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Writer's pictureJiasheng Qu

Assessing the Health of E-commerce Business



Introduction


In this project, I serve as the Data Analyst for a startup named Maven Fuzzy Factory, an online toy retailer. If you're interested in learning how I used SQL to address business challenges, please follow this link. If access to Power BI is an issue, you can download the PDF version of the dashboard here.


The management and marketing teams aim to track Key Performance Indicators (KPIs), analyze trends, and make data-driven decisions. The challenge was not just in collecting data but in making sense of it in a way that would drive the business forward.


The Objective


  1. Connect Power BI with MySQL.

  2. Build a relational data model: Organize the data into a structured model that reflects the real-world relationships between different entities.

  3. Create calculated columns and measures with DAX.

  4. Design an interactive dashboard to visualize the data.


Validation of Results


To ensure accuracy and reliability, I compared the Power BI dashboard results with those obtained directly from SQL queries. Additionally, applying business acumen was crucial in evaluating whether the trends and numbers made logical sense within the context of the business operations.


Insights from the Dashboard


Page 1: Overview of Financial Health
  • Financial Metrics: Monthly revenue, COGS, and profit metrics, including their Year-Over-Year growth rates, provide a snapshot of the financial health. The analysis reveals a Year-Over-Year (YOY) growth of 15.78% in monthly revenue, signaling a robust increase in sales. The Monthly Cost of Goods Sold (COGS) also grew by 15.12%, slightly less than revenue growth, hinting at an enhancement in profitability.

  • Product Performance Trends: Visualization of quarterly revenue and profit trends offers insights into the performance and contribution of different products.


Pages 2 to 4: Operational Insights and Consumer Behavior
  • Order Trends: I observed a notable YOY increase of 76.6% in quarterly orders, indicating a strong demand for our products.

  • Device Usage: Data indicates a predominant use of desktops for online shopping, a critical insight for optimizing user experience.

  • Traffic Source Analysis: While gsearch remains the primary traffic source, a notable shift from socialbook highlights changing consumer discovery pathways. I believe this is a strategic shift in content marketing efforts away from socialbook.

  • Pageview Counts by URL: Underlines the popularity and engagement of specific pages on the website over time, such as /the-original-mr-fuzzy and /products, guiding content and marketing strategies


Conclusion


In this project, I used Power BI to improve Maven Fuzzy Factory's use of data in making decisions. The company appears to be in a healthy state, with strong growth in revenue, profit, and customer engagement metrics. I found that customer engagement and orders increased, customers preferred using desktops, and there were changes in where our traffic comes from, showing that customer habits are changing. This dashboard gives a clear picture of our business now and helps our management and marketing teams plan for growth and success.


Thank you for taking the time to read my project! If you have any feedback or suggestions, please don't hesitate to reach out to me. You can contact me at jiashengqu@outlook.com, or if you'd like to connect on LinkedIn, please feel free to send me a connection request.

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