E-Commerce Shopping Behavior & Predictive Analytics Dashboard
Overview
This Power BI dashboard provides a comprehensive analysis of customer shopping behavior, designed to help e-commerce businesses understand purchasing patterns and optimize marketing strategies. Developed as part of a predictive analytics project, it transforms raw transaction data into actionable insights regarding customer demographics, product preferences, and seasonal trends.
Key Features & Visuals
Customer Demographics Analysis: Deep dive into consumer profiles, segmenting data by age, gender, and location to identify primary customer bases.
Purchasing Patterns: Visualizes average transaction values, frequency of purchases, and the most popular product categories.
Engagement Metrics: Tracks the effectiveness of discounts, promotional codes, and loyalty programs on overall sales volume.
Shipping & Payment Preferences: Analysis of preferred shipping methods and payment gateways used by different customer segments.
Review & Rating Analysis: Correlates product ratings with purchase frequency to understand customer satisfaction and its impact on repeat business.
Technical Implementation
Data Modeling: Built with a robust star-schema data model ensuring efficient performance and accurate cross-filtering.
DAX Measures: Includes custom DAX calculations for Key Performance Indicators (KPIs) such as total revenue, average rating per category, and discount impact analysis.
Advanced Visualizations: Utilizes a mix of native Power BI visuals and conditional formatting to highlight critical outliers in consumer behavior.
Interactive Slicers: Dynamic filtering by season, category, and region for granular data exploration.
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