for suppliers
 Shoplifting prevention

3. Customer Behavior Analysis
 Clear view of customer flows
 Improvement in retail space, goods outlay and showcases layout
 Evaluation of marketing and advertising investments efficiency
 Determination of the most important areas and “dead zones”
 Optimization and rearrangement of the retail space staff
 Queues cutting
 Justification for a shelf cost rate for suppliers

4. Customer Experience
Sales increase due to queues reduction
Queue Length Control
Service quality enhancement
Queue Time Control Service Tome Control
Management of cash operating staff and
shiftwork scheduling

5. Numerous Questions Answered
1. What are the most time-consuming areas for customers and what rows do they
pass by?
2. Which goods outlays and promotions attract the most of shoppers?
3. What is the efficiency ratio of the certain shopping rows and the end caps?
4. When do the longest shopping queues appear and how many checkout operators
are needed to avoid exceeding the target queue length during these peaks?
5. How to design the most convenient shiftwork schedule depending on customers’
number in the store?
6. How many customers have left the store with no purchases? Why?
7. … and many others.
Assistance in making strategic decisions to boost sales

6. The Operation Pattern
People counting Customer flow analysis
Queue analysis Face detection Statistics analysis
SMS notification

7. Customers Counting
Key opportunities
 The software detects an individual by characteristic
features
 95-95% veracity rate, including queuing peaks
Data correction and adjustment to sales staff
 Aside from customers, 25% of counted people may
be the staff
 Software suggests staff uniform analysis and deletion
of data, leading to errors
 It applies detection procedures to certain groups of
customers
Associate (orange shirt,
black pants)
Customers

8. Customer Flow Analysis
 The software analyzes customers’ movements
around the retail space and records the trajectories in
a special database
 There are different ways to visualize the collected
data
 Customers recording in restricted areas
Examples of different ways to visualize collected data
30 in day
68
12
3
Min
Max
Dead zone

9. Queue Analysis
Target goals
 Boosting sales due to reduction queue length
 Customer experience enhancement
 Cash operating staff management
Queue length forecast
 Using collected data, monitoring system provides
forecasts for 15, 30, 45 minutes ahead that allows
enabling extra checkout points
 Designated staff is notified by a system via SMS
Detection of customer groups
 The considerable number of purchases is made by
families
 Large coverage areas and advanced algorithms
enable detection of families in queues and
recognizing them as the one customer
Queue analysis statistics
 The number of customers in queue
 Checkout capacity
 Average queuing time
 Peak hours
 Downtime hours

10. Resource Optimization
Operating resources optimization effect based on demand
measurement
 From practical experience, the peak time of purchases is 6-
10 PM
 QMS by Miritec detects the biggest customer flow in the store
during the period from 1:30 PM to 7:30 PM. Sales operations
management may design more effective strategy, based on
newly collected data
 Accomplished studies resulted in 32% sales increase
during next 6 months Human resources optimization
Staffing – human resources optimization according to working load
statistics and essential needs
 Peak time is different in different departments
 Human resource optimization depends on the department
 One thus can easily define weekdays, weekends and holidays
trends
On average
weekday
(green line)
Storage media
Home theaters
Computers
Spades

11. Efficiency Ratio by Department

12. Different Customer Locations
11,000 people per day 3700 people per day Customer counting per store
Show window analysis
Measurable space around the show
window and its analysis

13. Queue Management System (QMS) Custom Development
Dev Center Miritec
UI/UX Design Independent Software
Testing
IT-System Migration and
Reengineering
Custom Development and
Support

14. Miritec Projects

15. Thanks for Watching
Contacts
www.miritec.com/en/ marketing@miritec.com 03680 Kiev, 4 Ivan Lepse blv,
Ukraine
+38 (044) 359-05-90