Customer Shopping Behavior Analysis with Data Analytics

🛒 3,900 transactions. One question: What makes customers spend more? I built a full end-to-end data analysis project to find out. Here's what the data revealed: 📌 Clothing dominates both revenue & sales across all segments 📌 73% of customers are non-subscribers — a massive untapped opportunity 📌 Young Adults & Middle-aged customers drive the highest revenue 📌 Average purchase amount: $59.76 with a solid 3.75 rating Tools used: Python (EDA & cleaning) → SQL (business queries & segmentation) → Power BI (interactive dashboard) The real skill in data analytics isn't just running queries - it's knowing which questions to ask. #DataAnalytics #Python #SQL #PowerBI #DataScience #Portfolio

🚀 Excited to share my latest Data Analytics Project! 📊 Customer Behavior Analysis using Python, SQL & Power BI In this project, I analyzed customer purchasing behavior to uncover actionable insights and trends. 🔍 Key Highlights: • Data cleaning and preprocessing using Python • Performed Exploratory Data Analysis (EDA) • Used SQL for querying and insights extraction • Built an interactive Power BI dashboard 📈 Key Insights: • High-value customers contribute most of the revenue • Certain product categories perform better • Seasonal trends impact purchasing behavior • Discounts influence buying frequency 📊 The dashboard helps businesses make data-driven decisions and understand customer trends. 🔗 GitHub Repository: (https://lnkd.in/g9UZmNs8) #DataAnalytics #Python #SQL #PowerBI #DataScience #Portfolio #Projects

Excited to share a data analytics project I recently worked on! 📊 Customer Shopping Behavior Analysis Tools: SQL | Python | Power BI In this project, I analyzed over 3,900 customer transactions using SQL, Python, and Power BI to uncover meaningful business insights and trends. Key contributions: • Performed data cleaning and feature engineering using Python (Pandas) • Designed and queried a PostgreSQL database using SQL • Built interactive dashboards in Power BI for data visualization Key insights: • Subscription customers spend 68% more and demonstrate higher loyalty • Female customers contribute slightly higher revenue • Express shipping users show higher average transaction values. This project enhanced my ability to translate raw data into actionable business insights. 🔗 Project Link: https://lnkd.in/gTmmXjbS #DataAnalytics #SQL #Python #PowerBI #BusinessIntelligence #DataDriven

📊 I built an end-to-end Customer Churn Analysis project using Python + Machine Learning + Power BI. Here’s what I found: 💡 Key insights: • ~33% churn rate across 100k customers • Month-to-month contracts show the highest churn (~46%) • The first 12 months are the most critical for retention • High-paying customers are more likely to churn 🔧 What I built: • EDA + statistical testing (Chi-square) • Feature engineering (tenure groups, avg revenue) • Logistic Regression model (ROC-AUC ~0.79) • Interactive Power BI dashboard with risk segmentation 📈 This project simulates real-world product analytics and shows how data can drive retention strategy. 🔗 Check it out: GitHub → https://github.com/RuiCDev Dashboard → https://bit.ly/3Qadvjk Feedback is welcome 👇 #PowerBI #DataAnalytics #MachineLearning #SQL #DataScience #AnalyticsPortfolio #Churn #CustomerRetention

Excited to share my latest project on Customer Shopping Behavior Analysis! Worked with 3,900+ records to perform data cleaning, EDA, SQL analysis, and built a Power BI dashboard. Key insights include revenue trends by age group, customer segmentation, and discount behavior. This project helped me strengthen my skills in Python, SQL, and data visualization. #DataAnalytics #Python #PowerBI #PostegreSQL #MYSQL Amlan Mohanty

