Introduction A customer receives a drink from Starbucks barista millions of times each week, but each interaction is unique. This is just a moment in time, but nevertheless a connection. How does this customer behave, and what prompts them to make a purchase? To find out, we can use a simulated dataset that mimics customer behaviour on the Starbucks rewards mobile app. Once every few days, Starbucks sends out an offer to users of the mobile app. An offer can be merely an advertisement for a drink or an actual offer such as a discount or BOGO (buy one get one free). Some users might not receive any offers during certain weeks. Not all users receive the same offer, and that is the challenge to solve with this data set. Our task is to combine transactions, demographics and offer data to determine which demographic groups respond best to which offer…
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