Increase Sales by Optimizing Staff Scheduling

Given the highly competitive nature of retail, it is becoming increasingly important for businesses in the sector to optimize their operations. The biggest names in the sector are already using traffic data to improve their operations; from marketing and advertisements to staff scheduling and other in-store activities.

Automated staff scheduling, in particular, is turning out to be very effective for increasing sales. Imagine having enough staff on the floor (at all times) to cater to all the customers present? This helps to reduce cart abandonment and lost sales opportunities considerably, leading to higher conversion rates and improved customer satisfaction. Here are some tips on how to leverage automated staff scheduling to devastating effect:

 

Employ and deploy staff efficiently

The usual practice for store managers is to employ a number of people that they estimate will be enough to run the store. This approach could lead to one of two problems. One, they don’t employ enough staff and struggle to provide optimal service to customers during rush hours. This leads to an increase in cart abandonment, lost sales opportunities, and a lot of unhappy customers. Two, in order to ensure that there are enough attendants no matter how busy things get, the store employs too many people. They end up with an inflated budget and lots of idle employees during slow periods.

Customer traffic data provides a very good basis on which to employ and deploy staff efficiently. When historical data is analyzed using AI algorithms, the reports provide managers with information on how many attendants will be required to run the store optimally. Since the analyzed data covers periods of low, as well as high, customer traffic; understaffing or overstaffing is almost completely avoided. Furthermore, computer-generated schedules are used to deploy staff based on traffic patterns. This ensures that for every shift, there will be enough attendants on the floor for all the customers present.

The schedule is continuously tracked and optimized based on in-store activity. V-count’s Business Intelligence Platform, for example, comes with a dashboard that provides hourly information on sales/traffic and lost sales opportunities.

 

Backroom operations must never interfere with the selling process

Sales attendants are often given backroom duties like receiving shipments, processing inventory, restocking shelves, and so on. If these are allowed to interfere with the selling process, it distracts the attendant, affects their service delivery, and the result is a decrease in sales. Attendants on the sales floor must always be focused on providing customers with the best service possible.

For instances when the backroom operations are urgent, the ideal option would be to wait for slow periods. Traffic data can be analyzed to figure out when the store is least active, and secondary duties can be scheduled for these periods.

Closing tasks have also been known to lead to lost sales opportunities. Store managers should check their customer data and conversion rates in the last hour of business days. If the numbers show fewer visits and fewer sales, it may be indicative of the quality of customer service in that period. If you are performing closing tasks while customers are still in your store, you are interfering with the selling process.

 

Staff breaks should be scheduled using traffic data

To ensure that your attendants provide optimum customer service, you need to keep them happy. A good way to do this is to give them breaks when due. However, it is important that breaks are scheduled in the same way that work shifts are; based on store traffic patterns. The goal is to make periods of low customer activity the break times. The peak hours on a Saturday will not be the same as the peak hours on an average Monday; the break times on these 2 days cannot be the same.

The automated staff scheduling provides a good solution here also. Since schedules are generated based on store traffic data, historically slow periods are fixed as the break periods. As a result, by the time the store gets active, the attendants will be well-rested and primed to convert visitors to customers, i.e. more sales.

Data measures the way that customers behave [customer behavior analytics] in your store. When this data is analyzed using AI algorithms, it becomes possible to predict how the customers will behave in the future. The automated staff scheduling technology uses historical data to improve how you deploy your staff and the solution keeps improving itself. What this means is: the longer the technology is leveraged, the more the schedule is optimized, and the higher your increase in sales.

 

About V-Count

V-Count is the foremost provider of visitor analytics in the world. Via our Business Intelligence Platform, we provide customers with a cloud-based storage infrastructure that analyzes collected data using artificial intelligence and machine learning tools. As a result, we are able to provide clients with information on how well their store is performing and automated staff scheduling. Additionally, we offer reports and features that help improve operations and optimize new business initiatives.

We offer products and services to clients in over 110 countries worldwide. Please visit v-count.com for more information or call +1 866 549 9360 to begin your free trial.


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