Automated Feedaty Review Scraper 📈 using ScrapegraphAI & Gemini 3

Description

This workflow automates the entire process of collecting, analyzing, and reporting customer reviews from Feedaty (similar to Trustpilot) using ScrapeGraphAI, transforming raw user feedback into a structured, management-ready reputation report in PDF using new Gemini 3 model and ConvertAPI & Upload to Google Drive.

Key Advantages

✅ End-to-End Automation

From data collection to final PDF delivery, the entire reputation analysis process is fully automated, eliminating manual scraping, copy-paste work, and reporting overhead.

✅ AI-Driven, Management-Ready Insights

The workflow does not just summarize reviews it interprets them strategically, producing insights that are immediately useful for:

Management
Marketing
Customer Support
Operations
Product & UX teams

✅ Structured & Consistent Reporting

Every execution produces reports with the same structure, metrics, and logic, making it ideal for:

Periodic reputation monitoring
Trend analysis over time
Internal performance reviews

✅ Scalable & Configurable

Easily adaptable to any Feedaty company profile
Page limits and review volume can be adjusted without changing logic
Can be scheduled or extended to multiple brands

✅ Data Quality & Compliance

No personal data exposure
Explicit handling of missing or ambiguous information
No assumptions or hallucinated insights
Fully transparent and audit-friendly output

✅ Seamless Stakeholder Distribution

Automatic upload to Google Drive ensures reports are centralized, shareable, and accessible, with no additional manual steps.

Ideal Use Cases

Brand & reputation monitoring
Customer experience audits
Quarterly or monthly executive reports
Pre-sales or investor documentation
Customer support performance evaluation

How it works
This workflow automates the entire process of collecting, analyzing, and reporting customer feedback from Feedaty.

It starts by scraping live reviews from a specified company's Feedaty page using ScrapeGraphAI, extracting review details like date, rating, and text. Each review is then individually analyzed for sentiment (Positive, Neutral, or Negative) using an AI model.

All processed reviews are aggregated and passed to a specialized AI agent that performs a comprehensive company-level reputation analysis, generating a structured management report.

Finally, the report is converted into an HTML/PDF format and uploaded to a designated Google Drive folder, creating a fully automated pipeline from data collection to actionable insights delivery.

Set up steps
Configure Parameters: Set the Feedaty company identifier (e.g., maxisport) and the maximum number of review pages to scrape in the "Set Parameters" node.
API Credentials: Ensure the following credentials are configured in n8n:
ScrapeGraphAI API (for web scraping)
Google Gemini API (for AI sentiment analysis and report generation)
Google Drive OAuth2 (for file upload)
ConvertAPI (for HTML to PDF conversion)
Customize Output: Optionally adjust the "Limit reviews" node to control the number of reviews processed and modify the AI agent's system prompt in "Company Reputation Management" to tailor the report format.
Destination Folder: Verify the Google Drive folder ID in the "Upload file" node points to the correct destination for the generated reports.
Execution: Trigger the workflow manually via the "When clicking ‘Test workflow’" node to run the complete scraping, analysis, and reporting pipeline.

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Need help customizing?
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