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Tableau Project – Customer Personality Analysis

Goal: Analyze customer demographics, spending behavior, and campaign response to uncover insights that can inform marketing strategies.

Tools Used: Tableau, Excel

📝 Dataset Overview

Source: Kaggle – Customer Personality Analysis
Records: ~2,210 customers
Columns include:
- Demographics: Age, Marital Status, Education, Income
- Spending: Amount spent on wine, meat, fruits, fish, etc.
- Campaigns: Response to 5 previous campaigns and one final campaign
- Others: Number of children, Recency (days since last purchase)

📊 Analysis Questions

Which customer segments spend the most?
How does income level affect spending patterns?
What demographics respond best to marketing campaigns?
What is the relationship between age and product preferences?

🔧 Data Cleaning Steps

Created Age = 2024 - Year_Birth
Created Age_category =IF(C2<21, “1-20”, IF(C2<41, “21-40”, IF(C2<61, “41-60”, IF(C2<81, “61-80”, IF(C2<101, “81-100”, “100+”)))))
Created Total_Children = Kidhome + Teenhome
Created Total_Spend = sum of all Mnt columns
Created Campaign_Response_Total = sum of AcceptedCmp1 to AcceptedCmp5 & Response
Cleaned nulls in Income

📈 Visualizations Created

Viz Type	Description
Bar Chart	Avg spend by education level
Box Plot	Income vs Total Spend
Heatmap	Response rate by Age and Income
Stacked Bar	Campaign acceptance by marital status
KPI Cards	Avg Income, Avg Recency, Response Rate
Filters	Age, Education, Marital Status

🔍 Key Insights

Customers aged 21–60 with high income are the top spenders.
Married and educated individuals are more likely to accept marketing campaigns.
Parents with children at home respond less to campaigns.
Wine and meat are the top spending categories across all groups.

🖼️ Dashboard Preview

Customer Dashboard

🔗 Links