Optimize your store ?

How do we reach a good decision?

We now want to take our projects to new levels with the target to get more analytical data directly to provide documentation in the form of decision support in optimizing the stores. This means that we go deeper into the analysis and try to develop new reports that provide the information we seek. To achieve this we need to find intersections between sales data and key figures from our CAD models and the measurement data in customer behavior.

Our first pilot that we conducted in collaboration with camera vendor Axis (www.axis.com) has been a good start to understand the technology and that it is possible to get KPIs out of our measurements, we now want to take work forward and approach the concrete decision support for people at headquarters and even store managers.

We will involve new technologies and help from other analysts as well as experience from previous projects with Walmart and BMW group. Together with a company who are experts in the analysis and measurement of motion with very high resolution make the necessary information. This is done by a technique that maps customers’ mobile phone communication with the surrounding network.

All data points are stored as raw data in the form of ID, position, time and motion, which in processing may cause to:

• Follow the customer in the store (anonymously) in the form of individual customer laps
• The total customer time in the store
• Identify points of interest based on the customer stops in store
• Repeat customers through the mobile phone’s unique ID
• High precision allows us to see which shelves and might even be what the customers stop by
• From the earlier pilot project, we continue with:
  • Measure in / out passed customers
  • Activity index at selected locations such as campaign surfaces

“Our goal is based on measurement data to display it on the store’s layout in the form of various graphic expressions and new reports that hopefully leads to decision support.”