return-predictions | HU Assignment for Business Analystics

return-predictions is a Jupyter Notebook library. return-predictions has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Customers send back a substantial part of the products that they purchase online. Return shipping is expensive for online platforms and return orders are said to reach 50% for certain industries and products. Nevertheless, free or inexpensive return shipping has become a customer expectation and de-facto standard in the fierce online competition on clothing, but shops have indirect ways to influence customer purchase behavior. For purchases where return seems likely, a shop could, for example, restrict payment options or display additional marketing communication. For this assignment, we are provided with real-world data by an online retailer. The task is to identify the items that are likely to be returned. When a customer is about to purchase a item, which is likely to be returned, the shops is planning to show a warning message. The task is to build a targeting model to balance potential sales and return risk in order to optimize shop revenue. The data we receive is artificially balanced (1:1 ratio between returns and non-returns).