YouTube comment scraper & analyzer with GPT-4o + email summary report

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

How it Works This workflow automates the collection and analysis of YouTube comments from a video and sends a summary report via email , using Google Sheets , the YouTube API , OpenAI (GPT 4o) , an...

Best for

Market Research automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.limit, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.if, n8n-nodes-base.set, n8n-nodes-base.youtube, n8n-nodes-base.httprequest

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Amit Mehta.

Original n8n.io source

1.1 Workflow description

Title: YouTube comment scraper & analyzer with GPT-4o + email summary report
Workflow name: YouTube comment scraper & analyzer with GPT-4o + email summary report

How it Works

This workflow automates the collection and analysis of YouTube comments from a video and sends a summary report via email, using Google Sheets, the YouTube API, OpenAI (GPT-4o), and Gmail.

Whether you're a content creator, brand manager, or social media analyst, this workflow helps you automate sentiment analysis and receive insights directly in your inbox — all triggered from a simple spreadsheet.

🎯 Use Case

Ideal for:

YouTubers monitoring audience sentiment
Marketing teams analyzing campaign feedback
Community managers summarizing engagement

Setup Instructions

1. Upload the Spreadsheet

File name: Youtube_Video
Sheet structure: | ID | Video Title | YouTube Video ID | Status |
Add video IDs and set their Status as Pending

2. Configure Google Sheets Nodes

Connect your Google account to:

Pick Video IDs from Google Sheet
Update Status on Google Sheet

3. Add API Credentials

YouTube API Key → for comment + video scraping nodes
OpenAI API Key → for analyzing comments
Gmail Account → for sending the summary email

4. Activate the Workflow

Once live, the workflow will:

Watch for new or updated rows in the spreadsheet
Scrape comments using the YouTube API
Analyze sentiment and key themes via GPT-4o
Send a formatted HTML email with the summary
Update the spreadsheet status to Mail sent

🔁 Workflow Logic

Trigger: New/updated row in Google Sheet
Retrieve: YouTube video metadata + comments
Analyze: Comments using GPT-4o
Email: Summary report via Gmail
Update: Spreadsheet status to Mail sent

🧩 Node Descriptions

Node Name	Description
Pick Video IDs from Google Sheet	Watches the spreadsheet and retrieves pending video IDs
If	Checks whether status is 'Pending'
Limit	Restricts the number of processed rows
Set Video Details	Prepares video info (e.g., title, channel)
Get YouTube Video Details	Fetches metadata (title, channel, etc.)
Get YouTube Video Comments	Pulls top-level comments using YouTube API
Prepare Comments Data	Formats comment text for OpenAI
AI Agent	Summarizes comments using OpenAI's GPT-4o
Prepare HTML for Email	Converts summary into HTML for email body
Gmail Account Configuration	Sends the email report via Gmail
Update Status on Google Sheet	Marks the row as 'Mail sent'

🛠️ Customization Tips

Change the AI prompt for tone, length, or custom metrics
Send results to Slack or Telegram instead of Gmail
Export summaries to Notion, Airtable, or PDF
Schedule it daily/weekly for recurring analysis

📒 Suggested Sticky Notes for Workflow

Node/Section	Sticky Note Content
Pick Video IDs from Google Sheet	"Triggers on new YouTube videos in your spreadsheet"
AI Agent	"Uses OpenAI to generate an analysis summary – customize prompt as needed"
Gmail	"Sends summary report – you can update subject, recipients, or style"
Update Status	"Marks video as processed to avoid duplicate runs"

📎 Required Files

File Name	Purpose
Youtube_Video	Google Sheet to hold YouTube video IDs and status
Youtube_Comment_Scraper.json	Main n8n workflow export for this automation

🧪 Testing Tips

Add one test video with a valid YouTube video ID and status = Pending
Monitor the workflow logs to confirm API responses
Confirm summary delivery in your inbox
Verify that status updates in the sheet

