This workflow automatically extracts Amazon product reviews and identifies hidden friction signals that are costing you conversions.
It helps ecommerce and product teams turn customer complaints into measurable revenue opportunities.
This workflow uses Bright Data's Web Scraper API to collect Amazon reviews, then scans them for friction signals like delivery issues, return complaints, sizing problems, and product defects.
AI classifies each friction signal by revenue impact, scores severity, and prioritizes the most costly conversion leaks.
Results are split into:
Both are logged into Google Sheets for immediate action.
Download the .json file and import it into your n8n instance.
Add your Bright Data API credentials to all Bright Data nodes.
Add your OpenRouter API key for AI friction analysis.
Create a spreadsheet following the "Google Sheets Setup" sticky note inside the workflow.
Connect each Google Sheets node to your document.
Edit the configuration node to define:
Find out exactly why customers are dropping off and fix the highest-impact issues first.
Identify recurring product defects or sizing issues from real customer feedback at scale.
Spot delivery and returns patterns before they become widespread complaints.
Prioritize checkout and UX improvements based on actual revenue impact data.
Analyze competitor product reviews to uncover weaknesses you can capitalize on.
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