Dashboard Link : https://app.powerbi.com/links/Bx0PNZeGlK?ctid=a1a4ee51-99fa-437d-8ba7-d05192f6c077&pbi_source=linkShare&bookmarkGuid=e0b17b44-83e2-4b57-9279-c722148d51ce
Amazon Sales Dashboard Analysis Report Report Summary: This report analyzes key sales metrics, customer feedback, and operational data for Amazon to help improve product offerings, sales strategies, and customer satisfaction. The report was created using Power BI Desktop and published to Power BI Service. The dashboard highlights essential insights from sales data, product performance, customer satisfaction ratings, and order fulfillment metrics, aiming to optimize business operations and enhance customer experience.
Metrics and Calculations:
Step 1: Loading and Cleaning the Data The dataset was loaded into Power BI from a CSV file for analysis. The data was then cleaned using Power Query Editor. In the Power Query Editor, columns with missing or inconsistent values were reviewed, and necessary transformations were applied. For example, rows with null values or errors were handled appropriately, and data types were corrected to ensure the dataset was clean and ready for analysis.
Step 2: Sales Parameters and Average Ratings The analysis focused on key sales parameters affecting customer satisfaction and operational efficiency. Key performance indicators (KPIs) such as product quality, shipping speed, and customer service were measured, and ratings were calculated for the following parameters:
Product Quality: 4.25/5 Ease of Navigation on Website/App: 4.38/5 Delivery Timeliness: 4.12/5 Ease of Online Purchase: 4.41/5 Payment Process Transparency: 4.30/5 Customer Support: 3.98/5 Return/Refund Process: 4.14/5 Promotional Offers & Discounts: 4.07/5 Packaging Quality: 4.26/5 Mobile App Features: 4.18/5 Order Notification Process: 4.22/5 Personalized Recommendations: 4.12/5 Checkout Convenience: 4.36/5 Step 3: Key Visualizations Added to the Dashboard
Branding:
Company name and tagline displayed using text boxes. Amazon logo inserted for visual branding. Sales Data Segmentation:
A calculated column was created for product categories, sales region, and customer type segmentation using DAX expressions for further analysis. Step 4: Total Sales and Customer Distribution
Total Sales Volume:
Total sales volume represented via a card visual, which shows overall sales in terms of revenue and units sold. Customer Type Breakdown:
Segmented customers into new and returning categories to understand repeat business and customer loyalty. Returning customers: 62% New customers: 38% Step 5: Product Category Distribution
Sales data was segmented by product categories to identify high-performing and underperforming products. Categories include: Electronics: 35% Clothing & Apparel: 28% Home Goods: 18% Books: 10% Others: 9% Step 6: Order Fulfillment Insights
Average Shipping Time:
Calculated the average shipping time to identify delays in fulfillment and processing, displayed in a card visual. Average shipping time: 3.5 days Average Delivery Delay:
Calculated the average delivery delay (in days) and tracked delayed shipments to help improve fulfillment speed. Average delivery delay: 0.8 days Insights from the Dashboard:
Sales Distribution:
Total sales for the analyzed period amounted to $4,500,000. The Electronics category generated the highest revenue, contributing to 35% of total sales. Customer Feedback:
Product Quality: Customers rated product quality the highest, at 4.25/5. Customer Support: This area was identified as needing improvement, with a rating of 3.98/5. Sales Growth Trends:
A growth rate of 15% was observed in year-over-year sales for the Electronics category. Clothing & Apparel showed a decline in sales by 5% over the last quarter. Average Delays:
The average shipping time was 3.5 days, indicating room for improving fulfillment speed. There is a slight delay in delivery, with an average delay of 0.8 days. Recommendations:
Improve Customer Support:
Focus on enhancing the responsiveness and effectiveness of customer service, possibly by implementing chatbots and improving knowledge base resources. Optimize Shipping and Delivery:
Reduce delivery times and improve fulfillment by optimizing logistics and collaborating with faster shipping providers. Focus on High-Performing Categories:
Increase marketing and promotional efforts for the Electronics category, which has shown the highest growth and customer satisfaction. Enhance Product Availability:
Ensure high-demand products, especially in the Electronics and Clothing categories, are well-stocked and available for fast delivery. Promotions and Discounts:
Focus on better promotional offers for the Books and Home Goods categories to stimulate sales in those areas, which have lower revenue contributions. By leveraging these insights, Amazon can fine-tune its operations, improve customer satisfaction, and drive greater sales performance across its product categories.