by Vigh Sandor
Workflow Overview This advanced n8n workflow provides intelligent email automation with AI-generated responses. It combines four core functions: Monitors incoming emails via IMAP (e.g., SOGo) Sends instant Telegram notifications for all new emails Uses AI (Ollama LLM) to generate contextual, personalized auto-replies Sends confirmation notifications when auto-replies are sent Unlike traditional auto-responders, this workflow analyzes email content and creates unique, relevant responses for each message. Setup Instructions Prerequisites Before setting up this workflow, ensure you have: An n8n instance (self-hosted or cloud) with AI/LangChain nodes enabled IMAP email account credentials (e.g., SOGo, Gmail, Outlook) SMTP server access for sending emails Telegram Bot API credentials Telegram Chat ID where notifications will be sent Ollama installed locally or accessible via network (for AI model) The llama3.1 model downloaded in Ollama Step 1: Install and Configure Ollama Local Installation Install Ollama on your system: Visit https://ollama.ai and download the installer for your OS Follow installation instructions for your platform Download the llama3.1 model: ollama pull llama3.1 Verify the model is available: ollama list Start Ollama service (if not already running): ollama serve Test the model: ollama run llama3.1 "Hello, world!" Remote Ollama Instance If using a remote Ollama server: Note the server URL (e.g., http://192.168.1.100:11434) Ensure network connectivity between n8n and Ollama server Verify firewall allows connections on port 11434 Step 2: Configure IMAP Credentials Navigate to n8n Credentials section Create a new IMAP credential with the following information: Host: Your IMAP server address Port: Usually 993 for SSL/TLS Username: Your email address Password: Your email password or app-specific password Enable SSL/TLS: Yes (recommended) Security: Use STARTTLS or SSL/TLS Step 3: Configure SMTP Credentials Create a new SMTP credential in n8n Enter the following details: Host: Your SMTP server address (e.g., Postfix server) Port: Usually 587 (STARTTLS) or 465 (SSL) Username: Your email address Password: Your email password or app-specific password Secure connection: Enable based on your server configuration Allow unauthorized certificates: Enable if using self-signed certificates Step 4: Configure Telegram Bot Create a Telegram bot via BotFather: Open Telegram and search for @BotFather Send /newbot command Follow instructions to create your bot Save the API token provided by BotFather Obtain your Chat ID: Method 1: Send a message to your bot, then visit: https://api.telegram.org/bot<YOUR_BOT_TOKEN>/getUpdates Method 2: Use a Telegram Chat ID bot like @userinfobot Method 3: For group chats, add the bot to the group and check the updates Note: Group chat IDs are negative numbers (e.g., -1234567890123) Add Telegram API credential in n8n: Credential Type: Telegram API Access Token: Your bot token from BotFather Step 5: Configure Ollama API Credential In n8n Credentials section, create a new Ollama API credential Configure based on your setup: For local Ollama: Base URL is usually http://localhost:11434 For remote Ollama: Enter the server URL (e.g., http://192.168.1.100:11434) Test the connection to ensure n8n can reach Ollama Step 6: Import and Configure Workflow Import the workflow JSON into your n8n instance Update the following nodes with your specific information: Check Incoming Emails Node Verify IMAP credentials are connected Configure polling interval (optional): Default behavior checks on workflow trigger schedule Can be set to check every N minutes Set mailbox folder if needed (default is INBOX) Send Notification from Incoming Email Node Update chatId parameter with your Telegram Chat ID Replace -1234567890123 with your actual chat ID Customize notification message template if desired Current format includes: Sender, Subject, Date-Time Dedicate Filtering As No-Response Node Review spam filter conditions: Blocks emails from addresses containing "noreply" or "no-reply" Blocks emails with "newsletter" in subject line (case-insensitive) Add additional filtering rules as needed: Block specific domains Filter by keywords Whitelist/blacklist specific senders Ollama Model Node Verify Ollama API credential is connected Confirm model name: llama3.1:bf230501 (or adjust to your installed version) Context window set to 4096 tokens (sufficient for most emails) Can be adjusted based on your needs and hardware capabilities Basic LLM Chain Node Review the AI prompt engineering (pre-configured but customizable) Current prompt instructs the AI to: Read the email content Identify main topic in 2-4 words Generate a professional acknowledgment response Keep responses consistent and concise Modify prompt if you want different response styles Send Auto-Response in SMTP Node Verify SMTP credentials are connected Check fromEmail uses correct email address: Currently set to {{ $('Check Incoming Emails - IMAP (example: SOGo)').item.json.to }} This automatically uses the recipient address (your mailbox) Subject automatically includes "Re: " prefix with original subject Message text comes from AI-generated content Send Notification from Response Node Update chatId parameter (same as first notification node) This sends confirmation that auto-reply was sent Includes original email details and the AI-generated response text Step 7: Test the Workflow Perform initial configuration test: Test Ollama connectivity: curl http://localhost:11434/api/tags Verify all credentials are properly configured Check n8n has access to required network endpoints Execute a test run: Click "Execute Workflow" button in n8n Send a test email to your monitored inbox Use a clear subject and body for better AI response Verify workflow execution: First Telegram notification received (incoming email alert) AI processes the email content Auto-reply is sent to the original sender Second Telegram notification received (confirmation with AI response) Check n8n execution log for any errors Verify email delivery: Check if auto-reply arrived at sender's inbox Verify it's not marked as spam Review AI-generated content for appropriateness Step 8: Fine-Tune AI Responses Send various types of test emails: Different topics (inquiry, complaint, information request) Various email lengths (short, medium, long) Different languages if applicable Review AI-generated responses: Check if topic identification is accurate Verify response appropriateness Ensure tone is professional Adjust the prompt if needed: Modify topic word count (currently 2-4 words) Change response template Add language-specific instructions Include custom sign-offs or