Create a Customer Segmentation Report for Arvato Financial Solutions

To introduce yourself to the scenario you'll be investigating in this capstone project option, take a look at the following video with Timo Reis from Arvato Financial Solutions.

Hiring Opportunity

The data and outline of this project was provided by Arvato Financial Solutions, a Bertelsmann subsidiary. High performers on this project will have their Udacity profile sent directly to Arvato for review, and may lead to an interview at either Arvato or Bertelsmann. This is a tremendous opportunity to get access to a data science hiring manager!

Steps to Complete This Project

The project has three major steps: the customer segmentation report, the supervised learning model, and the Kaggle Competition.

1. Customer Segmentation Report

This section will be similar to the corresponding project in Term 1 of the program, but the datasets now include more features that you can potentially use. You'll begin the project by using unsupervised learning methods to analyze attributes of established customers and the general population in order to create customer segments.

2. Supervised Learning Model

You'll have access to a third dataset with attributes from targets of a mail order campaign. You'll use the previous analysis to build a machine learning model that predicts whether or not each individual will respond to the campaign.

3. Kaggle Competition

Once you've chosen a model, you'll use it to make predictions on the campaign data as part of a Kaggle Competition. You'll rank the individuals by how likely they are to convert to being a customer, and see how your modeling skills measure up against your fellow students.