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Title

“SALES OVERVIEW”

Dashboard

Screenshot 2025-01-02 224754 Screenshot 2025-01-02 224832

Project Objective

To find out the total bicycle sales and bicycle-related products in different countries according to the 2015, 2016, and 2017 sales year.

Dataset used

The data set mentioned above as the power BI data set

KPIs

KPIs used are: - • Total Sales • Count of Order • Total Return • Return %

Process

  1. Data collection: Imported data on sales of year 2015,16,17, product category, customer details.
  2. Data cleaning: Handle missing or invalid values Standardize data and time formats.
  3. Data Visualization: Created chart for Total Sales by Subcategory and Status, Sum of Sales and Adjusted sales by Date, Total Sales by Year and Country, Total Sales by Parent Status.
  4. Data Analysis: Calculated KPIs such as Total sales, count of order, Total return, Return %. Categorize data by Category name, gender, region.
  5. Insights Extraction: Identify sales data to improve the sales performance in different region according to product category.

Project insight

  1. Key Metrics Overview: o Total Sales: $24.91M. o Count of Orders: 25,160. o Total Returns: 1,828, with a return percentage of 7.26%. o June 2017 Performance:  Sales: $1.83M, exceeding the goal of $1.77M (+3.31%).  Orders: 2,146, slightly below the goal of 2,165 (-0.88%).
  2. Sales by Subcategory and Status: o High-Income Segment: Road bikes lead with $8M in sales. o Medium-Income Segment: Road bikes and mountain bikes perform well ($2M each). o Low-Income Segment: Mountain bikes dominate ($5M), followed by touring bikes ($2M). o Sales for other subcategories like tires, helmets, and jerseys are significantly lower.
  3. Geographic Performance: o The map visualization highlights sales contributions globally. o Concentrated sales activity in North America, Europe, and parts of Asia.
  4. Trends Over Time: o Sales and adjusted sales show fluctuations, with spikes in certain months (e.g., March and April 2017). o Adjusted sales are dynamically influenced by the price adjustment slider, which is set to -10 in the screenshot.
  5. Customer Insights: o The "Customer Name" dimension selector shows individual customer contributions to total sales. o Top-performing customers include "ABBY RAMAN" and "ABBY SUBRAM" with sales exceeding $4,000.

conclusion

The "Sales Overview" dashboard effectively summarizes key performance indicators, sales trends, and customer demographics.

  1. Performance Highlights: o The business achieved strong sales overall, with notable performance in high-income and low-income segments for specific product categories like road bikes and mountain bikes. o Geographic analysis shows a wide distribution of sales globally, suggesting diverse market penetration.
  2. Areas for Improvement: o Returns are relatively high at 7.26%, indicating potential issues with product quality, customer expectations, or order handling. o Certain product categories, such as helmets and jerseys, have lower sales and may require marketing focus or reassessment.
  3. Recommendations: o Focus on high-performing segments (road bikes, mountain bikes) and regions with strong sales to maximize revenue. o Investigate the reasons behind the high return rate to reduce costs and improve customer satisfaction. o Analyze underperforming categories and regions for potential growth opportunities.
  4. Future Directions: o Incorporate additional customer feedback data to understand reasons for returns. o Track sales trends post-June 2017 to monitor growth and address challenges. o Explore targeted campaigns to improve order volume and meet order goals consistently.

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“SALES OVERVIEW” Using power BI

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