branding Step 9: Activate the Workflow Once testing is successful and AI responses are satisfactory: Toggle the workflow to "Active" state The workflow will now run automatically on the configured schedule Monitor initial production runs: Review first few auto-replies carefully Check Telegram notifications for any issues Verify SMTP delivery rates Set up monitoring: Enable n8n workflow error notifications Monitor Ollama resource usage Check email server logs periodically How to Use Normal Operation Once activated, the workflow operates fully automatically: Email Monitoring: The workflow continuously checks your IMAP inbox for new messages based on the configured polling interval or trigger schedule. Immediate Incoming Notification: When a new email arrives, you receive an instant Telegram notification containing: Sender's email address Email subject line Date and time received Note indicating it's from IMAP mailbox Intelligent Filtering: The workflow evaluates each email against spam filter criteria: Emails from "noreply" or "no-reply" addresses are filtered out Emails with "newsletter" in the subject line are filtered out Filtered emails receive notification but no auto-reply Legitimate emails proceed to AI response generation AI Response Generation: For emails that pass the filter: The AI reads the full email content Analyzes the main topic or purpose Generates a personalized acknowledgment Creates a professional response that: Thanks the sender References the specific topic Promises a personal follow-up Maintains professional tone Automatic Reply Delivery: The AI-generated response is sent via SMTP to the original sender with: Subject line: "Re: [Original Subject]" From address: Your monitored mailbox Body: AI-generated contextual message Response Confirmation: After the auto-reply is sent, you receive a second Telegram notification showing: Original email details (sender, subject, date) The complete AI-generated response text Confirmation of successful delivery Understanding AI Response Generation The AI analyzes emails intelligently: Example 1: Business Inquiry Incoming Email: "I'm interested in your consulting services for our Q4 project..." AI Topic Identification: "consulting services" Generated Response: "Dear Correspondent! Thank you for your message regarding consulting services. I will respond with a personal message as soon as possible. Have a nice day!" Example 2: Technical Support Incoming Email: "We're experiencing issues with the API integration..." AI Topic Identification: "API integration issues" Generated Response: "Dear Correspondent! Thank you for your message regarding API integration issues. I will respond with a personal message as soon as possible. Have a nice day!" Example 3: General Question Incoming Email: "Could you provide more information about pricing?" AI Topic Identification: "pricing information" Generated Response: "Dear Correspondent! Thank you for your message regarding pricing information. I will respond with a personal message as soon as possible. Have a nice day!" Customizing Filter Rules To modify which emails receive AI-generated auto-replies: Open the "Dedicate Filtering As No-Response" node Modify existing conditions or add new ones: Block specific domains: {{ $json.from.value[0].address }} Operation: does not contain Value: @spam-domain.com Whitelist VIP senders (only respond to specific people): {{ $json.from.value[0].address }} Operation: contains Value: @important-client.com Filter by subject keywords: {{ $json.subject.toLowerCase() }} Operation: does not contain Value: unsubscribe Combine multiple conditions: Use AND logic (all must be true) for stricter filtering Use OR logic (any can be true) for more permissive filtering Customizing AI Prompt To change how the AI generates responses: Open the "Basic LLM Chain" node Modify the prompt text in the "text" parameter Current structure: Context setting (read email, identify topic) Output format specification Rules for AI behavior Example modifications: Add company branding: Return only this response, filling in the [TOPIC]: Dear Correspondent! Thank you for reaching out to [Your Company Name] regarding [TOPIC]. I will respond with a personal message as soon as possible. Best regards, [Your Name] [Your Company Name] Make it more casual: Return only this response, filling in the [TOPIC]: Hi there! Thanks for your email about [TOPIC]. I'll get back to you personally soon. Cheers! Add urgency classification: Read the email and classify urgency (Low/Medium/High). Identify the main topic. Return: Dear Correspondent! Thank you for your message regarding [TOPIC]. Priority: [URGENCY] I will respond with a personal message as soon as possible. Customizing Telegram Notifications Incoming Email Notification: Open "Send Notification from Incoming Email" node Modify the "text" parameter Available variables: {{ $json.from }} - Full sender info {{ $json.from.value[0].address }} - Sender email only {{ $json.from.value[0].name }} - Sender name (if available) {{ $json.subject }} - Email subject {{ $json.date }} - Date received {{ $json.textPlain }} - Email body (use cautiously for privacy) {{ $json.to }} - Recipient address Response Confirmation Notification: Open "Send Notification from Response" node Modify to include additional information Reference AI response: {{ $('Basic LLM Chain').item.json.text }} Monitoring and Maintenance Daily Monitoring Check Telegram Notifications**: Review incoming email alerts and response confirmations Verify AI Quality**: Spot-check AI-generated responses for appropriateness Email Delivery**: Confirm auto-replies are being delivered (not caught in spam) Weekly Maintenance Review Execution Logs**: Check n8n execution history for errors or warnings Ollama Performance**: Monitor resource usage (CPU, RAM, disk space) Filter Effectiveness**: Assess if spam filters are working correctly Response Quality**: Review multiple AI responses for consistency Monthly Maintenance Update Ollama Model**: Check for new llama3.1 versions or alternative models Prompt Optimization**: Refine AI prompt based on response quality observations Credential Rotation**: Update passwords and API tokens for security Backup Configuration**: Export workflow and credentials (securely) Advanced Usage Multi-Language Support If you receive emails in multiple languages: Modify the AI prompt to detect language: Detect the email language. Generate response in the SAME language as the email. If English: [English template] If Hungarian: [Hungarian template] If German: [German template] Or use language-specific conditions in the filtering node Priority-Based Responses Generate different responses based on sender importance: