The Starbucks Rewards Program is the signature loyalty program of Starbucks, it comes with a card, an app, and plenty of special offers ready to be taken by their most loyal customers who are ready to pay what it gets to get their daily warm coffee. A portion of the Starbucks Rewards dataset has been released to the public so it can be freely explored, analysed and modelled.
This project makes use of the Starbucks App Customer Rewards Program Open Data to analyse how each special offer made by Starbucks impacts different segments of their customer base, clustered by age, gender, and income; classify and measure transaction volumes across these variables and groups; and make use of predictive classification modelling in order to determine which offers are likely to succeed or not, giving room to different applications such as simulation playgrounds, user-specific offer creation, general offer fine-tuning, among other different ranges of model usability.
Feel free to fork this repository and use the research of this project to build upon. If you have any question, please open an issue to discuss your inquiry.