📊 Nike Sales Analysis – Boosting Revenue with Data

📌 Project Overview

This Power BI project analyzes Nike's sales data to understand key trends, customer behavior, and product performance. Based on insights from the data, I have provided actionable recommendations to increase sales and profitability.

🔍 Key Findings & Analysis

🛒 1. Sales Trends & Performance

✔ Identified peak sales periods and seasonal fluctuations.
✔ Noticed a sales drop in Q2, indicating possible issues in marketing or product demand.
✔ Sales were highest in urban areas with strong digital engagement.

👥 2. Customer Segmentation

✔ 65% of total sales came from customers aged 18-30.
✔ Repeat customers generated 40% more revenue than first-time buyers.
✔ Female customers preferred lifestyle products, while male customers leaned towards sportswear & running shoes.

👟 3. Product Performance Analysis

✔ Best-selling products: Running shoes & sportswear.
✔ Underperforming products: Some casual wear and accessories.
✔ Discounted products saw higher sales volume but reduced profitability.

🛍 4. Sales Channels & Marketing Insights

✔ Online sales grew 30% faster than physical store sales.
✔ Influencer marketing campaigns increased sales by 25% compared to regular ads.
✔ Stores in metro cities performed significantly better than rural areas.

💰 5. Pricing & Profit Margins

✔ A 5-10% price increase on premium products did not affect demand.
✔ Bundling products (e.g., shoes + socks) led to 15% more purchases per order.
✔ A dynamic pricing strategy could optimize revenue during peak seasons.

---

🚀 Recommendations to Increase Sales

📈 1. Enhance Digital Presence

• Invest more in social media ads & influencer partnerships.
• Launch limited-time online exclusive products to drive urgency.

👟 2. Optimize Product Strategy

• Expand top-performing product categories (sportswear & running shoes).
• Reduce production of underperforming items & test new designs.

📍 3. Expand to High-Demand Locations

• Focus on metro cities with proven high demand.
• Strengthen e-commerce reach in lower-performing regions.

💡 4. Improve Customer Retention

• Launch a Nike Loyalty Program with rewards for repeat purchases.
• Use personalized recommendations & targeted discounts based on customer behavior.

🎯 5. Dynamic Pricing & Promotions

• Implement AI-driven dynamic pricing based on demand & seasonality.
• Introduce bundle offers to increase average order value.

---

📁 Project Files

📌 Nike Sales Analysis.pbix → Power BI Dashboard
📊 Data/ → Raw data files

🚀 How to Use

1️⃣ Download the .pbix file.
2️⃣ Open in Power BI to explore the interactive dashboard.
3️⃣ Use the insights to optimize Nike’s sales & business strategy.

---

🔗 Connect with Me

👤 Ashad K
📧 ashadakber32@gmail.com
🔗 GitHub
🔗 LinkedIn