Add an IF node after filtering to check sender domain Route VIP emails to a different LLM chain with priority messaging Standard emails use the normal AI chain Response Logging To maintain a record of all AI interactions: Add a database node (PostgreSQL, MySQL, etc.) after the auto-reply node Store: timestamp, sender, subject, AI response, delivery status Use for compliance, analytics, or training data A/B Testing AI Prompts Test different prompt variations: Create multiple LLM Chain nodes with different prompts Use a randomizer or round-robin approach Compare response quality and user feedback Optimize based on results Troubleshooting Notifications Not Received Problem: Telegram notifications not appearing Solutions: Verify Chat ID is correct (positive for personal chats, negative for groups) Check if bot has permissions to send messages Ensure bot wasn't blocked or removed from group Test Telegram API credential independently Review n8n execution logs for Telegram API errors AI Responses Not Generated Problem: Auto-replies sent but content is empty or error messages Solutions: Check Ollama service is running: ollama list Verify llama3.1 model is downloaded: ollama list Test Ollama directly: ollama run llama3.1 "Test message" Review Ollama API credential URL in n8n Check network connectivity between n8n and Ollama Increase context window if emails are very long Monitor Ollama logs for errors Poor Quality AI Responses Problem: AI generates irrelevant or inappropriate responses Solutions: Review and refine the prompt engineering Add more specific rules and constraints Provide examples in the prompt of good vs bad responses Adjust topic word count (increase from 2-4 to 3-6 words) Test with different Ollama models (e.g., llama3.1:70b for better quality) Ensure email content is being passed correctly to AI Auto-Replies Not Sent Problem: Workflow executes but emails not delivered Solutions: Verify SMTP credentials and server connectivity Check fromEmail address is correct Review SMTP server logs for errors Test SMTP sending independently Ensure "Allow unauthorized certificates" is enabled if needed Check if emails are being filtered by spam filters Verify SPF/DKIM records for your domain High Resource Usage Problem: Ollama consuming excessive CPU/RAM Solutions: Reduce context window size (from 4096 to 2048) Use a smaller model variant (llama3.1:8b instead of default) Limit concurrent workflow executions in n8n Add delay/throttling between email processing Consider using a remote Ollama instance with better hardware Monitor email volume and processing time IMAP Connection Failures Problem: Workflow can't connect to email server Solutions: Verify IMAP credentials are correct Check if IMAP is enabled on email account Ensure SSL/TLS settings match server requirements For Gmail: enable "Less secure app access" or use App Passwords Check firewall allows outbound connections on IMAP port (993) Test IMAP connection using email client (Thunderbird, Outlook) Workflow Not Triggering Problem: Workflow doesn't execute automatically Solutions: Verify workflow is in "Active" state Check trigger node configuration and schedule Review n8n system logs for scheduler issues Ensure n8n instance has sufficient resources Test manual execution to isolate trigger issues Check if n8n workflow execution queue is backed up Workflow Architecture Node Descriptions Check Incoming Emails - IMAP: Polls email server at regular intervals to retrieve new messages from the configured mailbox. Send Notification from Incoming Email: Immediately sends formatted notification to Telegram for every new email detected, regardless of spam status. Dedicate Filtering As No-Response: Evaluates emails against spam filter criteria to determine if AI processing should occur. No Operation: Placeholder node for filtered emails that should not receive an auto-reply (spam, newsletters, automated messages). Ollama Model: Provides the AI language model (llama3.1) used for natural language processing and response generation. Basic LLM Chain: Executes the AI prompt against the email content to generate contextual auto-reply text. Send Auto-Response in SMTP: Sends the AI-generated acknowledgment email back to the original sender via SMTP server. Send Notification from Response: Sends confirmation to Telegram showing the auto-reply was successfully sent, including the AI-generated content. AI Processing Pipeline Email Content Extraction: Email body text is extracted from IMAP data Context Loading: Email content is passed to LLM with prompt instructions Topic Analysis: AI identifies main subject or purpose in 2-4 words Template Population: AI fills response template with identified topic Output Formatting: Response is formatted and cleaned for email delivery Quality Assurance: n8n validates response before sending
by Shayan Ali Bakhsh
About this Workflow This workflow helps you repurpose your YouTube videos across multiple social media platforms with zero manual effort. It’s designed for creators, businesses, and marketers who want to maximize reach without spending hours re-uploading content everywhere. How It Works Trigger from YouTube The workflow checks your YouTube channel every 10 minutes via RSS feed. It compares the latest video ID with the last saved one to detect if a new video was uploaded. Tutorial: How to get YouTube Channel RSS Feed Generate Descriptions with AI Uses Gemini 2.5 Flash to automatically generate fresh, engaging descriptions for your posts. Create Images with ContentDrips ContentDrips offers multiple templates (carousel, single image, branding templates, etc.). The workflow generates a custom promotional image using your video description and thumbnail. Install node: npm install n8n-nodes-contentdrips Docs: ContentDrips Blog Tutorial Publish Across Social Platforms with SocialBu Instead of manually connecting each social media API, this workflow uses SocialBu. From a single connection, you can post to: Facebook, Instagram, TikTok, YouTube, Twitter (X), LinkedIn, Threads, Pinterest, and more. Website: SocialBu Get Real-Time Notifications via Discord After each run, the workflow sends updates to your Discord channel. You’ll know if the upload was successful, or if an error occurred (e.g., API limits). Setup guide: Discord OAuth Credentials Why Use This Workflow? Saves time by automating the entire repurposing process. Ensures consistent branding and visuals across platforms. Works around platform restrictions by leveraging SocialBu’s integrations. Keeps you updated with Discord notifications—no guessing if something failed. Requirements YouTube channel RSS feed link ContentDrips API key, template ID, and branding setup SocialBu account with connected social media platforms Discord credentials (for webhook updates) Need Help? Message me on LinkedIn: Shayan Ali Bakhsh Happy Automation 🚀
