README.md

Customer Personality Segmentation w/ EDA & K-means clustering

Data Source:

Kaggle - Customer Personality Analysis (Analysis of company's ideal customers) https://www.kaggle.com/imakash3011/customer-personality-analysis

Goal:

Unravel the correlations among customers' personal background, shopping behaviors and spending trends, as well as provide insights into the optimal marketing strategies for customers divided into different segments.

Tasks:

Data cleaning - Categorize data columns, handle missing data, encode categorical data, scale/normalize numerical data and parse datetime data; Feature engineering - Tranform, combine and/or reduce original feature columns; Exploratory Data Analysis (EDA) - Visualize correlations among features; Clustering/segmentation: Use K-means clustering to divide customers into groups for marketing purposes.