Let’s see how we can reduce and minimize the negative effects of in-store queues.
The consumer profile has changed in recent years due to new technologies, ecommerce and high market competition. Customers have more choices, and if they have a bad shopping experience, they move to another store. Also, they are used to faster and faster processes and are less tolerant of store queues.
According to the study “The state of brick and mortar 2017”, 60% of consumers think that the main disappointment when they go to a physical store is the queues. An EPSON report on the effect of store queues on sales, confirms that 29% of European consumers leave a store when they see long queues at the checkout counters. 25% say they go to another store to buy the same product or they buy it online.
This is a problem for physical stores that suffer a great loss of sales opportunities because of this fact.
This problem is due to not planning enough employees in hours with a high volume of customer visits. Having undersized staff during peak visiting hours, results in store queues. Consequence: poor customer service and loss of sales opportunities.
These inefficiencies in employee scheduling (with oversized or undersized hours) are often caused by manual scheduling or tools that only automate the process. These tools do not take into account all the variables that influence the process. Also, they are based on intuition and experience instead of real data.
Undersized hours result in the loss of up to 10% of the store’s conversion ratio, which means a cost of thousands of euros.
The first step will be to predict the future volume of visits to the store at any given time, in order to align the number of employees with the demand. Then, we have to calculate the optimal staff size in the store for every hour of the day, every day of the week and every day of the month. After that, we have to generate an optimal planning of schedules and tasks for each employee, in line with the number of customers at any given time.
This is the only way to have the perfect employee in the right place at the right time to serve customers. And always have the necessary number of employees to avoid long waiting times and queues in the store.
Only workforce scheduling solutions based on the most advanced analytical techniques are capable of generating optimal schedules. Always looking to maximize employee productivity and sales.
If you would like to read more articles on staff scheduling or how Advanced Analytics can help in retail, ask to join our Linkedin group “Performance Based Scheduling” or visit the blog section on our website.
C007/20-ED. 2020 call for aid on technological development based on artificial intelligence and other digital enabling technologies within the framework of the strategic action of the digital economy and society of the state R&D program.