Had some free time on Friday so built this 👇 Customer Behavior Analysis | Python, SQL, Power BI Analyzed 3,900+ customer shopping transactions to extract meaningful insights. Here's the breakdown: 📊 What I did: - Python: Cleaned messy data, handled missing values, engineered features - SQL : Executed queries for revenue segmentation & loyalty analysis - Power BI: Built an interactive dashboard with multi-dimensional filtering 💡 What I found: ✓ 70%+ customer retention rate ✓ Adults (25-55 years) drive 60% of revenue ✓ Free shipping generates highest transaction volume ✓ Repeat customers show 40% higher lifetime value 🎯 Real takeaways: - Age segment matters more than gender for targeting - Shipping options significantly impact conversion - Loyalty programs drive repeat purchases Github Link for pbix, ipynb and excel file : (https://lnkd.in/gaGj8usx) #DataAnalytics #PowerBI #SQL #Python #DataScience #BusinessIntelligence #SideProject

https://lnkd.in/dc4xdegR Ever wondered what drives customer shopping behavior? 🤔 I explored this question by analyzing 3,900+ transactions across multiple product categories. Here’s what stood out: 📌 A small segment of customers drives the majority of revenue 📌 Non-subscribers contribute 73% of total sales 📌 Discounts significantly influence buying decisions for certain products 📌 Loyal customers dominate — but new customer acquisition is low To visualize these insights, I built an interactive dashboard using Power BI. 🛠 Tools used: Python, MySQL, Power BI This project helped me strengthen my skills in data cleaning, SQL analysis, and business storytelling. here the GitHub repo- https://lnkd.in/dc4xdegR Check out the presentation and let me know your thoughts! #DataAnalytics #SQL #Python #PowerBI #Learning #DataProjects

Excited to share my latest project on Customer Behavior Analysis Dashboard 🚀 Built using Python, PostgreSQL, and Power BI, this dashboard transforms raw customer data into meaningful insights that support data-driven decision-making. 🔹 Key Highlights: Data extraction & preprocessing using Python Structured storage and querying with PostgreSQL Interactive and dynamic visualizations in Power BI Customer segmentation based on purchasing patterns Trend analysis to identify high-value customers and retention opportunities 🔹 Impact: This project helps businesses better understand customer preferences, optimize marketing strategies, and improve overall customer experience. Always open to feedback and collaboration—let’s connect and build impactful data solutions together! 💡 #DataAnalytics #Python #PostgreSQL #PowerBI #CustomerInsights #DataVisualization #BusinessIntelligence

I recently worked on a Customer Behavior Dashboard to analyze sales performance, customer trends, and product insights. Tools Used: Excel | Python | SQL | Power BI Key Insights: • A few top product categories contribute to the majority of overall revenue • Customers purchasing discounted items showed higher buying frequency • Certain categories generated high sales but lower profit margins • Revenue trends highlighted peak purchasing periods and seasonal demand What I Did: • Cleaned and transformed raw data using Python & SQL • Built Pivot Tables & Charts in Excel for initial analysis • Created KPIs like Total Sales, Revenue, and Category Performance • Designed an interactive Power BI dashboard with slicers for dynamic filtering • Visualized customer behavior and top-performing products. What I Learned: • End-to-end data analysis workflow (cleaning → analysis → visualization) • How to extract meaningful business insights from raw datasets • Building interactive dashboards for decision-making 📷 Dashboard preview attached below 🔗 GitHub: https://lnkd.in/g7VN3GeS #DataAnalytics #PowerBI #SQL #Python #Excel #DataAnalyst #PortfolioProject

📊 Excited to share my latest Power BI project – Customer Churn Analysis! Built an interactive dashboard to analyze telecom customer churn patterns and uncover actionable business insights. 🔍 Key Findings: • Month-to-month contract customers churn the most • Electronic check users show higher churn rates • Higher monthly charges are linked with increased churn 🛠️ Tools Used: Power BI, Python, pandas, NumPy This project helped me strengthen my skills in data visualization, business analytics, and storytelling with data. 🎥 Sharing a quick walkthrough of the project dashboard and workflow. #PowerBI #DataAnalytics #CustomerChurn #BusinessIntelligence #DataVisualization #Python #AnalyticsProject #LinkedInProjects #DashboardDesign