Adaptive Visualization for Analysis of Customer Behaviour

Companies with a strong online presence are seeking to increase users’ engagement by adding recommendation and prediction algorithms to their websites. These algorithms can for example predict which users’ actions are more likely to happen and which users’ actions are likely more profitable. Companies use such algorithms to tailor the content of their websites based on the users’ behavior. Websites tailored to users’ behavoiur become more profitable and competitive for digital advertisement and e-commerce. Despite the proven effectiveness of these recommendation and prediction algorithms, how to illustrate their benefits and educate the stakeholders still remains a challenge. This is the problem that our industrial partner Youneeq wants to address: How can data visualization be used to convince stakeholders than a recommendation algorithm is having a positive impact on e-commerce metrics? And does the visualization need to change for stakeholders with different roles and backgrounds?

Faculty Supervisor:

Dr. Melanie Tory


Maria-Elena Froese




Computer science


Digital media


University of Victoria



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