Artificial Intelligence in Venue Analytics

AI Case Study: Venue Analytics

Web site analytics provides insight into what your web traffic represents. It helps you answer questions like:

  • Who visits my website and what do they read?
  • How much time users spend in each area of my website?
  • What do those users click on?
  • How can I turn those users into customers?

While generation of website analytics is a well-established area of expertise, obtaining such data for brick-and-mortar venues is a challenging task.

The purpose of this ongoing project is bridging the gap in analysis of customer behavior in online and physical environments. The below video visualises how our AI-based software system conducts customer segmentation and behaviour analysis in a retail store using 3 video camera equipped IoT (Internet of Things) devices.

Important Note:

To avoid misuse and protect people’s identity this Venue Analytics system:

  • does not use Facial Recognition for person identification
  • person’s data is deleted once person exits the store
  • video streams are not stored
  • snapshots for classification and analysis are encrypted and deleted once AI processing is completed

Skip to relevant parts of the video by selecting below.

0:00 Start of the recording. View is set to Camera #1 - Entrance Door.
0:06 Person is detected as entering the venue.
0:11 View is switched to Camera #2 - Zone 7.
0:17 Person is detected as entering the specified zone.
0:20 Person is detected as touching and looking at the product on the shelf.
0:25 Person is detected as leaving the specified zone.
0:28 View is switched to Camera #3 - Exit Door.
0:35 Person is detected as leaving the venue.
0:42 End of recording.


This AI case study has been conducted in Australia, Melbourne.