This case study focuses on e-commerce, analyzing a dataset of 6500 rows to improve profits based on historical data and recommend effective business strategies.

• Explore Spike's (Doudle-day) impact on ADO and GMV in the platform.
• Analyze capital allocation and efficiency based on ADO and GMV to identify effective and inefficient points.
• Analyze the registration behavior of program packages to propose pitching, selling combos, or adjusting prices.
• Based on the analysis results, propose solutions and expected outcomes.

• Understand and research the business context and situation, find out suitable business metrics;
• Data cleaning and modeling using Excel and Power BI;
• Exploratory data analysis (EDA) on the dataset. Utilize Python and Power BI to analyze significant insights and create actionable reports;
• Suggest cost optimization solutions to increase platform profits