Our thirst for online shopping and engagement with multi-media streaming sites seems insatiable. The success of the likes of Amazon, Netflix, Spotify, and YouTube, demonstrates this major growth area, and Covid-19 has served to accelerate our consumer behaviour from offline to online. It seems ironic, that whilst our offline interactions have become ever more de-personalised through social distancing requirements, limited personal interactions and the wearing of face masks, it is our online interactions which have become increasingly more personalised. The more we consume and interact online, the more data we create. This data is the currency of the digital world. Recommender systems leverage this data to tailor the content of websites in real time to match individual predicted user preferences and needs.
But, do recommender systems influence our actual behaviour? Do they enrich our lives, or simply reinforce our own behaviour? And, how does this technology benefit organisations, customers and society?
These were just some of the questions raised in Mark Graus’s Recommender session, delivered as part of the Digital Strategy module for the MaastrichtMBA programme in November. Mark is an Assistant Professor on Data Science in Marketing at Maastricht University. His background in Human-Technology Interaction combines machine learning with fundamental psychological theory. It is this combination of expertise, which enabled a dynamic and nuanced debate on the recommender session, and yes, it got personal!