This project was completed as part of the Udacity Data Scientist Nanodegree requirements
The goal of this project is using unsupervised learning techniques of Principal Component Analysis (PCA) and KMeans to identify customer segments of the German population that were popular or less popular with a mail-order sales in Germany.
The data is provided by Bertelsmann partners AZ Direct and Arvato Financial Solution. There are two dataset provided first was demographic data (891,211 individuals)for the general population of Germany and the second dataset was demographic data for customers of a mail-order company (191,652 individuals). Both dataset consists of 85 different features.
The summary of this project can be found at my medium blog post.
The mail-order is popular with individuals who:
- Estimated age around 30-60 years of age
- High for dutiful
- High for traditional
- Higher for sparer and investor
- Low for 'be prepared'
- Low for sensual minded