Retail Sales Analysis

I'm excited to share my latest data analytics project: a comprehensive Retail Performance Analysis Dashboard. Problem: The retail company struggled with a lack of clear insights, making it difficult to track overall performance, understand customer behavior, and manage inventory efficiently. Solution: I developed and deployed an interactive, end-to-end Power BI dashboard. By connecting directly to SQL databases, the solution provides a real-time, holistic view of the business, analyzing key KPIs like sales, profit margins, customer segmentation, supplier performance, and stock health. 📊 Tools Used: Power BI | SQL | Excel | DAX | Data Modeling 💡 Key Insights & Highlights: • Total Sales: ₹5.34M • Profit Margin: 28.77% • YoY Sales Growth: 23.48% • Top Performers: The North Region (₹1.52M) and the supplier "Boat" (₹1.1M) were the primary drivers of sales. • Operational Health: Maintained a 65% delivery rate against a 9.17% return rate. • Actionable Inventory: Identified 3 critical products as "Low Stock" (Stock = Reorder Level), flagging them for immediate re-purchasing. Dashboard Link: https://lnkd.in/gHTPaTce #PowerBI #SQL #DataAnalytics #BusinessIntelligence #Dashboard #DataVisualization #RetailAnalytics #DataInsights

The bottom line for the March data on retail and food services sales is that while these finished the first quarter 2025 on an up note, the quarter as a whole was one of only modest overall gains. March got most of its boost from two components – motor vehicles and building materials. Other categories were broadly higher. In many instances, this represented stocking up on items where consumers were worried about higher prices in the near future. There may also have been some impact from receipts of tax refunds. Most of these factors will have dissipated in April, however, that could get a lift from the spring holidays. In any case, Fed policymakers will take the ongoing moderate consumer activity as a positive for the economy and another reason why no change in monetary policy is needed as yet. Total sales in March were up 1.4%, in line with market expectations. Retail excluding motor vehicles was up 0.5% from the prior month. Retail excluding gasoline was up 0.8% month-over-month. So-called “core” retail – excluding the three most volatile components of motor vehicles, gasoline, and building materials – is up 0.6% in March from February. March sales of motor vehicles and parts accounted for 19.6% of total sales. The dollar value of these sales rose 5.3% month-over-month as the number of units purchased rose substantially. Sales of gasoline accounted for 7.0% of total sales in March. Prices at the pump declined in March and some travel in March was pushed back to April due to the timing of the spring holidays. Gasoline station sales were down 2.5% in March. Sales of building materials had a 5.6% share of total sales for March. The dollar value of building material sales was up 3.3% in March as warmer weather increased demand for outdoor activities like gardening and home repair after the winter months. Sales at nonstore retailers – which include online retailers – composed 17.3% of all sales in March. Although sales only increased 0.1% in March, this sector is a consistent source of sales activity. The Census Bureau will release annual revisions on April 25 which will be incorporated into the April report set for released on Thursday, May 15 at 8:30 ET. #retailsales Please do not use without attribution. Prepared without use of AI. Copyright © Theresa A Sheehan

📊 **Retail Sales Dashboard | Data Analysis Project** I recently built a **Retail Sales Performance Dashboard** to analyze business performance across different dimensions such as **sales, profit, regions, product categories, and customer segments**. This project focuses on understanding key business metrics like **revenue trends, profitability, regional performance, and customer behavior** to generate meaningful insights that can support data-driven decision-making. The dashboard highlights: • Total Sales, Profit, Orders, and Profit Margin KPIs • Monthly revenue trends and seasonal patterns • Regional sales distribution • Category and product profitability • Customer segment analysis To make this project more comprehensive, I also included supporting files for data analysis and preparation. 🔧 **Tools & Technologies Used:** • **Microsoft Excel** – Dashboard development and data visualization • **SQL** – Data analysis and queries • **Python (Jupyter Notebook)** – Additional data exploration and analysis • **GitHub** – Project repository and documentation 📁 The repository includes: • Dataset used for analysis • SQL queries for data exploration • Python notebook for analysis • Excel dashboard file • Dashboard preview images You can explore the complete project and files here: 👉 https://lnkd.in/dmFTyq_a I would love to hear your feedback and suggestions! #DataAnalytics #DataAnalysis #ExcelDashboard #SQL #Python #BusinessIntelligence #DataVisualization