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.

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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.

  • Product Selection: Choosing products with 4 or 5-star ratings increases the likelihood of successful orders.

  • Optimal Joining Time: Sellers should consider joining Amazon in September, October, or November for better results.

  • Product Profitability: It is risky to sell products with negative profits; therefore, products with positive profits should be selected .

  • 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.