What Was the Problem?
Manually collecting product reviews and turning them into social media testimonials is time-consuming and inconsistent.
For businesses managing multiple products or plugins, this becomes even harder when:
- Reviews need to be monitored continuously
- Positive and negative reviews need different handling
- Low-rated reviews should be escalated to the team immediately
- Social proof content needs to be created fast
- Testimonial images need to be branded and visually consistent
- Product links should be shared carefully to avoid reducing post reach
They needed a system that could:
- Automatically monitor incoming product reviews
- Detect whether a review is positive or negative using AI
- Filter only high-quality reviews for social posting
- Route reviews by product automatically
- Generate post copy and branded testimonial creatives
- Publish the content to social media with proof links in comments
- Alert the internal team when bad or low-rated reviews appear
What I Built
Using n8n, I built a fully automated review collection and testimonial posting system that tracks new reviews, filters them with AI, generates branded testimonial assets, and publishes them to social media automatically.
Workflow Overview
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Scheduled Review Monitoring
- The workflow runs automatically every hour
- It checks product RSS review feeds to detect whether any new review has been posted within the last hour
- If no new review is found, the workflow stops
- If a new review is found, it moves to the next step
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AI Sentiment Check
- An AI agent analyzes the incoming review
- It determines whether the review is positive or negative
- If the review is negative, the system immediately sends an alert email to the internal team
- If the review is positive, the workflow continues
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Star Rating Validation
- A second AI/logic step checks the review rating
- If the review is greater than 4 stars, it qualifies for testimonial creation
- If the review is 4 stars or below, the system sends an email alert to the team instead of posting it publicly
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Product-Based Routing
- Since the workflow handles multiple products/plugins, a switch router detects which product the review belongs to
- The review is then sent to the correct product-specific branch
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AI Social Post Writing
- Inside the selected product branch, an AI agent writes a social media caption
- The post is based on:
- What the customer said in the review
- Product value/highlights
- A natural promotional tone suitable for testimonial content
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Reviewer Profile Scraping
- The workflow scrapes the reviewer profile to collect profile data
- This includes checking whether a usable profile image is available
- The goal is to make the testimonial more authentic by using the reviewer’s image when possible
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Human Image Detection
- Another AI/image analysis step checks whether the profile image contains a real human face
- If the image is a valid human profile image, it is approved for the testimonial design
- If not, the workflow skips using the profile image in the creative
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Dynamic Testimonial Template Generation
- A testimonial template built with HTML + CSS is used
- The template dynamically inserts:
- Reviewer name
- Reviewer profile image (if valid)
- Review text
- Star rating
- Product logo
- Product branding elements
- This ensures visually consistent testimonial posts across all products
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HTML to Image Conversion
- The generated testimonial template is converted into a JPG image
- This final image is prepared for use as the social media post creative
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Automated Social Media Publishing
- The final testimonial image and AI-generated caption are published automatically to Facebook
- The post also includes product value messaging and relevant hashtags for better engagement
- Comment-Based Proof & Product Links
- After publishing the post, the workflow automatically adds a comment containing:
- The original review link
- The product link
- This is done intentionally because direct links inside the post can reduce reach
- Keeping links in the comment helps preserve engagement while still providing proof and conversion paths
Key Technical Details
- Built using n8n modular workflow architecture
- Used RSS feed monitoring to detect new reviews automatically
- Implemented AI-based sentiment analysis for review qualification
- Added rating-based filtering logic to separate top reviews from low-rated ones
- Used switch routing for handling multiple products in a single workflow
- Automated AI caption generation for social media posting
- Integrated profile scraping and human image detection to improve testimonial authenticity
- Built reusable HTML/CSS testimonial templates with dynamic content injection
- Converted testimonial layouts into JPG creatives for platform-friendly publishing
- Added Facebook posting + automated comment publishing as the final delivery step
- Designed alert logic to notify the internal team instantly about negative or lower-rated reviews
Results
🚀 100% automated review-to-social workflow — no manual testimonial creation needed
🧠 AI-powered review filtering — only positive, high-quality reviews get published
🎨 Dynamic testimonial generation — branded creatives created automatically
⏱️ Hourly review monitoring — new feedback is processed in near real time
📣 Automated Facebook posting — caption, creative, and follow-up comments handled end-to-end
🔔 Instant team alerts — bad or low-rated reviews are escalated immediately
Tools Used
- n8n — Workflow automation & orchestration
- Gemini API — Sentiment analysis, content generation, decision logic
- RSS Feed — Product review monitoring
- Apify API — Reviewer profile scraping / data collection
- HTML & CSS — Testimonial template design
- Image Processing / HTML-to-Image — JPG testimonial generation
- Facebook API — Social media publishing and comment posting