The way we think about shopping has been completely transformed by the advent of online retail. Nowadays, customers are able to use, in addition to traditional physical stores, online shopping giants such as Amazon and Alibaba, and omnichannel services allowing them to pick their ordered items up in-store. By doing so, customers leave a tremendous amount of data in the hands of their favoured retailers. Through Internet of Things (IoT), Beacons, Videos, or your mobile phone, these shopkeepers can find out at the click of a button what you have been browsing, which items you have reviewed, which ones you bought and your current location. The growing and vital field of big data harvesting have even become fashionable, with buzzwords such as Machine Learning and Artificial intelligence entering suddenly into the public consciousness. Companies ranging from startups like Stich-fix, using these data to curate your next outfit, to multinational conglomerates like Google, using them to modify the world’s most popular search engine, depend on it. Besides all this, such data can also be used to ask fundamental questions about business models: What is the role of a store? Do we need fast delivery options or do customers attach more value to delivery speed? Do customers really react to marketing scarcity tactics such as Booking.com’s dreaded “only 5 left”? While it is mainly computer and data scientists who analyse and develop algorithms, business students also have a major role to play in putting challenging new questions to the established data science community, coming up with inventive changes to entrenched business models and ways of thinking, and finding promising potential business applications that will shape the future of retail. It is thus important that business students understand the underlying principles used in this field. 

Prerequisites: Yes (see syllabus)