Customer Shopping Behaviour Analysis
Uncovering key drivers of sales, loyalty, and satisfaction through data-driven insights
👤 Author
Abdul Valiyapurakkal Hassan
Project Objectives
Spending Trends
Understand customer purchasing patterns and behavior
Loyalty Drivers
Identify factors influencing repeat purchases and subscriptions
Demographics
Compare performance across gender, age, and channels
Interactive Insights
Build Power BI dashboard for stakeholder exploration
Tools & Technologies
Python
Data cleaning, preprocessing, and modeling in Jupyter Notebook
SQL Server
Querying and extracting insights from structured data
Power BI
Building dashboards and visualizing insights
GitHub
Version control and project file storage
Data Preparation
01
Data Loading
Imported dataset using pandas, explored structure with df.info()
02
Data Cleaning
Imputed 37 missing Review Rating values using median by category
03
Feature Engineering
Created age_group and purchase_frequency_days columns
04
Database Integration
Connected to SQL Server and loaded cleaned data for analysis
3,900
Total Rows
18
Columns
SQL Analysis Highlights
Revenue by Gender
Males generate slightly more revenue than females
Discount Impact
Some discount users spend above average purchase amount
Top Products
Identified products with highest average review ratings
Shipping Preference
Express shipping users spend significantly more
Customer Segmentation Insights
Loyal Customers
Customers with 10+ purchases demonstrate strong brand loyalty and repeat buying behavior
Subscription Analysis
- 958 repeat buyers are subscribed
- 2,518 repeat buyers are non-subscribers
- Subscribers show stronger loyalty potential
Key Opportunity: Expanding subscription program could boost repeat purchases
Revenue by Age Group
Young Adults generate the highest revenue at £62,143, showing they are the most active spenders with steady engagement across other age groups
Top Products by Category
Accessories
Jewelry leads with highest total orders
Clothing
Blouse & Pants show strong performance
Footwear
Sneakers demonstrate consistent demand
Well-balanced customer interest across all categories indicates diverse shopping preferences
Key Insights
Young Adults Lead
Generate highest revenue, followed by middle-aged customers
Loyalty Matters
Loyal customers form largest segment, showing strong retention
Subscribers Win
Spend more with higher repeat purchase rates
Category Leaders
Clothing and Accessories lead in sales and revenue
Discounts Work
Encourage higher spending, proving effective for growth
Premium Service
Express shipping users spend significantly more
Business Recommendations
Strengthen Loyalty Programs
Boost subscription adoption to increase repeat purchases
Promote Top Products
Focus on Jewelry, Blouses, and Sneakers with highest ratings
Strategic Discounts
Target high-value transactions to increase spending
Focus on Young Adults
Concentrate marketing on most active spending demographic
Highlight Express Shipping
Position as premium value-added feature
By leveraging insights on customer segments, product performance, and spending patterns, the company can enhance retention and drive sustainable growth.