Retail Analytics, Big Data Logics and Fair Collection under Australian Privacy Law

Topic: Retail Analytics, Big Data Logics and Fair Collection under Australian Privacy Law

Presenter: Helen Gregorczuk, PhD Candidate, TC Beirne School of Law

Venue: Moot Court (Room W247), Forgan Smith

Time: 12:30pm Thursday, 6 April 2017

Contact: Claire Ritchie, c.ritchie@law.uq.edu.au 

More Information: All welcome, no RSVP required

Abstract

Bricks and mortar retailers are facing increasing financial pressures due to the growth and ease of online shopping.  In order to stay competitive, retail outlets with a physical presence are employing some surprising technologies to gather and process customer data.  Known as retail analytics, it involves using the sophisticated analytics techniques of big data to better understand customers with the aim of personalising marketing and ultimately increasing store profits.  Retail analytics also involves tracking customer movement, compiling detailed customer purchase histories and creating customer profiles. The logics of big data that underpin the adoption of retail analytics thus signifies a potentially new shopping environment in which the large-scale, passive and automated data gathering of customer behaviours becomes the norm.

However it is unclear whether retail analytics collections of customer data are compatible with the ‘fair collection’ principles (APPs 1, 3, 5) of the Privacy Act 1988 (Cth).  Under these principles retailers are required to only collect personal information in a fair and lawful way, to have a privacy policy which outlines what they collect in terms of personal information and how it will be used, and to give notice to customers of collections of personal information at the time of collection.  This thesis will look at the compatibility of these ‘fair collection’ principles with retail analytics collections with a view to making recommendations around what a fair collection should look like under the Privacy Act in an increasingly big data environment.