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Customer Segmentation & Clustering using Python

For this case study, I performed customer segmentation on a mall customer dataset using the KMeans clustering, an unsupervised ML algorithm. The goal is to cluster mall customers based on their purchasing behavior and demographic characteristics.

This will help effectively allocate spend and efforts on marketing campaigns, maximising profitability.

The dataset contains information about customers such as their age, gender, annual income, and spending score. Link to the dataset.

The task

• Exploratory data analysis
• KMeans clustering (bivariate using elbow method)
• Visualization

Findings

• Cluster 1 is recommended as our target group due to the high Annual Income (k$) and Spending Score (1-100).
• 54% of cluster 1 are female shoppers. We should look for ways to attract these customers with a marketing campaign targeting popular items in this cluster. We can look at this with further analysis and data concerning order items.
• Despite the lower annual income, cluster 3 is also an interesting market opportunity for sales due to the high spending score.

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