Customer Segmentation With K-Means and UMAP

A report for the non-technical marketing team.

R
k-means
UMAP
Author

Sandra Jurela

Published

December 15, 2022

Problem Statement

Marketing team would like to increase email campaign engagement by segmenting the customer-base using their buying habits.

Solution Summary

The 4 customer segments were identified and given descriptions based on the customer’s top product purchases.

  1. Segment 1 Preferences: Road Bikes, Below $3200 (Economical Models) - 27%

  2. Segment 2 Preferences: Mountain Bikes, Above $3200 (Premium Models) - 10%

  3. Segment 3 Preferences: Road Bikes, Above $3200 (Premium Models) - 20%

  4. Segment 4 Preferences: Both Road and Mountain, Below $3200 (Economical Models) - 43%

Customer Preferences

Heat Map

Our customer-base consists of 30 bike shops. Several customers have purchasing preferences for Road or Mountain Bikes based on the proportion of bikes purchased by category (mountain or road) and sub-category (Over Mountain, Trail, Elite Road, etc).

Customer Segmentation

This is a 2D Projection based on customer similarity that exposes 4 clusters, which are key segments in the customer base.

Customer Preferences By Segment

The 4 customer segments were given descriptions based on the customer’s top product purchases.



Note: The table below is sortable. You can sort a column by clicking on its header.