Understanding the association between customer demographics and behaviour is critical for operators of indoor retail spaces. In our new study published in EPj Data Science, we explore associations based on a combined understanding of customer Cyber (online), Physical (Where?), and Social behaviour. We combine the results of a traditional questionnaire with large-scale WiFi access logs which capture customer cyber and physical behaviour. We investigate the predictability of user demographics based on CPS behaviors captured from both sources and provide strong support for demographic studies based on large-scale logs data capture.

This is the most recent publication from the fruitful ARC LP TRIIBE collaboration, with colleagues Yongli Ren, Flora Salim, Jeff Chan and Mark Sanderson (all RMIT).

Cite as:

Ren, Y., M. Tomko, F. D. Salim, J. Chan and M. Sanderson (2018). “Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces.” EPJ Data Science 7(1): 1-21. DOI: 10.1140/epjds/s13688-017-0128-2

The paper can be freely accessed here: http://rdcu.be/DZkO

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