Customer Shopping Behavior Analysis & Retail Insights

Customer Shopping Behavior Analysis

Insights into spending patterns, customer segments, and product preferences using Python, SQL, and Power BI.

Dataset Summary

<li><strong>Volume:</strong> 3,900 Rows, 18 Columns</li><li><strong>Demographics:</strong> Age, Gender, Location, Subscription Status</li><li><strong>Purchase Details:</strong> Item, Category, Amount, Season, Size, Color</li><li><strong>Behavior:</strong> Discounts, Frequency, Reviews, Shipping Type</li>

Data Cleaning & Preparation (Python)

<h3>Missing Data Handling</h3><p>Detected 37 nulls in 'Review Rating'. Imputed using the median rating of each product category to maintain statistical integrity.</p>

<h3>Feature Engineering</h3><p>Created 'age_group' by binning ages and 'purchase_frequency_days'. Standardized all column names to snake_case for consistency.</p>

<h3>Database Integration</h3><p>Verified data consistency (dropped redundant 'promo_code_used'). Loaded cleaned DataFrame into PostgreSQL for advanced querying.</p>

Revenue Analysis by Gender

A significant disparity exists in total revenue generation. Male customers contributed over twice the revenue compared to female customers in this dataset.

Top 5 Products by Average Rating

Accessories like Gloves and Hats, along with Footwear (Sandals, Boots), consistently receive the highest customer satisfaction scores.

Subscribers vs. Non-Subscribers

While non-subscribers generate more total revenue due to volume (2,847 vs 1,053 customers), the average spend per transaction is nearly identical (~$59) between groups.

Customer Segmentation Profile

The business heavily relies on 'Loyal' customers (80%+). There is a significant opportunity to convert 'Returning' users into the loyal tier and to improve acquisition of 'New' users.

Revenue Contribution by Age Group

Young Adults differ as the highest revenue contributors ($62k), followed closely by Middle-aged customers. The distribution is relatively balanced, suggesting broad market appeal.

Power BI Dashboard Overview

An interactive dashboard was built to visualize key metrics: Total Customers (3.9K), Average Purchase Amount ($59.76), and Average Review Rating (3.75). It enables dynamic filtering by demographics and behavior.

Strategic Business Recommendations

<strong>Boost Subscriptions:</strong> Develop exclusive benefits or early access features to drive subscription uptake, as current conversion is low.

<strong>Enhance Loyalty:</strong> Implement rewards for repeat buyers to officially move them into the 'Loyal' segment, maximizing lifetime value.

<strong>Targeted Marketing:</strong> Focus campaigns on 'Young Adults' and 'Express Shipping' users who show higher engagement and revenue potential.

<strong>Product Positioning:</strong> Highlight top-rated items (Gloves, Sandals) in hero campaigns to build brand trust.