Customer Segmentation using R

Overview

Customer segmentation is the process of dividing a customer base into groups of individuals with similar characteristics. This project uses R to analyze customer data and implement clustering techniques to identify meaningful segments.

Dataset

• File: Mall_Customers.csv
• Columns:
  • CustomerID: Unique customer identifier
  • Gender: Male/Female
  • Age: Customer age
  • Annual Income (k$): Customer's yearly income
  • Spending Score (1-100): Score assigned based on spending behavior

Methodology

1. Data Exploration
   • Displaying the first few rows
   • Checking for missing values
   • Summary statistics and standard deviation analysis
2. Data Visualization
   • Gender distribution
   • Age distribution
   • Income vs. Spending Score plots
3. Clustering
   • Using the Elbow method to determine optimal clusters
   • Applying K-means clustering
   • Visualizing cluster results

Results

• Identified optimal clusters for customer segmentation
• Visualized customer groups based on spending behavior and income

Visualizations

Business Insights

• Gender Analysis: The dataset shows that female customers are slightly more than male customers, indicating potential targeted marketing strategies for different demographics.
• Age Distribution: The majority of customers fall within the 30-35 age group, suggesting that marketing campaigns should focus on this age range.
• Spending Behavior: Customers with mid-range annual incomes tend to have higher spending scores, highlighting a key target audience for promotional offers.
• Cluster Findings:
  • High-income, high-spending customers form a premium segment, ideal for luxury product marketing.
  • Low-income, low-spending customers represent a budget-conscious segment that may respond well to discounts.
  • Young customers with moderate income and high spending scores indicate an opportunity for trendy and lifestyle-based promotions.

Dependencies

• R (version 4.0+ recommended)
• Required libraries: ggplot2, dplyr, cluster, factoextra

Usage

1. Install required libraries using install.packages("package_name")
2. Run the provided R script or execute the notebook step by step

Conclusion

This project provides an insightful analysis of customer segmentation, helping businesses target specific customer groups more effectively.

Author

Hari Patel