Build an Automated Amazon Review Monitoring & Reporting Tool (AI + Amazon API)
✅ Key Features:
ASIN Configuration: Ability to set up and manage a list of ASINs to track.
Daily Review Monitoring: Automatically fetch new product reviews every 24h.
Either via Amazon SP-API or web scraping (to be discussed).
AI-Based Filtering: Use OpenAI / GPT to classify reviews as negative or policy-violating (e.g. abusive language, product confusion, competitor mentions).
Automated Reporting:
Send an email to Amazon’s review team with the flagged review details.
Keep track of reported reviews.
Follow-up Automation: If Amazon replies with a standard denial, the system should automatically send a follow-up email using predefined templates.
Dashboard / Config UI (MVP): Simple web interface where we can:
Add/remove ASINs
See flagged reviews
Track reporting status
⚙️ Tech Requirements:
Experience with Amazon SP-API (preferred) OR web scraping solutions
Backend: Python (FastAPI, Flask, or Django) or Node.js
Integration with OpenAI GPT API (for review analysis)
Email automation (SMTP or API like SendGrid/Gmail API)
Optional: Basic web dashboard (React, Next.js, or similar)
Who We’re Looking For:
Developer with proven experience in Amazon integrations (SP-API)
Strong skills in automation & AI integration
Ability to build a simple, stable MVP fast (future improvements possible)
Bonus: Familiarity with Chrome Extensions or SaaS architecture
Deliverables (MVP):
Working system that pulls reviews for given ASINs
GPT-based filtering of negative / policy-violating reviews
Automated email reporting to Amazon
Configurable ASIN list + basic review reporting log
Why this is exciting:
Amazon is very strict with review removals – sellers waste huge time manually checking & reporting reviews. This tool saves time and money, and we plan to develop it into a SaaS solution with monthly subscriptions.
To Apply:
Share relevant projects you’ve built (Amazon API, scraping, automation, GPT/OpenAI).
Briefly explain how you would approach fetching reviews (SP-API vs scraping).
Include your estimated timeline for building the MVP.
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