Customer Segmentation Analysis

: Marketing analysis with RFM values on customer purchase data and customer segmentation using K-means

1. Who Is Your Golden Goose?

Customer segmentation is the technique of diving customers into groups based on their purchase patterns to identify who are the most profitable groups. In segmenting customers, various criteria can also be used depending on the market such as geographic, demographic characteristics or behavior bases. This technique assumes that groups with different features require different approaches to marketing and wants to figure out the groups who can boost their profitability the most.

This analysis is focused on two steps getting the RFM values and making clusters with K-means algorithms. Online retail data is used, which is available at UCI ML repo. The original resource of this note is from the course “Customer Segmentation Analysis in Python” on DataCamp.

• Project Date: Dec, 2018

• Applied skills: Data Manipulation. RFM analysis. K-means clustering, Visualization with Seaborn & Plotly

• Publication: "Who Is Your Golden Goose?: Cohort Analysis", Jan 6. 2019, Medium ( 👉 Republished on KDnuggets)

2. File Details

• Cohort_Anaylsis_Medium.ipynb: Code script for the blog post on Medium
• Cohort_Anaylsis_1.ipynb: Duplication code for customer segmentation course on DataCamp