n8n Product Research Automation

I want a complete n8n workflow that automates my ecommerce product discovery exactly as shown in the Loom video attached. The end-to-end flow should:

• Pull fresh product data from Amazon and AliExpress.
• Check Google Trends for each product keyword to gauge current and historical interest.
• Grab related YouTube video stats—especially watch counts—to confirm real-world demand.
• Apply the following filters in sequence: Google Trends score, price margins between Amazon and AliExpress, sales volume, watch counts .
• Output the products to a neatly formatted Google Sheet, even the ones that failed the filters, then indicate the products that pass every filter

Key expectations
1. Demonstrate the finished automation in a short screen recording, including a recording of the execution showing the results.
2. Include clear, step-by-step setup notes so I can plug in my own API keys or proxies, schedule runs, and tweak thresholds later.
3. Keep modules and expressions clean so I can expand the flow in the future (e.g., additional marketplaces).
4. Build and hand over a ready-to-import .json n8n workflow.

I’ve detailed the logic and example filters in the Loom; please watch it before you bid. My goal is to hit “Run” and instantly receive a shortlist of winning products—no manual scraping, no guesswork.

If you have proven n8n experience with e-commerce data, let’s get started right away.

Here is the Loom video overview:
https://www.loom.com/share/dac2f99082ec4bfb9ae6caac7e8be152

Here is the YouTube video in that Loom:
https://youtu.be/HTlmvJfRCfs