Amazon-Sales-Analysis
May 24, 2024 ยท View on GitHub
This repository contains an analysis of Amazon sales. The objective is to analyze Amazon sales data and formulate a strategy for a new seller based on the insights derived.
Technologies used:
- Oracle SQL: as the database,
- Python (Pandas): for data cleaning,
- Qlik Sense: for data visualization.
Analysis Results:
- FBA Sellers: Joining Amazon as an FBA (Fulfilled by Amazon) seller seems more logical as it increases the likelihood of receiving orders.
Note: According to additional research, AMZ types are products sold directly by Amazon, while individuals can join as FBA or FBM (Fulfilled by Merchant) sellers.
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Product Selection: Choosing products with 4 or 5-star ratings increases the likelihood of successful orders.
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Optimal Joining Time: Sellers should consider joining Amazon in September, October, or November for better results.
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Product Profitability: It is risky to sell products with negative profits; therefore, products with positive profits should be selected .
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Shipping Type: Choose the shipping type that aligns with your plan in terms of time and cost .
Note: Additional research indicates that shipping by sea takes approximately four times longer than shipping by air.