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. Apply tot his job