📊 Motorola Mobile Sales Dashboard (Power BI)

📌 Project Overview

This project aims to analyze Motorola mobile sales data using Power BI. The process includes data cleaning, exploratory data analysis (EDA), feature generation, financial modeling, and interactive visualizations. The dashboard provides insights into sales performance, customer behavior, payment methods, and city-wise distribution to support data-driven decision-making.

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🛠️ Steps Followed

1. Data Collection

• Gathered Motorola mobile sales data from internal sources.

2. Data Preprocessing

Cleaning Raw Data:

• Handled missing values, duplicates, and outliers.
• Standardized formats and corrected data types for consistency.
• Ensured accurate numerical and categorical representations for analysis.

3. Exploratory Data Analysis (EDA)

Feature Generation:

• Created new features such as average sales per transaction, monthly trends, and customer rating metrics.
• Identified key metrics and KPIs relevant to Motorola sales performance.

Visualizations:

• Explored trends, patterns, and correlations in the data using Power BI.
• Generated charts for sales by city, payment method, and weekday.

4. Financial Modeling

• Calculated total sales, total quantity sold, total transactions, and average sales per transaction.
• Analyzed revenue contributions by payment method and city.
• Modeled sales projections based on historical trends and seasonal fluctuations.

5. Analysis

Sales Performance:

• Identified top-performing cities: Delhi, Mumbai, Ranchi, Chennai, Rajkot, Bangalore, Hyderabad, Kolkata.
• Tracked monthly sales fluctuations (1,400–1,700 units) and weekday patterns (Saturday, Monday, Friday, Tuesday).

Customer Insights:

• Analyzed customer ratings: 5 Stars: 100%, 4 Stars: 20.8%.
• Identified customer payment preferences: UPI 26.36%, Debit Card 24.72%, Credit Card 24.69%, Cash 24.22%.

6. Dashboard Creation

• Designed an interactive Power BI dashboard presenting key insights.
• Included filters for Motorola mobile models, payment methods, and day of the week.
• Added geographical sales maps, trend charts, and rating distributions.

7. Reporting

• Generated reports highlighting Motorola sales performance, trends, and recommendations.
• Provided actionable insights for sales strategy and customer experience improvement.

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✨ Key Insights

• Total Sales: ₹769M
• Total Quantity Sold: 19K units
• Total Transactions: 4K
• Average Sales per Transaction: ₹40K

🔹 Sales by Payment Method

• UPI: 26.36%
• Debit Card: 24.72%
• Credit Card: 24.69%
• Cash: 24.22%

🔹 Customer Ratings

• 5 Stars: 100%
• 4 Stars: 20.8%
• Lower ratings gradually decline

🔹 Top Performing Cities

• Delhi, Mumbai, Ranchi, Chennai, Rajkot, Bangalore, Hyderabad, Kolkata, etc.

🔹 Seasonal Trends

• Monthly sales fluctuate between 1,400–1,700 units.
• Weekday analysis shows consistent sales across Saturday, Monday, Friday, and Tuesday.

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📈 Business Impact

• Identifies top-selling Motorola models.
• Highlights city-wise demand distribution.
• Optimizes sales strategy based on customer preferences & payment behavior.
• Supports customer satisfaction tracking through ratings analysis.

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🚀 How to Use

1. Open the .pbix file in Power BI Desktop.
2. Use filters for:
   • Motorola Mobile Model
   • Payment Method
   • Day of Week
3. Explore visualizations to gain insights on Motorola sales, transactions, and customer behavior.

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🛠️ Features of the Dashboard

• 📍 Geographical Sales Map – Visualizes city-wise Motorola sales performance.
• 📊 Monthly & Weekly Trends – Understand seasonality and sales cycles.
• 💳 Payment Method Analysis – Track customer preferences for transactions.
• ⭐ Customer Ratings Distribution – Assess satisfaction levels.
• 📱 Motorola Model Insights – Identify top-selling Motorola models.

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📂 Files Included

• Motorola_Sales_Dashboard.pdf – Exported report overview.
• Motorola_Sales_Dashboard.pbix – Power BI dashboard file.

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🧑‍💻 Author

Developed by Prerna
📍 Rajiv Gandhi Institute of Petroleum Technology