🏷 Suggested Tags & Categories

#YouTube
#OpenAI
#Automation
#Marketing
#Email
#Analytics

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Workflow Overview

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 2 - Trigger Documentation

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 3 - YouTube API Section

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 4 - AI Analysis Documentation

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 5 - Email & Status Update

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 6 - Data Processing Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 7 - Limit

Type / Role: n8n-nodes-base.limit - limit
Config choices: Version 1

Block 8 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.9

Block 9 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 10 - If

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 11 - Set Video Details

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 12 - Get Youtube Video Details

Type / Role: n8n-nodes-base.youTube - youTube
Config choices: Version 1

Block 13 - Get Youtube Video Comments

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 14 - Prepare Comments Data

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 15 - Prepare HTML for Email

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 16 - Gmail Account Configuration

Type / Role: n8n-nodes-base.gmail - gmail
Config choices: Version 2.1

Block 17 - Update Status on Google Sheet

Type / Role: n8n-nodes-base.googleSheets - googleSheets
Config choices: Version 4.5

Block 18 - Pick Video Ids from Google sheet

Type / Role: n8n-nodes-base.googleSheetsTrigger - googleSheetsTrigger
Config choices: Version 1

3. Summary Table

Workflow	YouTube comment scraper & analyzer with GPT-4o + email summary report
Complexity	advanced
Nodes	18
Categories	Market Research, AI Summarization
Author	Amit Mehta
Published	11 Jun 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/4863/4863.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Market Research workflows AI Summarization workflows

Frequently asked questions

What does YouTube comment scraper & analyzer with GPT-4o + email summary report do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI Summarization use case.

Amit Mehta

12 workflows

Nodes

n8n-nodes-base.stickynote n8n-nodes-base.limit @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai n8n-nodes-base.if n8n-nodes-base.set n8n-nodes-base.youtube n8n-nodes-base.httprequest

Complexity

advanced

Published 11 Jun 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/4863/4863.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Answer BigQuery questions in Microsoft Teams with Claude 3.5 dual agents

## Quick overview Turn Microsoft Teams into a natural language BI tool. This dual-agent Claude workflow intelligently classifies user questions, generates safe BigQuery SQL, executes the query, and returns a plain-English summary alongside a data preview directly to your Teams channel. ## How it works 1. The workflow listens for new messages in a designated Microsoft Teams channel or chat. 2. It checks a 24-hour static data cache for your BigQuery schema. If the cache is missing or expired, it automatically fetches the latest INFORMATION_SCHEMA metadata. 3. A main Claude 3.5 Sonnet agent classifies the user's intent (analytical, conversational, or unsafe) and identifies the relevant database tables. 4. If the intent is analytical, a specialized Claude SQL sub-agent generates a read-only SELECT query tailored exactly to your schema. 5. The workflow executes the query against BigQuery (safely constrained to a maximum of 100 rows). 6. A final Claude agent translates the raw query results into a concise, plain-English summary. 7. The answer is posted back to Teams as an Adaptive Card, complete with a formatted data preview and the generated SQL code. 8. Non-analytical questions or pipeline errors are intelligently routed to receive standard conversational replies in Teams. ## Setup 1. CRITICAL SECURITY: Restrict your Google Cloud Service Account IAM roles to BigQuery Data Viewer and BigQuery Job User ONLY. Do not use a highly privileged account. 2. Configure your Microsoft Teams trigger and posting credentials, specifying the target team and channel for the bot to operate in. 3. Configure your Google BigQuery credentials to allow reading metadata and executing queries. 4. Configure your Anthropic credentials for the three Claude LangChain nodes. 5. Update the "Configure Variables" node with your specific GCP Project ID and BigQuery Dataset ID. ## Requirements - A Google Cloud project with BigQuery enabled and existing structured datasets. - An Anthropic API key with access to the Claude 3.5 Sonnet model. - Microsoft Teams administrator access to authorize the n8n integration. ## Customization - Distributed Environments: If you are running n8n with multiple worker nodes (Queue Mode), you must swap the $getWorkflowStaticData() schema cache logic to read/write from a dedicated Key-Value store (like Redis or Supabase) to ensure state synchronization. - UI Layout: Modify the Create Teams Adaptive Card node to add corporate branding, custom colors, or alter the FactSet data preview structure. ## Additional info This architecture features built-in pipeline protections, including strict 40,000-character payload limits to prevent LLM context window blowouts, and fallback handling for "zero-row" query results to ensure users are never left without a response.

