Customer Segmentation Using K-Means Clustering in Python
<p>In today’s data-driven business landscape, understanding your customers is essential for making informed decisions and delivering personalized experiences. Customer segmentation, the process of dividing your customer base into distinct groups, can provide valuable insights into customer behavior and preferences. In this article, we’ll explore how to perform customer segmentation using K-Means clustering in Python.</p>
<h1>What is K-Means Clustering?</h1>
<p>“K-means” gets its name from two things:</p>
<ol>
<li>K: This is the number of groups you want to create. You decide how many groups you want.</li>
<li>Means: This means finding the middle or average position of things in each group.</li>
</ol>
<p>So, “k-means” is like saying, “Let’s find K groups by figuring out where the middle of each group is.” It helps us sort things into groups based on their similarities.</p>
<h1>Prerequisites</h1>
<p>Before we dive into the code, ensure you have the following prerequisites:</p>
<ol>
<li>Python installed on your system.</li>
<li>Required Python libraries: pandas, scikit-learn, and matplotlib. You can install them using pip if not already installed.</li>
<li>Feel free to explore data from different sources. In this particular case, I’m using Shop Customer Data obtained from Kaggle. (https://www.kaggle.com/datasets/datascientistanna/customers-dataset)</li>
</ol>
<h1>The Code</h1>
<p>The full code can be found <a href="https://github.com/0xrsfagundes/Digital-Marketing/blob/812072e84414695639eb8e28184e8f36508719d3/Customer%20Segmentation%20Using%20K-Means%20Clustering.ipynb" rel="noopener ugc nofollow" target="_blank">here</a>. Let’s break down the Python code step by step:</p>
<h2>1. Importing Libraries</h2>
<p>We start by importing the necessary Python libraries: pandas for data handling, scikit-learn for machine learning, and matplotlib for plotting.</p>
<pre>
import pandas as pd
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt</pre>
<h2>2. Loading Customer Data</h2>
<p>We load our customer data from a CSV file. You can replace the file path with your dataset.</p>
<p><a href="https://rsfagundes.medium.com/customer-segmentation-using-k-means-clustering-in-python-c62ce4e264de">Website</a></p>