leamartinez1411 / end-of-bootcamp-project

Clustering with K-means apply to customer segmentation

End-of-Bootcamp-Project

From my dataset, my goal is to use K-means to create clusters and thus segments in my customer database.

In this repo, you will find :

• My Dataset : The export of data from an e-commerce company (sales from 2019 to 2020), anonymized with the customer ID and with no information relating to the price or to the customers as desired by the company that provided me with this data.

• My Tableau Dashboard : It contains a detailed analysis of my dataset with interesting visualizations such as: the distribution of sales over a year with the "critical" moments, the visualization of sales from a geographical point of view, etc.

• My Python Notebook: All of my code which covers the steps of cleaning my dataset, exploring my data and using K-means to set up and assign each client its cluster as well that the detailed analysis of these clusters according to the different variables.

• My final presentation: A presentation taking up the key elements of this project, and organized in such a way as to bring out the business aspect understandable by the greatest world, mixed with the more technical part that I carried out.