by PhilanthropEAK Automation
Who's it for Marketing teams, social media managers, content creators, and small businesses looking to maintain consistent social media presence across multiple platforms. Perfect for organizations that want to automate content creation while maintaining quality and brand consistency. How it works This workflow creates a complete social media automation system that generates platform-specific content using AI and schedules posts across Twitter, LinkedIn, and Instagram based on your content calendar in Google Sheets. The system runs daily at 9 AM, reading your content calendar to identify scheduled topics for the day. It uses OpenAI's GPT-4 to generate platform-optimized content that follows each platform's best practices - concise engaging posts for Twitter, professional thought leadership for LinkedIn, and visual storytelling for Instagram. DALL-E creates accompanying images that match your brand style and topic themes. Each piece of content is automatically formatted for optimal engagement, including appropriate hashtags, character limits, and platform-specific calls-to-action. The workflow then schedules posts through Buffer's API at optimal times and updates your spreadsheet with posting status, content previews, and generated image URLs for tracking and approval workflows. How to set up Prerequisites: Google account with Sheets access OpenAI API key with GPT-4 and DALL-E access Buffer account with connected social media profiles Slack workspace (optional for notifications) Setup steps: Create your content calendar: Copy the provided Google Sheets template Set up columns: Date, Topic, Platforms, Content Type, Keywords, Status, Generated Content, Image URL Fill in your content schedule with topics and target platforms Configure credentials in n8n: Add OpenAI API credential with your API key Set up Google Sheets OAuth2 for spreadsheet access Add Buffer API token from your Buffer dashboard Add Slack API credential for success notifications (optional) Update Configuration Variables: Set your Google Sheet ID from the spreadsheet URL Define your brand voice and company messaging Specify target audience for content personalization Set image style preferences for consistent visuals Configure Buffer integration: Connect your social media accounts to Buffer Get profile IDs for Twitter, LinkedIn, and Instagram Update the Schedule Post node with your specific profile IDs Set optimal posting times in Buffer settings Test the workflow: Add test content to tomorrow's date in your calendar Run the workflow manually to verify content generation Check that posts appear in Buffer's queue correctly Verify spreadsheet updates and Slack notifications work Requirements Google Sheets with template structure and editing permissions OpenAI API key with GPT-4 and DALL-E access (estimated cost: $0.10-0.30 per day for content generation) Buffer account (free plan supports up to 3 social accounts, paid plans for more) Social media accounts connected through Buffer (Twitter, LinkedIn, Instagram) n8n instance (cloud subscription or self-hosted) How to customize the workflow Adjust content generation: Modify AI prompts in the OpenAI node to match your industry tone and style Add custom content types (promotional, educational, behind-the-scenes, user-generated) Include seasonal or event-based content variations in your prompts Customize hashtag strategies per platform and content type Enhance scheduling logic: Add time zone considerations for global audiences Implement different posting schedules for weekdays vs weekends Create urgency-based posting for time-sensitive content Add approval workflows before scheduling sensitive content Expand platform support: Add Facebook, TikTok, or YouTube Shorts using their respective APIs Integrate with Hootsuite or Later as alternative scheduling platforms Include Pinterest for visual content with optimized descriptions Add LinkedIn Company Page posting alongside personal profiles Improve content intelligence: Integrate trending hashtag research using social media APIs Add competitor content analysis for inspiration and differentiation Include sentiment analysis to adjust tone based on current events Implement A/B testing for different content variations Advanced automation features: Add engagement monitoring and response workflows Create monthly performance reports sent via email Implement content recycling for evergreen topics Build user-generated content curation from brand mentions Add crisis communication protocols for sensitive topics Integration enhancements: Connect with your CRM to include customer success stories Link to email marketing for cross-channel content consistency Integrate with project management tools for campaign coordination Add analytics dashboards for content performance tracking
by vinci-king-01
Customer Support Analysis Dashboard with AI and Automated Insights 🎯 Target Audience Customer support managers and team leads Customer success teams monitoring satisfaction Product managers analyzing user feedback Business analysts measuring support metrics Operations managers optimizing support processes Quality assurance teams monitoring support quality Customer experience (CX) professionals 🚀 Problem Statement Manual analysis of customer support tickets and feedback is time-consuming and often misses critical patterns or emerging issues. This template solves the challenge of automatically collecting, analyzing, and visualizing customer support data to identify trends, improve response times, and enhance overall customer satisfaction. 