View

Evaluate LinkedIn profiles with Apify and Groq Llama chat model

## Quick overview This workflow collects a LinkedIn profile URL via an n8n form, scrapes the public profile data using the Apify LinkedIn Profile Scraper actor, analyzes the results with a Groq-hosted Llama model, and displays an HTML-formatted evaluation back to the user. ## How it works 1. Receives a LinkedIn Profile URL when a user submits the n8n form. 2. Prepares the LinkedIn URL along with the Apify API token and Groq API key used for downstream requests. 3. Sends the profile URL to the Apify `harvestapi/linkedin-profile-scraper` actor and retrieves the scraped dataset items. 4. Passes the scraped profile JSON to a Groq chat model via an LLM chain to generate an HTML evaluation with a score and recommendations. 5. Displays the generated HTML evaluation to the user as the form completion message. ## Setup 1. Add a valid Apify API token and ensure the Apify actor endpoint (`harvestapi/linkedin-profile-scraper`) is accessible for your account. 2. Add Groq API credentials in n8n and confirm the selected model (meta-llama/llama-4-scout-17b-16e-instruct) is available to your Groq account. 3. Replace the placeholder API key values in the workflow (or move them to n8n credentials/environment variables) and verify the form field label matches `LinkedIn Profile URL`.

View

Validate startup ideas with Google Gemini, Groq, and Gmail

## Quick overview This workflow collects a startup idea via an n8n form, uses Google Gemini to generate a SWOT-style analysis, assigns a viability score, uses Groq to turn the results into a structured validation report, and emails the final report through Gmail. ## How it works 1. Receives a startup idea, industry, and target audience from an n8n Form trigger. 2. Sends the submission to Google Gemini to generate a professional analysis covering the problem, business model, and SWOT factors. 3. Generates a startup viability score (currently a random value from 80–100) and packages it with the Gemini analysis. 4. Sends the score and analysis to Groq (Llama 3.3 70B) to compile a full validation report with an executive summary, market potential, recommendations, and final verdict. 5. Emails the generated validation report to the configured recipient using Gmail. ## Setup 1. Add credentials for Google Gemini (PaLM) API, Groq API, and a Gmail OAuth2 connection. 2. Replace the placeholder recipient address in the Gmail step ("[email protected]") with your target email address before activating the workflow. 3. Publish the n8n form, then share the form URL with the users who should submit their startup ideas for validation.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

YouTube comment scraper & analyzer with GPT-4o + email summary report

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

How it Works

🎯 Use Case

Setup Instructions

1. Upload the Spreadsheet

2. Configure Google Sheets Nodes

3. Add API Credentials

4. Activate the Workflow

🔁 Workflow Logic

🧩 Node Descriptions

🛠️ Customization Tips

📒 Suggested Sticky Notes for Workflow

📎 Required Files

🧪 Testing Tips

🏷 Suggested Tags & Categories

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Workflow Overview

Block 2 - Trigger Documentation

Block 3 - YouTube API Section

Block 4 - AI Analysis Documentation

Block 5 - Email & Status Update

Block 6 - Data Processing Note

Block 7 - Limit

Block 8 - AI Agent

Block 9 - OpenAI Chat Model

Block 10 - If

Block 11 - Set Video Details

Block 12 - Get Youtube Video Details

Block 13 - Get Youtube Video Comments

Block 14 - Prepare Comments Data

Block 15 - Prepare HTML for Email

Block 16 - Gmail Account Configuration

Block 17 - Update Status on Google Sheet

Block 18 - Pick Video Ids from Google sheet

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions