AMZ Wholesale Analytics

Overview

AMZ Wholesale Analytics is a proof-of-concept full-stack tool for Amazon sellers that provides:

• A historical sales dashboard with adjustable time filters.
• A wholesale profit margin scanner for uploaded CSVs.
• Automated backend updates via GitHub Actions (every 15 minutes).

Note: This project requires an active Amazon SP-API subscription. Since the owner is no longer selling on Amazon, SP-API access may stop, so functionality may be deprecated.

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Technical Stack

Backend:

• Flask (/src/server/trial.py, /src/server/script.py)
• Flask-CORS
• Firebase Admin SDK (firebase_admin)
• Amazon SP-API integration
• Python 3.9
• dotenv for environment variables

Frontend:

• React (/src/client/src/pages/Scanner.jsx, /src/client/src/pages/Home.jsx)
• ag-grid-react for data tables
• PapaParse for CSV parsing
• Tailwind CSS + DaisyUI for styling
• Theme switching (/src/client/src/components/ThemeController.jsx, /src/client/src/context/themeContext/index.jsx)

Automation/CI:

• GitHub Actions (.github/workflows/actions.yaml) runs script.py every 15 minutes

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Deployment

• Backend (Python / SP-API): Hosted on Render
• Frontend (Next.js / React): Hosted on Netlify

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How It Works

• Amazon Seller Data Integration: Fetches and processes sales/order data using SP-API credentials.
• Historical Sales Dashboard: Displays Visualization of sales trends with interactive charts and tables.
• Profit Margin Scanner: Upload a CSV, parse UPC/costs, calculate profit margins minus fees, ROI, etc., and display results in ag-grid tables.
• Theme Switching: Supports light/dark mode across the dashboard.
• Firebase Integration: Reads/writes data to Firebase Realtime Database.
• Automated Data Updates: GitHub Actions triggers backend scripts every 15 minutes to update data.

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Demo Videos

Dashboard – Historical Sales

Showcases the login, theme switching and sales chart visualization with time filter adjustment (Part 1).

Additional sales charts including line chart, bar chart and area chart graphs (Part 2).

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Scanner – Profit Margin Analysis

CSV upload; backend logic hosted on Render (Part 1).

Selecting parameters necessary for scanning CSV sheet with batch processing (Part 2).

Chart results (Part 3).

More chart results featuring column metrics such as fees, and profit margin calculations (Part 4).

Filtering by profit margin and ROI for best products (Part 5).

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GitHub Actions Automation

Shows the automated 15-minute backend data update workflow (Part 1)

Shows the python script execution and results (Part 2)

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Quick Start

1. Clone the repo

git clone https://github.com/jhalzel/amz-wholesale-analytics.git
cd amz-wholesale-analytics