🔧 How it Works This workflow automatically monitors customer support channels using AI-powered analysis, processes tickets and feedback, and provides actionable insights for improving customer support operations. Key Components Scheduled Trigger - Runs the workflow at specified intervals to maintain real-time monitoring AI-Powered Ticket Analysis - Uses advanced NLP to categorize, prioritize, and analyze support tickets Multi-Channel Integration - Monitors email, chat, help desk systems, and social media Automated Insights - Generates reports on trends, response times, and satisfaction scores Dashboard Integration - Stores all data in Google Sheets for comprehensive analysis and reporting 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | timestamp | DateTime | When the ticket was processed | "2024-01-15T10:30:00Z" | | ticket_id | String | Unique ticket identifier | "SUP-2024-001234" | | customer_email | String | Customer contact information | "john@example.com" | | subject | String | Ticket subject line | "Login issues with new app" | | description | String | Full ticket description | "I can't log into the mobile app..." | | category | String | AI-categorized ticket type | "Technical Issue" | | priority | String | Calculated priority level | "High" | | sentiment_score | Number | Customer sentiment (-1 to 1) | -0.3 | | urgency_indicator | String | Urgency classification | "Immediate" | | response_time | Number | Time to first response (hours) | 2.5 | | resolution_time | Number | Time to resolution (hours) | 8.0 | | satisfaction_score | Number | Customer satisfaction rating | 4.2 | | agent_assigned | String | Support agent name | "Sarah Johnson" | | status | String | Current ticket status | "Resolved" | 🛠️ Setup Instructions Estimated setup time: 20-25 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Google Sheets account with API access Help desk system API access (Zendesk, Freshdesk, etc.) Email service integration (optional) Step-by-Step Configuration 1. Install Community Nodes Install required community nodes npm install n8n-nodes-scrapegraphai npm install n8n-nodes-slack 2. Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working 3. Set up Google Sheets Connection Add Google Sheets OAuth2 credentials Grant necessary permissions for spreadsheet access Create a new spreadsheet for customer support analysis Configure the sheet name (default: "Support Analysis") 4. Configure Support System Integration Update the websiteUrl parameters in ScrapeGraphAI nodes Add URLs for your help desk system or support portal Customize the user prompt to extract specific ticket data Set up categories and priority thresholds 5. Set up Notification Channels Configure Slack webhook or API credentials for alerts Set up email service credentials for critical issues Define alert thresholds for different priority levels Test notification delivery 6. Configure Schedule Trigger Set analysis frequency (hourly, daily, etc.) Choose appropriate time zones for your business hours Consider support system rate limits 7. Test and Validate Run the workflow manually to verify all connections Check Google Sheets for proper data formatting Test ticket analysis with sample data 🔄 Workflow Customization Options Modify Analysis Targets Add or remove support channels (email, chat, social media) Change ticket categories and priority criteria Adjust analysis frequency based on ticket volume Extend Analysis Capabilities Add more sophisticated sentiment analysis Implement customer churn prediction models Include agent performance analytics Add automated response suggestions Customize Alert System Set different thresholds for different ticket types Create tiered alert systems (info, warning, critical) Add SLA breach notifications Include trend analysis alerts Output Customization Add data visualization and reporting features Implement support trend charts and graphs Create executive dashboards with key metrics Add customer satisfaction trend analysis 📈 Use Cases Support Ticket Management**: Automatically categorize and prioritize tickets Response Time Optimization**: Identify bottlenecks in support processes Customer Satisfaction Monitoring**: Track and improve satisfaction scores Agent Performance Analysis**: Monitor and improve agent productivity Product Issue Detection**: Identify recurring problems and feature requests SLA Compliance**: Ensure support teams meet service level agreements 🚨 Important Notes Respect support system API rate limits and terms of service Implement appropriate delays between requests to avoid rate limiting Regularly review and update your analysis parameters Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Consider data privacy and GDPR compliance for customer data 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Google Sheets permission errors: Check OAuth2 scope and permissions Ticket parsing errors: Review the Code node's JavaScript logic Rate limiting: Adjust analysis frequency and implement delays Alert delivery failures: Check notification service credentials Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Google Sheets API documentation for advanced configurations Help desk system API documentation Customer support analytics best practices
by Yang
Who’s it for This template is perfect for content marketers, social media managers, and creators who want to repurpose YouTube videos into platform-specific posts without manual work. If you spend hours brainstorming captions, resizing content, or creating images for different platforms, this workflow automates the entire process from video selection to ready-to-publish posts. What it does The workflow takes a topic from a Google Sheet, finds the most relevant and recent YouTube video using Dumpling AI and GPT-4o, then automatically generates unique posts for Instagram, Facebook, and LinkedIn. Each post comes with a tailored AI-generated image, and all content is saved back into a Google Sheet for easy scheduling and review. Here’s what happens step by step: Picks an unsearched topic from Google Sheets Searches YouTube via Dumpling AI and sorts videos Uses GPT-4o to select the most relevant video Extracts the video transcript using Dumpling AI Generates three platform-specific posts using GPT-4o Creates matching images for each post using Dumpling AI image generation Saves the final Instagram, Facebook, and LinkedIn posts into a Google Sheet Marks the topic as processed so it won’t repeat How it works Scheduled Trigger: Starts the workflow automatically on a set schedule Google Sheets: Retrieves one unprocessed topic from the YouTube Topics sheet Dumpling AI: Finds and filters YouTube videos matching the topic GPT-4o: Chooses the best video and turns the transcript into three unique posts Dumpling AI (Image): Generates platform-specific visuals for each post Google Sheets: Saves all posts and images to the Social Media Post sheet for publishing Requirements ✅ Dumpling AI API key stored as credentials ✅ OpenAI GPT-4 credentials ✅ Google Sheets connection with the following sheets: YouTube Topics with columns Youtube Topics and Searched? Social Media Post with columns platform, Content, Image How to customize Adjust the GPT prompt to match your brand voice or content style Add or remove platforms depending on your posting strategy Change the schedule trigger frequency to fit your content calendar Integrate with scheduling tools like Buffer or Hootsuite for auto-publishing Add review or approval steps before posts are finalized > This workflow helps you transform a single YouTube video into three polished, platform-ready posts with matching visuals, in minutes—not hours.
