The Otto Group is one of the world’s biggest e-commerce companies, with subsidiaries in more than 20 countries, including Crate & Barrel (USA), Otto.de (Germany) and 3 Suisses (France). They sell millions of products worldwide every day, with several thousand products being added to their product line.
A consistent analysis of the performance of products is crucial. However, due to their diverse global infrastructure, many identical products get classified differently. Therefore, the quality of their product analysis depends heavily on the ability to accurately cluster similar products. The better the classification, the more insights that can generate about their product range.
The task is to build a classification model that accurately classifies products based on the given features into the right categories.
Each row corresponds to a single product. There are a total of 93 numerical features, which represent counts of different events. All features have been obfuscated and will not be defined any further.
There are nine categories for all products. Each target category represents one of our most important product categories (like fashion, electronics, etc.).