π Specifications β AI Development for Product Research and SEO [French Market]
π― Context & Objective
A concrete and strategic mission: automate and enhance product research (winners) and high-potential SEO keywords through AI for the Winners Club.
π§© Current Challenges
- 7 team members currently dedicated to manual research of products and keywords.
- Use of platforms such as:
- Data tracking is done in a shared Google Sheet, including links to sources and weekly manual validation.
- Objective: 10 validated new products per week.
π§ Project Goal (AI)
Create an autonomous or semi-autonomous tool that:
- Automates trending, high-potential SEO keyword discovery.
- Performs intelligent scraping of e-commerce and ad sources.
- Uses AI to correlate keywords with potentially winning products.
- Generates a weekly prioritized list of products and keywords for human validation.
- Automatically fills a dashboard or database (e.g., Google Sheet, Notion, Airtable, Supabase, etc.).
βοΈ Expected Features for this POC (Proof of Concept)
1. π Trend Detection
- Use the Google Trends API (country-by-country in Europe + USA).
- Identify emerging keywords in major e-commerce categories.
- Combine with SEMrush databases or free alternatives (e.g., Ubersuggest, Ahrefs API if available).
2. π§° Multi-Source Scraping
Scrape the following sources, with filters by country/language (non-exhaustive):
- Facebook Ads Library (by keyword or specific pages)
- TikTok Creative Center / Ads Library
- Amazon Best Sellers
- Google Shopping
- Mindeo
- Competitor stores (predefined list)
β οΈ The scraper must:
- Avoid duplicates
- Tag already analyzed products
- Allow filtering by date / recency
3. π€ AI Correlation & Scoring
- Correlate trending keywords with found products.
- Generate a relevance score based on:
4. π Output & Visualization
- Create a management app for keywords/products by niche, including:
- Product database should include:
- Interface: ideally a user-friendly web app, initially connected to Google Sheet for easy integration into the current workflow.
π‘ Example Use Case
- A trending keyword is detected on Google Trends: βanti-mosquito fly summer 2025β.
- The AI scrapes Amazon, TikTok, Mindeo and finds products in this category.
- It cross-checks product appearances with Facebook/TikTok ads.
- It scores the product and adds it to the database with associated details.
π Suggested Tech Stack (modifiable)
- Languages: To be determined
- APIs (non-exhaustive):
- Database: Supabase / Google Sheets
- Frontend (v1 simple): Notion or Google Sheet for weekly validation
π
Projected Timeline for Testing
Phase
Deadline
Source gathering (store & category lists)
Day 0
Basic scraping & keyword detection
Day 3
AI correlation between keywords & products
Day 6
Delivery of test dashboard with 10 proposed products
Day 7
β
Success Criteria
- Deliver at least 10 relevant product suggestions correlated with high-potential keywords.
- Tool must work at least in semi-autonomy, with minimal manual intervention.
- Provide clear documentation of how it works.
- Scalability to other niches or sources is a bonus.
So we need someone who speaks french better, can do the demo within 7 days test to show it works.