by Max aka Mosheh
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works • Publishes content to 9 social platforms (Instagram, YouTube, TikTok, Facebook, LinkedIn, Threads, Twitter/X, Bluesky, Pinterest) from a single Airtable base • Automatically uploads media to Blotato, handles platform-specific requirements (YouTube titles, Pinterest boards), and tracks success/failure for each post • Includes smart features like GPT-powered YouTube title optimization, Pinterest Board ID finder tool, and random delays to avoid rate limits Set up steps • Takes ~20–35 minutes to configure all 9 platforms (or less if you only need specific ones) • Requires Airtable personal access token, Blotato API key, and connecting your social accounts in Blotato dashboard • Workflow includes comprehensive sticky notes with step-by-step Airtable base setup, credential configuration, platform ID locations, and quick debugging links for each social network Pro tip: The workflow is modular - you can disable any platforms you don't use by deactivating their respective nodes, making it flexible for any social media strategy from single-platform to full omnichannel publishing.
by WeblineIndia
IPA Size Tracker with Trend Alerts – Automated iOS Apps Size Monitoring This workflow runs on a daily schedule and monitors IPA file sizes from configured URLs. It stores historical size data in Google Sheets, compares current vs. previous builds and sends email alerts only when significant size changes occur (default: ±10%). A DRY_RUN toggle allows safe testing before real notifications go out. Who’s it for iOS developers tracking app binary size growth over time. DevOps teams monitoring build artifacts and deployment sizes. Product managers ensuring app size budgets remain acceptable. QA teams detecting unexpected size changes in release builds. Mobile app teams optimizing user experience by keeping apps lightweight. How it works Schedule Trigger (daily at 09:00 UTC) kicks off the workflow. Configuration: Define monitored apps with {name, version, build, ipa_url}. HTTP Request downloads the IPA file from its URL. Size Calculation: Compute file sizes in bytes, KB, MB and attach timestamp metadata. Google Sheets: Append size data to the IPA Size History sheet. Trend Analysis: Compare current vs. previous build sizes. Alert Logic: Evaluate thresholds (>10% increase or >10% decrease). Email Notification: Send formatted alerts with comparisons and trend indicators. Rate Limit: Space out notifications to avoid spamming recipients. How to set up 1. Spreadsheet Create a Google Sheet with a tab named IPA Size History containing: Date, Timestamp, App_Name, Version, Build_Number, Size_Bytes, Size_KB, Size_MB, IPA_URL 2. Credentials Google Sheets (OAuth)** → for reading/writing size history. Gmail** → for sending alert emails (use App Password if 2FA is enabled). 3. Open “Set: Configuration” node Define your workflow variables: APP_CONFIGS = array of monitored apps ({name, version, build, ipa_url}) SPREADSHEET_ID = Google Sheet ID SHEET_NAME = IPA Size History SMTP_FROM = sender email (e.g., devops@company.com) ALERT_RECIPIENTS = comma-separated emails SIZE_INCREASE_THRESHOLD = 0.10 (10%) SIZE_DECREASE_THRESHOLD = 0.10 (10%) LARGE_APP_WARNING = 300 (MB) SCHEDULE_TIME = 09:00 TIMEZONE = UTC DRY_RUN = false (set true to test without sending emails) 4. File Hosting Host IPA files on Google Drive, Dropbox or a web server. Ensure direct download URLs are used (not preview links). 5. Activate the workflow Once configured, it will run automatically at the scheduled time. Requirements Google Sheet with the IPA Size History tab. Accessible IPA file URLs. SMTP / gmail account (Gmail recommended). n8n (cloud or self-hosted) with Google Sheets + Email nodes. Sufficient local storage for IPA file downloads. How to customize the workflow Multiple apps**: Add more configs to APP_CONFIGS. Thresholds**: Adjust SIZE_INCREASE_THRESHOLD / SIZE_DECREASE_THRESHOLD. Notification templates**: Customize subject/body with variables: {{app_name}}, {{current_size}}, {{previous_size}}, {{change_percent}}, {{trend_status}}. Schedule**: Change Cron from daily to hourly, weekly, etc. Large app warnings**: Adjust LARGE_APP_WARNING. Trend analysis**: Extend beyond one build (7-day, 30-day averages). Storage backend**: Swap Google Sheets for CSV, DB or S3. Add-ons to level up Slack Notifications**: Add Slack webhook alerts with emojis & formatting. Size History Charts**: Generate trend graphs with Chart.js or Google Charts API. Environment separation**: Monitor dev/staging/prod builds separately. Regression detection**: Statistical anomaly checks. Build metadata**: Log bundle ID, SDK versions, architectures. Archive management**: Auto-clean old records to save space. Dashboards**: Connect to Grafana, DataDog or custom BI. CI/CD triggers**: Integrate with pipelines via webhook trigger. Common Troubleshooting No size data** → check URLs return binary IPA (not HTML error). Download failures** → confirm hosting permissions & direct links. Missing alerts** → ensure thresholds & prior history exist. Google Sheets errors** → check sheet/tab names & OAuth credentials. Email issues** → validate SMTP credentials, spam folder, sender reputation. Large file timeouts** → raise HTTP timeout for >100MB files. Trend errors** → make sure at least 2 builds exist. No runs** → confirm workflow is active and timezone is correct. Need Help? If you’d like this to customize this workflow to suit your app development process, then simply reach out to us here and we’ll help you customize the template to your exact use case.
