Adidas Sales Analysis: SQL & Power BI

I present a comprehensive analysis of Adidas sales data using SQL & PowerBI. As a personal project to improve my data analysis skills, I leveraged Excel's data manipulation, SQL's data analysis and PowerBI's visualization tools to uncover key insights into sales performance, trends, and patterns. Join me as I analyze the data to highlight useful information that can drive strategic decision-making and enhance business outcomes for Adidas.

Dataset

The dataset used in this analysis was obtained online and covers Adidas sales data from 2020 to 2021. It includes detailed information on sales transactions, including product categories, quantities sold, sales revenue, and regional sales performance. This dataset provides a valuable basis for analyzing sales trends and patterns over the two years. Download Dataset

ANALYSIS SUMMARY:

The analysis was conducted using Excel, SQL and PowerBI,and following a series of steps outlined below:

• Data Cleaning: The initial dataset was assessed for consistency, reliability, completeness, duplicates, and correct spelling. Verification checks were performed to ensure the dataset's integrity and cleanliness.

• Data Analysis: I used SQL to derive meaningful insights from the data.

• Data Visualization: Various PowerBI charts were used to visualize the analysis results. To increase interactivity and improve the dashboard's usability, slicers were implemented.

Dashboard

ANALYSIS PHASE:

• Total Sales, Total Profit, Average Price per Unit, Profit Margin and Total Units Sold:

  • The overall sales for 2020 and 2021 combined is $899.90 M.
  • The overall profit generated within this time frame is $332.13 M.
  • The total units sold amount to 2,478,861 units.
  • The average price per unit sold is $45.22.
  • The profit margin within this time frame is 36.91%.

• Most Effective Sale Method:

  • In-store sales method generated the highest sales of $127.59 M, indicating customers' preference for physically seeing the items.
  • Outlet sales method generated the lowest sales of $96.56M.

• Sales & Profit Analysis:

  • Sales showed a significant upward trend from Q1, peaking in Q3, indicating that more sales occur in the summer. This was followed by a decline, culminating in a profit spike in December due to the holiday season.
  • Q3 recorded total sales of $265.30 M, with July being the highest-performing month, recording sales of $95.48 M.

• Sales by State:

  • The highest-performing region is the West, with total sales of $269.94 M, while the Midwest region has the lowest performance, with total sales of $135.80 M. In terms of states, New York has the highest total sales at $64.23 M while Nebraska has the lowest at $5.93 M.

• Sales by product category:

  • Men's Street Footwear is our top-selling product category. It has performed exceptionally well, with total sales amounting to $208.83 M. This highlights its popularity and its substantial role in Adidas’ total sales.

• Sale Method Share Distribution:

  • The most significant contribution to the overall sales came from in-store transactions. These physical transactions accounted for a substantial percentage, specifically over 38% of the total sales. This highlights the critical role that physical stores play in the company's revenue generation, despite the growing emphasis on online sales channels.

FINDINGS:

1. In-store sales were the most effective method, generating $127.59 M in revenue. In contrast, online sales were lower, totaling $107.99 M. Therefore, it's crucial to improve the online sales platform and apply targeted digital marketing strategies to increase online sales.
2. The West region led in performance, achieving total sales of $269.94 M. States with sales under $8 million need targeted improvement strategies to unlock their potential.
3. Men’s Street Footwear emerged as the top-selling product category, contributing $208.83 M in sales. Understanding customer preferences is crucial for targeting marketing efforts effectively.