Shoppers Persona Analysis: Statistical Learning of Shoppers’ Behaviour

The project is to break down shoppers into different groups. Shoppers have different preferences, for instance some shoppers tend to buy online in the morning, some might prefer purchasing online at night. If one could group together shoppers based on their different shopping behaviours, one would then be able to come up with personalized sales strategy that could better serve the customers, for example the retailer could send push notification in the morning to the group whose shoppers tend to buy in the morning. In return, this will provide advanced algorithms to help to generate more profit for the retail company. In this sense, this is a win-win project that will benefit both the retailers and the shoppers.

Faculty Supervisor:

William Welch


Hao Chen


Mobify Research and Development Inc


Statistics / Actuarial sciences


Information and communications technologies




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