Customer Personality Analysis
Budget: $10 – $30 USD
Project Description
I need a data specialist to analyze a customer dataset and build a machine learning model based on it. The goal is to understand customer behavior, identify meaningful segments, and generate insights that can help with decision-making. The work should include data cleaning, exploratory analysis, feature engineering, model training, model evaluation, and a final report with clear explanations.
Dataset Description (Customer Personality Analysis)
This dataset contains information about customer demographics, purchase behavior, marketing responses, and overall interaction with a retail business. It is in CSV format with 2,240 rows and 29 columns.
Data Fields
1. Customer Demographics
ID: Unique customer identifier
Year_Birth: Birth year
Education: Education level
Marital_Status: Marital status
Income: Household income
Kidhome: Number of children
Teenhome: Number of teenagers
2. Recency
Recency: Days since the last purchase
3. Spending on Product Categories
Total amount spent in each product category:
MntWines
MntFruits
MntMeatProducts
MntFishProducts
MntSweetProducts
MntGoldProds
4. Purchase Channels
NumDealsPurchases: Purchases with discounts
NumWebPurchases: Web purchases
NumCatalogPurchases: Catalog purchases
NumStorePurchases: In-store purchases
NumWebVisitsMonth: Website visits in the last month
5. Marketing Campaign Responses
AcceptedCmp1 to AcceptedCmp5: Response to previous campaigns
Response: Response to the last campaign
6. Additional Information
Complain: Indicates whether a complaint was filed
Dt_Customer: Date the customer joined
Z_CostContact and Z_Revenue: Internal technical fields
Objectives
I need the freelancer to perform the following:
Data Cleaning & Preparation
Handle missing values
Fix formatting issues
Encode categorical variables
Prepare features for modeling
Exploratory Data Analysis (EDA)
Visualize distributions and correlations
Identify customer patterns and trends
Provide insights and observations
Customer Segmentation Model (Clustering)
Use suitable algorithms (e.g., K-Means)
Provide a clear explanation of chosen cluster numbers
Deliver visual results for the segments
Predictive Modeling (Optional, but preferred)
Build a classification or regression model using relevant fields
Explain feature importance
Evaluate performance
Deliverables
Full analysis report in PDF/Word
Python notebook or script used for the model
Visualizations (plots, charts, cluster diagrams)
Final summary of insights and recommendations
What I Expect
Clear communication
Clean and organized code
Professionally prepared results and visualizations
Ability to explain findings in simple language
If you are experienced in data science, machine learning, and customer analytics, I would be glad to work with you on this project.
I need a data specialist to analyze a customer dataset and build a machine learning model based on it. The goal is to understand customer behavior, identify meaningful segments, and generate insights that can help with decision-making. The work should include data cleaning, exploratory analysis, feature engineering, model training, model evaluation, and a final report with clear explanations.
Dataset Description (Customer Personality Analysis)
This dataset contains information about customer demographics, purchase behavior, marketing responses, and overall interaction with a retail business. It is in CSV format with 2,240 rows and 29 columns.
Data Fields
1. Customer Demographics
ID: Unique customer identifier
Year_Birth: Birth year
Education: Education level
Marital_Status: Marital status
Income: Household income
Kidhome: Number of children
Teenhome: Number of teenagers
2. Recency
Recency: Days since the last purchase
3. Spending on Product Categories
Total amount spent in each product category:
MntWines
MntFruits
MntMeatProducts
MntFishProducts
MntSweetProducts
MntGoldProds
4. Purchase Channels
NumDealsPurchases: Purchases with discounts
NumWebPurchases: Web purchases
NumCatalogPurchases: Catalog purchases
NumStorePurchases: In-store purchases
NumWebVisitsMonth: Website visits in the last month
5. Marketing Campaign Responses
AcceptedCmp1 to AcceptedCmp5: Response to previous campaigns
Response: Response to the last campaign
6. Additional Information
Complain: Indicates whether a complaint was filed
Dt_Customer: Date the customer joined
Z_CostContact and Z_Revenue: Internal technical fields
Objectives
I need the freelancer to perform the following:
Data Cleaning & Preparation
Handle missing values
Fix formatting issues
Encode categorical variables
Prepare features for modeling
Exploratory Data Analysis (EDA)
Visualize distributions and correlations
Identify customer patterns and trends
Provide insights and observations
Customer Segmentation Model (Clustering)
Use suitable algorithms (e.g., K-Means)
Provide a clear explanation of chosen cluster numbers
Deliver visual results for the segments
Predictive Modeling (Optional, but preferred)
Build a classification or regression model using relevant fields
Explain feature importance
Evaluate performance
Deliverables
Full analysis report in PDF/Word
Python notebook or script used for the model
Visualizations (plots, charts, cluster diagrams)
Final summary of insights and recommendations
What I Expect
Clear communication
Clean and organized code
Professionally prepared results and visualizations
Ability to explain findings in simple language
If you are experienced in data science, machine learning, and customer analytics, I would be glad to work with you on this project.