Creating Customer Segments

Now that you've learned a lot about unsupervised learning, it's time to apply that to a project.

A wholesale distributor recently tested a change to their delivery method for some customers, by moving from a morning delivery service five days a week to a cheaper evening delivery service three days a week.Initial testing did not discover any significant unsatisfactory results, so they implemented the cheaper option for all customers. Almost immediately, the distributor began getting complaints about the delivery service change and customers were canceling deliveries — losing the distributor more money than what was being saved. You’ve been hired by the wholesale distributor to find what types of customers they have to help them make better, more informed business decisions in the future. Your task is to use unsupervised learning techniques to see if any similarities exist between customers, and how to best segment customers into distinct categories.

Project Files

For this assignment, you can find the customer_segments folder containing the necessary project files on the Machine Learning projects GitHub, under the projects folder. You may download all of the files for projects we'll use in this Nanodegree program directly from this repo. Please make sure that you use the most recent version of project files when completing a project!

Evaluation

Your project will be reviewed by a Udacity reviewer against the Creating Customer Segments project rubric. Be sure to review this rubric thoroughly and self-evaluate your project before submission. All criteria found in the rubric must be meeting specifications for you to pass.

Submission Files

When you are ready to submit your project, collect the following files and compress them into a single archive for upload. Alternatively, you may supply the following files on your GitHub Repo in a folder named customer_segments for ease of access:

  • The customer_segments.ipynb notebook file with all questions answered and all code cells executed and displaying output.
  • An HTML export of the project notebook with the name report.html. This file must be present for your project to be evaluated.

I'm Ready!

When you're ready to submit your project, click on the Submit Project button at the bottom of the page.

What's Next?

You will get an email as soon as your reviewer has feedback for you. In the meantime, review your next project and feel free to get started on it or the courses supporting it!