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Data-driven store management - an eye-opening opportunity!

Kaarina Päivinen , Iiwari Tracking Solutions Oy
16 Sep, 2022
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Automatic data flow of everything that happens in the store.

Store chain manager or store manager, do you dream of an automatic data flow that would help you find out what actually happens between when a customer enters and leaves the store?

And would you be interested in comparing the detailed performance of different stores? Or do you know the actual productivity of different departments in the store?

Automatic data flow of everything that happens in the store.

And now we are not only talking about sales, but how department-specific customer visits are directly related to the amount of work assigned to the department and the sales received from the department. In this way, the real efficiency and profitability of the department can be found out.

The data needed for this analysis is collected completely automatically, without manual entries. The data collected in this way is accurate and is based on actual customer visits and realized rather than planned working hours.

Location data makes the invisible visible

It is possible to collect such a data stream with the help of indoor positioning, when the movements of employees and customers in the store are monitored with the help of positioning tags.

Although monitoring store personnel is voluntary for employees, it is widely accepted among them because it brings immediate benefits to their own work.

Real-time customer data helps the staff e.g. to prioritize tasks and plan breaks. By monitoring the personnel, data is obtained, which can be used to develop more reasonable working methods and to improve the operation of the entire store.

Employee involvement

It is important to involve the entire staff in the pursuit of efficiency in the operation of the store, because everyone’s contribution to the implementation of the change is crucial. The employees themselves usually also know best which things in working methods are difficult and they come up with the best development ideas for practical changes. The better quality data can be collected, the better it is possible to intervene in the ways of working. When the data can be used to show, for example, unnecessary kilometers walked in the store space (yes, kilometers are already walked in a week), it is easier to think about the necessary corrective measures and also to really monitor the impact of the changes. We don’t just rely on assumed information (I think it is this way…), but we really base decisions on data, manage with data and get concrete things done.

Staff participation naturally involves going through reports and following changes together, and this does not have to take a lot of time. Employees are definitely also motivated by the bonuses that are received when the performance of the store or individual department reaches the agreed goal.

When the collection of location data is justified and the easy steps required to collect the data are familiar (carrying the tag along), it is motivating to participate in improving the operation of one’s own workplace. Collecting location information from the staff does not really require anything other than wearing a voluntary anonymous tracking tag on e.g. a lanyard.

Real-time customer data, e.g. from a screen in the break room or in the store, helps the staff to prioritize their own tasks, plan breaks, etc. It is also interesting to be able to predict the formation of queues, so that the cash registers always have the optimal number of personnel.

Retail Analytics engStore- and department-specific performance

Chain managers are interested in comparing the detailed performance of different stores. The shopkeeper or store manager, on the other hand, is interested in finding out the actual productivity of the different departments of the store.

When customers are located using tracking tags attached to shopping carts and baskets, and staff with voluntary portable tracking tags, interesting information is obtained about how the store space is used.

The space is divided into zones, where entering is counted as one visit. The time of the visitor’s visit can be measured to the minute. In this way, the amount of work done by employees in certain departments can also be measured completely automatically.

It is also worth monitoring the duration of customers’ visits to different departments; why do customers stay longer in some departments than others? Are the items difficult to find, or are they so interesting that you don’t want to leave the department? Does the time spent in the department correlate with sales? And if not, what can be done, for example, in terms of presentation?

Super data comes by combining

A department may seem to be working well if there are a lot of customers and they spend a lot of time there. But it is only by combining the data that the real performance of the department can be found out.

Iiwari Retail Analytics 

The department’s performance is obtained by relating department-specific customer visits directly to the amount of work assigned to the department and to the sales received from the department. You can analyze sales / regional visit or, for example, sales in relation to the duration of the category visit. And does the working time spent in the department correlate with sales? Is e.g. time-consuming shelving worth the effort?

The data needed for this analysis is collected completely automatically, without manual entries. The data collected in this way is accurate and is based on actual customer visits and their durations, as well as realized rather than planned working hours.

With the help of location information, it is possible to measure, for example, the effectiveness of advertising much more precisely, as well as the effect of changes in the store’s layout on the number of visitors and sales of the category.

Data-driven store management, all this can be found out:
  • Detailed store performance
  • The number of customers between the entrance and the checkouts
  • How much working time is used / department
  • How many customers visit / department
  • What routes do customers take in the store
  • How long do customers spend in the store?
  • Is there any shelf space / aisle left for little use
  • Department conversion
  • The actual productivity of the department
  • Effectiveness of store advertisements
  • General analytics and trends for detailed store performance
Interesting opportunities at the chain level
  • Better overall business knowledge
  • Supporting the store manager with data
  • Faster response to trends
  • The ability to better compare the performance of different stores
Use cases
  • Big picture and better understanding of customer behavior
  • Actual performance of different stores
  • Comparing stores at a detailed level and learning from them
Virtual areas – the basic units of analytics
  • Tracking tags are attached to shopping baskets and carts.
  • The store space is divided into virtual areas
  • Tracking tags also in employees’ possession

The information is received in real time and for the desired periods:

  • number of visitors / store / hour / day / week
We help you understand what location is used for and how it could improve your facility and processes.

We offer access to indoor positioning, from a free demonstration to a thorough expert assessment of the suitability of the positioning for your company.

  1. See the positioning accuracy yourself – Book a virtual 20 min demo for free.
  2. Test the functionality of positioning with Iiwari Development Kit.
  3. Learn from our experts how you can improve efficiency with location information.

Get Started »

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