GitHub - bellemai/CustomerSegment: The project aims to better understand the company's customers and make more effective marketing strategies when modifying products to customers in different segments.

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The project aims to better understand the company's customers and make more effective marketing strategies when modifying products to customers in different segments.

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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.

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The project aims to better understand the company's customers and make more effective marketing strategies when modifying products to customers in different segments.

eda pca k-means-clustering correlations machine-learing

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