by Jitesh Dugar
Transform chaotic training requests into strategic skill development - achieving 100% completion tracking, 30% cost reduction through intelligent planning, and data-driven L&D decisions. What This Workflow Does Revolutionizes corporate training management with AI-driven course recommendations and automated approval workflows: 📝 Training Request Capture - Jotform collects skill gaps, business justification, and training needs 💰 Budget Intelligence - Real-time department budget checking and utilization tracking 🤖 AI Course Recommendations - Matches requests to training catalog with 0-100% scoring 📊 ROI Analysis - AI assesses business impact, urgency, and return on investment ✅ Smart Approval Routing - Auto-approves within budget or routes to manager with AI insights 🎯 Skill Development Paths - Creates personalized learning journeys from current to desired levels 👥 Team Impact Assessment - Identifies knowledge sharing opportunities and additional attendees ⚠️ Risk Analysis - Evaluates delays risks and over-investment concerns 📧 Automated Notifications - Sends detailed approvals to managers and confirmations to employees 📈 Complete Tracking - Logs all requests with AI insights for L&D analytics Key Features AI Training Advisor: GPT-4 analyzes requests across 10+ dimensions including needs assessment, ROI, and implementation planning Course Catalog Matching: AI scores courses 0-100% based on skill level, topic relevance, and outcomes alignment Budget Management: Real-time tracking of department budgets with utilization percentages Preventability Scoring: Identifies skill gaps that could have been addressed earlier Alternative Options: AI suggests cost-effective alternatives (online courses, mentoring, job shadowing) Skill Development Pathways: Maps progression from current to desired skill level with timeframes Team Multiplier Effect: Identifies how training one person benefits entire team Manager Guidance: Provides key considerations, questions to ask, and approval criteria Implementation Planning: Suggests timeline, preparation needed, and post-training actions Success Metrics: Defines measurable outcomes for training effectiveness Risk Assessment: Flags delay risks and over-investment concerns Cost Optimization: Recommends ways to reduce costs while maintaining quality Perfect For Growing Tech Companies: 50-500 employees with high skill development needs Enterprise Organizations: Large corporations managing 1000+ training requests annually Professional Services: Consulting, legal, accounting firms requiring continuous upskilling Healthcare Systems: Medical organizations with compliance and clinical training requirements Manufacturing Companies: Technical skills training for operations and quality teams Sales Organizations: Sales enablement and product training at scale Financial Services: Compliance training and professional certification tracking What You'll Need Required Integrations Jotform - Training request form (free tier works) Create your form for free on Jotform using this link OpenAI API - GPT-4 for AI training analysis (~$0.30-0.60 per request) Gmail - Automated notifications to employees, managers, and HR Google Sheets - Training request database and L&D analytics Quick Start Import Template - Copy JSON and import into n8n Add OpenAI Credentials - Set up OpenAI API key (GPT-4 recommended) Create Jotform Training Request Configure Gmail - Add Gmail OAuth2 credentials Setup Google Sheets: Create spreadsheet with "Training_Requests" sheet Replace YOUR_GOOGLE_SHEET_ID in workflow Columns auto-populate on first submission Customize Training Catalog: Edit "Check Training Budget" node Update training catalog with your actual courses, providers, and costs Add your company's preferred vendors Customization Options Custom Training Catalog: Replace sample catalog with your company's actual training offerings Budget Rules: Adjust approval thresholds (e.g., auto-approve under $500) AI Prompt Tuning: Customize analysis criteria for your industry and culture Multi-Level Approvals: Add VP or director approval for high-cost training Compliance Training: Flag required certifications and regulatory training Vendor Management: Track preferred training vendors and volume discounts Learning Paths: Create role-specific career development tracks Certification Tracking: Monitor professional certifications and renewal dates Training Calendar: Integrate with company calendar for session visibility Waitlist Management: Queue employees when sessions are full Pre/Post Assessments: Add skill testing before and after training Knowledge Sharing: Schedule lunch-and-learns for employees to share learnings Expected Results 100% completion tracking - Digital trail from request to certificate 30% cost reduction - Strategic planning prevents redundant/unnecessary training 95% manager response rate - Automated reminders and clear AI guidance 50% faster approvals - AI pre-analysis speeds manager decisions 40% better course matching - AI recommendations vs manual course selection 60% reduction in budget overruns - Real-time budget visibility 3x increase in skill development velocity - Streamlined process removes friction 85% employee satisfaction - Clear process and fast responses Data-driven L&D strategy - Analytics identify trending skill gaps 25% increase in training ROI - Better targeting and follow-through Use Cases Tech Startup (150 Engineers) Engineer requests "Advanced Kubernetes" training. AI identifies skill gap as "high severity" due to upcoming cloud migration project. Checks department budget ($22K remaining of $50K), recommends $1,800 4-day course with 92% match score. Auto-routes to engineering manager with business impact analysis. Manager approves in 2 hours. Training scheduled for next month. Post-training, engineer leads internal workshop, multiplying impact across 10-person team. Migration completes 3 weeks early, saving $50K. Enterprise Sales Org (500 Reps) Sales rep requests "Negotiation Mastery" after losing 3 deals. AI assesses urgency as "justified" based on revenue impact. Recommends $1,100 2-day course but also suggests lower-cost alternative: internal mentoring from top performer ($0). Manager sees both options, chooses mentoring first. Rep closes next deal with new techniques. Training budget preserved for broader team enablement. ROI: $200K deal closed with $0 training spend. Healthcare System (2,000 Nurses) Nurse requests ACLS recertification. AI flags as "compliance-critical" with "immediate" urgency (expiring in 30 days). Checks budget, finds sufficient funds. Auto-approves and schedules next available session. Sends pre-training materials 1 week before. Tracks attendance, generates certificate upon completion. Updates nurse's credential profile in HRIS. Compliance maintained, no manual intervention needed. Financial Services Firm Analyst requests CFA Level 1 prep course ($2,500). AI assesses as "high ROI" but identifies budget constraint (department at 95% utilization). Recommends deferring to next quarter when new budget allocated. Suggests free Khan Academy courses as interim solution. Manager sees complete analysis, approves deferral, adds analyst to Q2 priority list. Transparent communication maintains morale despite delay. Manufacturing Company Maintenance tech requests PLC programming training. AI identifies 5 other techs