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This workflow automatically analyzes user-submitted product reviews and classifies them by sentiment using OpenAI’s powerful language models. It eliminates the need to manually sift through feedback by tagging each review with a sentiment score.

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n8n-Sentiment-Analysis-of-Product-Reviews-using-Google-Sheets-OpenAI

This n8n workflow automatically analyzes customer-submitted product reviews and classifies them by sentiment (Positive, Neutral, Negative) using OpenAI’s language models.
The sentiment result is written back to Google Sheets, giving you a real-time snapshot of customer perception and satisfaction.


🚀 Quick Implementation Steps

  1. Trigger: Google Sheets triggers on new product review rows.
  2. Sentiment Analysis: Review text is sent to OpenAI.
  3. Writeback: Sentiment result (Positive / Neutral / Negative) is updated in the sheet.

Just connect your credentials and sheet — you're ready to go!


🔍 What It Does

  • Automates customer feedback analysis.
  • Tags each review with sentiment classification.
  • Scales effortlessly for 10 or 10,000 reviews.
  • Updates every minute with fresh results.

Outcome: Fast, clear view of overall customer perception, pain points, and positive highlights.


👤 Who’s It For

  • E-commerce teams collecting user reviews.
  • Product teams monitoring customer feedback.
  • Marketing teams identifying promotable reviews.
  • Support teams detecting negative experiences.
  • SaaS platforms & survey tools managing text feedback.

✅ Requirements

  • A Google Sheet with two columns: Review and Sentiment.
  • Google Sheets OAuth2 credentials in n8n.
  • OpenAI API Key (GPT-4o-mini or GPT-3.5).
  • n8n instance with LangChain + OpenAI nodes enabled.

⚙️ How It Works

  1. Google Sheets Trigger → Watches for new rows every minute.
  2. OpenAI Integration
    • Uses LangChain Sentiment Analysis.
    • Sends review text to GPT-4o-mini via Chat Model node.
  3. Sheet Update → Writes sentiment (Positive/Neutral/Negative) back to the same row.
  4. Sticky Notes → Added for visual clarity inside n8n editor.

🛠️ Steps to Configure & Use

  1. Prepare Your Google Sheet (named Sheet1):

    Review Sentiment
    Absolutely love it!
    Not worth the price.
  2. Set Up Credentials

    • Google Sheets: OAuth2 credentials.
    • OpenAI: API Key added via OpenAI credential in n8n.
  3. Import & Activate Workflow

    • Import JSON workflow into n8n.
    • Assign credentials to trigger and OpenAI nodes.
    • Activate workflow.

🧩 How to Customize

  • 🛎️ Alerts: Add Slack/Email nodes for negative review alerts.
  • 🔄 Triggers: Change from polling to real-time webhooks.
  • 📊 Extended Categories: Add labels like "Mixed" or "Sarcastic".
  • 🧾 Summaries: Use Cron + Aggregation for daily/weekly reports.
  • 🧠 Prompt Tuning: Customize prompts for context-based analysis.

➕ Add-ons

  • Email digest of negative reviews.
  • Google Drive logging of all processed reviews.
  • Team Slack notifications.
  • Export summaries to Notion, Airtable, or Google Docs.

📌 Use Case Examples

  • Online Stores: Monitor customer reputation automatically.
  • Product Teams: Track sentiment per feature/release.
  • CX Dashboards: Feed real-time data into BI tools.
  • Marketing: Extract positive reviews for campaigns.
  • Support: Flag critical issues instantly.

🧰 Troubleshooting Guide

Issue Possible Cause Suggested Fix
Sentiment not updating Google Sheets creds missing Reconnect OAuth2 credentials
Blank sentiment Empty or misaligned columns Ensure correct column names & values
OpenAI errors Invalid/expired API key Regenerate API Key from OpenAI
Workflow not running Polling misconfigured Verify sheet ID, tab, and trigger interval

🤝 Need Help?

We can help you:

  • ✅ Set up and configure this workflow.
  • ⚙️ Customize prompts and categories.
  • 🚀 Automate your entire review pipeline.

👉 Contact WeblineIndia for expert assistance.


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This workflow automatically analyzes user-submitted product reviews and classifies them by sentiment using OpenAI’s powerful language models. It eliminates the need to manually sift through feedback by tagging each review with a sentiment score.

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