Footprints for Retail is the most advanced marketing automation tool that enables shopping centers for the first time ever to address audiences based on behavioral data generated within the shopping center. 

One of the most important assets that Footprints for Retail platform has it’s the Retail Analytics engine that provides real time, accurate data gathered from within your Shopping Center and that can be afterwards used with the help of our unique feature Homomorphism in defining specific audiences for targeting marketing campaigns tailored to fulfill your Shopping Centers’ specific marketing objectives. “Homomorphism” represents our advanced AI framework that empowers our unique technology to have the capability to enrich any online database, at individual user level, with their physical shopping behavioral characteristics (more about homomorphism here ). In order to better understand the Retail Analytics’ capabilities and how the technology that stands behind this feature can help your business step forward to the digitization of your physical properties we have unveiled some of the definitions of the keywords that are mostly used to understand Retail Analytics.

The “Business” and “Visit” Concept

A “Business”, in the Footprints Retail Analytics terminology, is a well-defined area inside a monitored building. 

The main entity type that governs the whole platform is the concept called “Visit”. A visit is represented by a series of consecutive and/or continuous detection of the same identifier (MAC) in a period of time, in a certain area. All the visits and metrics are computed for multiple time intervals: hour, day, week, month and year. 

 Blacklisting

 The “Blacklisting” represents the concept of eliminating from the system all the devices that are considered not being relevant into the insights and reports, as, for example: employees and staff that works into the building (ex: security staff, sellers, operators etc.) or devices that are exposed into showrooms and store displays. 

Reports and Insights

 The reports and insights are represented in various chart formats, depending on the relevancy of the data versus the type of analysis.

 Most of the reports include (more details here):

  •   Weekly and monthly values at building level, with comparison against the previous similar interval, or last year’s parallel interval;
  •       Drill down to floor and business level;
  •       Comparison with averages, weighted averages and benchmarks;
  •       Detailed hour-by-hour view;
  •       Export to PDF file. (more details here)

 Total Visits

Shows the total number of visits in the selected area and compares it to the number of visits in the previous interval.

 Total Visits

Visits Pattern

Shows the distribution of the total number of visits by hours.

Visits Pattern

Average Visit Duration 

Shows the average duration of non-bounced visits and compares it to the previous interval.

 

Average Visit Duration

Dwell Time Segmentation

Segmentation of the number of non-bounced visits distributed between the longest and shortest durations.

 Dwell Time Segmentation 

Visit Duration vs. Weather

 The daily evolution of the average duration of non-bounced visits, correlated with the weather, in the corresponding intervals. The weather values displayed are the average weather condition and temperature for each of the intervals, as collected from the Open Weather Map API.

 Visit Duration vs Weather

Average Bounce Rate

 The percentage of bounced visits vs. the total number of visits.

 Average Bounce Rate

 Areas of Interest

 A heatmap indicating the traffic (number of visits) in each of the mapped areas.

 Area of Interest

Visits vs. Weather

 The daily evolution of the total number of visits, correlated with the weather, in the corresponding intervals.

 Visits vs Weather 

Cross-shopping Analysis

A statistic regarding the connected consecutive visits between the top connected pairs of businesses mapped into the system.With this dashboard you will understand which are the brands that act as anchors for your Shopping Center and also what are your shoppers’ visits flow. The insights provided are of tremendous importance in understanding what is actually going on within your Shopping Center and based on these insights you can develop not only specific campaigns but also business strategies. 

 Cross Shopping Analysis

Visitors Flow Analysis

A more in depth analysis of shopper’s habits within your Shopping Center is provided by the Visitors Flow Analysis dashboard. The analysis of connected visits between up to five consecutively visited businesses, with an option to view the insight by starting point or destination which means that you can now see where Zara’s shoppers are going after a Zara Shopping Session or which are Starbucks’s visitors shopping habits. 

Visitors Flow Analysis

 Common Path Analysis

 By analyizing the traffic on corridors and between businesses across the mapped areas our platform is able to provide you the most used paths by your Shopping Centers visitors. The insights provided by this dashboard can also be used in further developing marketing and business strategies altogether. 

 Common Path Analysis

 Conversion Funnel

A complete analysis that measures the conversion from simple visitors to engaged customers, based on their behavior into the monitored areas.

Conversion Funnel