You can watch the video below. Let us know if you learn something new or useful by tweeting us @DataIdols.
Determining a retail basket’s purpose is a key part of driving an understanding of shopping behavior. One way that dunnhumby has attempted to build understanding in the past is through topic modelling, where the basket is reimagined as a textual document being examined. Building off those foundations, the definition of a document is shifted to incorporate multiple baskets for identifiable customers. Using transaction data from a North American retailer, dunnhumby trained a topic model on millions of customers to learn several concepts that reflect individualized shopping behavior. The topics were found to correspond with distinct behavioral patterns and provide a way to tag customers with topics describing their shopping behavior.
More data science events to interest you 👀