Product Sales Data Analysis Dashboard

Descriptive Analysis of Fashion Product Sales 2014-2023

Identifying market trends, understanding customer preferences, and helping optimize business strategies for fashion products through sales data analysis.

$238,096
Top Product (Sweater)
5
Featured Product Categories
45 Years
Average Customer Age
2014-2023
Analysis Period

🏆 Top 5 Best-Selling Products

💡 Key Insights

  • Sweater ranks first with revenue of $238,096
  • Jeans in second place with $219,219
  • T-Shirts, Sunglasses, and Jackets complete the top 5 featured products
  • Revenue differences between products are relatively significant, showing clear customer preferences

📈 Annual Production Trends

💡 Production Trend Analysis

  • Production peak occurred in 2021
  • Drastic decline occurred in 2021-2023
  • All products experienced similar trends

💰 Annual Sales Trends

💡 Sales Trend Analysis

  • Highest revenue in 2021
  • Strong correlation between production and sales
  • Significant decline post-2021

👥 Average Customer Age by Location

📦 Product Profile (Price & Stock)

📋 Conclusion & Recommendations

🎯 Main Conclusions

  • Featured Products: Sweaters, Jeans, and T-Shirts show the best sales performance with the highest total revenue
  • Significant Decline: Trends from 2021-2023 show a drastic decline in both production and sales
  • Customer Demographics: Average customer age is 42-47 years across major locations
  • Strong Correlation: Production volume is directly proportional to sales revenue

💼 Strategic Recommendations

  • Stock Optimization: Adjust inventory according to declining trends to reduce excess stock
  • Regular Analysis: Monitor trends regularly to identify changes in purchasing behavior
  • Product Development: Develop products according to preferences of the 40s age segment
  • Promotional Strategy: Implement location and demographic-based marketing campaigns
  • Decline Investigation: Research the causes of drastic decline post-2021 for preventive solutions

🔬 Research Methodology

  • Data Source: Company internal dataset (Customers, Products, Sales)
  • Analysis Tools: Microsoft Excel (Pivot Tables), Tableau Public (Visualization)
  • Method: Descriptive Analysis with multi-dimensional data grouping
  • Period: Transaction data from 2014-2023 (10 years)
  • Analysis Focus: Sales trends, production, customer demographics, and inter-variable correlations