Personalisation is a popular and effective way in which companies provide customers relevant content and reduce their need to assess abundant information. Most people are familiar with the product recommendations of Amazon, the personalised music recommendations of Spotify, and personalised movie recommendations of Netflix. These tech companies are putting major effort into improving the accuracy of their recommendation algorithms. Companies increasingly use customer information from a variety of sources, to infer their preferences and provide personalised interactions across different channels, including information obtained from click-stream data, bidding data, advertising campaign data, social media data, mobile usage data, search data, and sales data. Apart from personalised product recommendations, companies are also working hard to tailor their interactions with customers by addressing them with customised e-mail communications and targeted advertising messages based on customers’ behavioural information. Some companies develop business models that provide personalised products and service offerings and tailor individual pricing and referral policies for each customer. We work on a number of personalisation related research projects where we see an increasing proliferation of personalisation practices by businesses for enhanced customer experience and maximising business opportunities, including recommendation systems, personalised advertising, mobile targeting.
D. Tsekouras, T.W. Frick & T. Li (2016). Don’t Take It Personally: The Effect of Explicit Targeting in Advertising Personalization. In International Conference on Information Systems (ICIS 2016) . Dublin: AIS
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Senior Lecturer in Business Information Management
Endowed Professor Digital Business
Academic Director Erasmus Centre for Data Analytics
Tel.: +31 (0) 10 408 1961