n8n ScrapegraphAI Gemini 3 Review Monitoring

Automated Feedaty Review Scraper using ScrapegraphAI & Gemini 3

Automatically collect, analyze and report customer reviews from Feedaty to improve your online reputation

Download Template JSON · n8n compatible · Free
Automated Feedaty Review Scraper workflow interface

What This Workflow Does

This n8n workflow automates the entire process of collecting, analyzing, and reporting customer reviews from Feedaty - a popular customer review platform similar to Trustpilot. It solves the time-consuming manual process of monitoring your online reputation by automatically scraping reviews, analyzing sentiment using Gemini 3 AI, and generating actionable reports.

The workflow combines ScrapegraphAI for reliable web scraping of Feedaty review pages with Gemini 3's advanced natural language processing to categorize feedback, detect sentiment trends, and highlight critical issues. This gives businesses real-time visibility into customer satisfaction without manual data collection.

How It Works

1. Automated Review Collection

The workflow uses ScrapegraphAI to scrape your Feedaty profile at scheduled intervals, extracting all new reviews with metadata like rating, date, and reviewer information. This happens without requiring API access from Feedaty.

2. AI-Powered Analysis

Each review is processed by Gemini 3 to perform sentiment analysis, categorize feedback into topics (product, service, delivery etc.), and flag urgent issues. The AI identifies emotional tone and extracts key phrases.

3. Reporting & Alerts

The system compiles analyzed reviews into periodic reports showing trends, sentiment scores, and improvement areas. Critical negative reviews trigger immediate alerts to your team via email or Slack.

Pro tip: Configure the workflow to run daily or weekly depending on your review volume. For high-traffic businesses, consider real-time processing.

Who This Is For

This automation is ideal for e-commerce stores, SaaS companies, and service businesses that receive customer feedback on Feedaty and need to:

  • Monitor online reputation without manual checking
  • Identify customer satisfaction trends over time
  • Quickly respond to negative feedback
  • Extract insights from unstructured review text
  • Benchmark performance against competitors

What You'll Need

  1. An active n8n instance (cloud or self-hosted)
  2. Access to ScrapegraphAI (API key)
  3. Google Gemini 3 API access
  4. Your Feedaty business profile URL
  5. Destination for reports (Google Sheets, Slack, or email)

Quick Setup Guide

  1. Download and import the JSON template into your n8n instance
  2. Configure the ScrapegraphAI node with your API key
  3. Set up Gemini 3 API credentials in the AI analysis node
  4. Enter your Feedaty profile URL in the web scraper
  5. Configure output destinations (Slack, email, or spreadsheet)
  6. Set your preferred scheduling frequency
  7. Test and activate the workflow

Key Benefits

Save 10+ hours monthly by automating review collection and analysis that would normally require manual work.

Respond 3x faster to negative feedback with real-time alerts when critical reviews are detected.

Uncover hidden insights with AI-powered categorization of thousands of reviews into actionable themes.

Improve customer satisfaction by systematically addressing the most common complaints identified in your reports.

Benchmark performance with automated sentiment scoring and trend analysis over time.

Frequently Asked Questions

Common questions about Feedaty review monitoring and automation

Automating Feedaty review collection saves significant time while ensuring you never miss important customer feedback. Manual checking is inefficient and risks overlooking critical reviews that need immediate response.

Businesses using automation typically respond to negative reviews 60% faster, improving customer retention. The AI analysis also surfaces patterns that would be impossible to spot manually across hundreds of reviews.

  • Eliminates daily manual checking of review platforms
  • Ensures 100% review coverage with no missed feedback
  • Provides structured data from unstructured reviews

AI transforms unstructured review text into actionable insights by detecting sentiment, categorizing feedback topics, and identifying urgent issues. Gemini 3 understands natural language context better than basic sentiment analysis tools.

For example, a restaurant chain used AI review analysis to discover that 38% of negative feedback related to delivery times - a problem they previously underestimated. This enabled targeted operational improvements.

  • Detects emotional tone (positive, neutral, negative)
  • Groups similar feedback into thematic categories
  • Flags reviews mentioning urgent issues like safety

Scraping public review data from your own Feedaty profile is generally permitted, as this is information you already have access to. The legal considerations mainly involve respecting rate limits and not overloading their servers.

ScrapegraphAI handles this responsibly with proper delays between requests. For competitor analysis, check Feedaty's terms of service and consider using their official API if available.

  • Scraping your own profile data is low-risk
  • Always respect robots.txt and rate limits
  • Consider official API for high-volume needs

Feedaty and Trustpilot are both customer review platforms, but Feedaty is more popular in European markets while Trustpilot has broader global adoption. Feedaty often provides more detailed verification of reviews.

From an automation perspective, the main differences are in website structure and available APIs. This workflow specifically handles Feedaty's page layout, but similar principles apply to monitoring any review platform.

  • Feedaty has stronger presence in Europe
  • Different verification processes for reviews
  • Varying website structures require custom scraping

Daily analysis is ideal for businesses receiving 10+ reviews daily, while weekly may suffice for lower volumes. The key is consistent monitoring to spot emerging issues before they escalate.

A retail client saw customer satisfaction improve 22% after shifting from monthly to daily review analysis, enabling faster response to complaints and identifying product issues sooner.

  • Daily for high-volume businesses
  • Weekly for moderate review volume
  • Real-time alerts for critical negative reviews

The core AI analysis components can work with any review source, but the scraping setup is specifically configured for Feedaty's website structure. Adapting it to other platforms requires modifying the scraping logic.

Many businesses use similar workflows for Trustpilot, Google Reviews, and industry-specific platforms. The analysis and reporting components typically require minimal changes for different data sources.

  • AI analysis works with any text reviews
  • Scraping requires platform-specific configuration
  • Common to monitor multiple review sources

Absolutely! GrowwStacks specializes in building custom review monitoring systems tailored to your specific platforms, reporting needs, and business processes. We can integrate multiple review sources, add custom analysis rules, and connect to your internal systems.

Our clients typically see 5-10x ROI from custom automation through improved response times, better review scores, and actionable customer insights. We'll design a solution that fits your exact requirements and existing tech stack.

  • Multi-platform monitoring solutions
  • Custom alert thresholds and reporting
  • Integration with your CRM or helpdesk

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