Contact person: Business Client

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Location: Williamsport, United States

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I need a full-stack analytics platform that automatically scrapes eBay and Vinted for clothing listings, processes the data, and presents clear, actionable insights in a modern web dashboard.

Core workflow
• Scrape new and historical listings from both marketplaces on a scheduled basis.
• Parse and store key fields (brand, model, size, condition, listing price, sold price, images, URLs, dates).
• Run analytics that surface top-selling clothing items, trending brands, and pricing patterns.
• Calculate sell-through rates so I can see how quickly items actually move.
• Generate AI-style sourcing recommendations (e.g., “Carhartt Detroit Jacket in black is rising 23% week-over-week”).
• Show an item preview card with thumbnail, quick stats, and a direct link back to the live listing.

Dashboard expectations
The UI should feel clean and lightweight—think simple dark-mode toggle, responsive charts, filterable tables, and brand or keyword search. A single-page React or Vue front end that talks to a Python (FastAPI or Django) or Node back end is fine as long as the codebase is organised and documented.

Minimum deliverables
1. Scraper modules for eBay and Vinted with retry logic and basic bot avoidance.
2. Normalised database schema (PostgreSQL or MongoDB) seeded with sample data.
3. API endpoints that the front end can hit for aggregated metrics and item detail.
4. Web dashboard with the insights and features listed above.
5. Setup guide plus a short video walk-through that proves the system works end-to-end.

Acceptance criteria
• Fresh data from both sites visible in the UI after running the scraper.
• Charts accurately reflect top sellers, trending brands, and pricing shifts.
• Sell-through rate calculations match sample spot checks.
• Recommendation engine outputs at least three justified suggestions per run.
• All links and images load correctly, with no broken references.

If you have experience with marketplace scraping, data visualisation, and a touch of ML for recommendations, this project should feel right at home." (client-provided description)