with same skill gap. Recommends group training session ($1,200 per person vs $2,000 individual). Calculates team multiplier effect: 6 techs trained = reduced downtime across 3 shifts. Manager approves group session, saving $4,800. All 6 techs complete training together, creating peer support network. Equipment downtime reduced 40%. Pro Tips Quarterly Planning: Use Google Sheets data to identify trending skill gaps and plan group training Budget Forecasting: Track monthly utilization to predict Q4 budget needs Course Ratings: Add post-training feedback to improve AI recommendations over time Internal Experts: Build database of employees who can provide mentoring (free alternative) Learning Paths: Create role-based tracks (e.g., "Junior Dev → Senior Dev" pathway) Compliance Flagging: Auto-identify regulatory/certification requirements Vendor Relationships: Track volume with vendors to negotiate discounts Knowledge Retention: Require post-training presentations to reinforce learning Manager Training: Educate managers on how to evaluate AI recommendations Budget Reallocation: Monthly reviews to move unused budget between departments Early Bird Discounts: AI can suggest booking 60+ days out for savings Continuous Learning: Supplement formal training with Udemy/LinkedIn Learning subscriptions Learning Resources This workflow demonstrates advanced automation: AI Agents with complex analysis across multiple decision dimensions Budget management algorithms with real-time calculations Course recommendation engines with scoring and matching Multi-criteria approval routing based on AI confidence Skill progression modeling from current to desired states ROI analysis balancing cost, impact, and urgency Alternative suggestion algorithms for cost optimization Team impact modeling for knowledge multiplication Risk assessment frameworks for training decisions Real-Time Budget Tracking: Live department budget visibility prevents overspending Audit Trail: Complete history for finance audits and compliance reviews Approval Documentation: Timestamped manager approvals for governance Cost Allocation: Track training costs by department, employee, category ROI Measurement: Compare training investment to business outcomes Compliance Monitoring: Flag required certifications and regulatory training Vendor Management: Track spending with training providers Ready to transform your corporate training? Import this template and turn training chaos into strategic skill development with AI-powered insights and automation! 📚✨ Questions or customization? The workflow includes detailed sticky notes explaining each AI analysis component.
by Cj Elijah Garay
Discord AI Content Moderator with Learning System This n8n template demonstrates how to automatically moderate Discord messages using AI-powered content analysis that learns from your community standards. It continuously monitors your server, intelligently flags problematic content while allowing context-appropriate language, and provides a complete audit trail for all moderation actions. Use cases are many: Try moderating a forex trading community where enthusiasm runs high, protecting a gaming server from toxic behavior while keeping banter alive, or maintaining professional standards in a business Discord without being overly strict! Good to know This workflow uses OpenAI's GPT-5 Mini model which incurs API costs per message analyzed (approximately $0.001-0.003 per moderation check depending on message volume) The workflow runs every minute by default - adjust the Schedule Trigger interval based on your server activity and budget Discord API rate limits apply - the batch processor includes 1.5-second delays between deletions to prevent rate limiting You'll need a Google Sheet to store training examples - a template link is provided in the workflow notes The AI analyzes context and intent, not just keywords - "I *cking love this community" won't be deleted, but "you guys are sht" will be Deleted messages cannot be recovered from Discord - the admin notification channel preserves the content for review How it works The Schedule Trigger activates every minute to check for new messages requiring moderation We'll fetch training data from Google Sheets containing labeled examples of messages to delete (with reasons) and messages to keep The workflow retrieves the last 10 messages from your specified Discord channel using the Discord API A preparation node formats both the training examples and recent messages into a structured prompt with unique indices for each message The AI Agent (powered by GPT-5 Mini) analyzes each message against your community standards, considering intent and context rather than just keywords The AI returns a JSON array of message indices that violate guidelines (e.g., [0, 2, 5]) A parsing node extracts these indices, validates them, removes duplicates, and maps them to actual Discord message objects The batch processor loops through each flagged message one at a time to prevent API rate limiting and ensure proper error handling Each message is deleted from Discord using the exact message ID A 1.5-second wait prevents hitting Discord's rate limits between operations Finally, an admin notification is posted to your designated admin channel with the deleted message's author, ID, and original content for audit purposes How to use Replace the Discord Server ID, Moderated Channel ID, and Admin Channel ID in the "Edit Fields" node with your server's specific IDs Create a copy of the provided Google Sheets template with columns: message_content, should_delete (YES/NO), and reason Connect your Discord OAuth2 credentials (requires bot permissions for reading messages, deleting messages, and posting to channels) Add your OpenAI API key to access GPT-5 Mini Customize the AI Agent's system message to reflect your specific community standards and tone Adjust the message fetch limit (default: 10) based on your server activity - higher limits cost more per run but catch more violations Consider changing the Schedule Trigger from every minute to every 3-5 minutes if you have a smaller community Requirements Discord OAuth2 credentials for bot authentication with message read, delete, and send permissions Google Sheets API connection for accessing the training data knowledge base OpenAI API key for GPT-5 Mini model access A Google Sheet formatted with message examples, deletion labels, and reasoning Discord Server ID, Channel IDs (moderated + admin) which you can get by enabling Developer Mode in Discord Customising this workflow Try building an emoji-based feedback system where admins can react to notifications with ✅ (correct deletion) or ❌ (wrong deletion) to automatically update your training data Add a severity scoring system that issues warnings for minor violations before deleting messages Implement a user strike system that tracks repeat offenders and automatically applies temporary mutes or bans Expand the AI prompt to categorize violations (spam, harassment, profanity, etc.) and route different types to different admin channels Create a weekly digest that summarizes moderation statistics and trending violation types Add support for monitoring multiple channels by duplicating the Discord message fetch nodes with different channel IDs Integrate with a database instead of Google Sheets for faster lookups and more sophisticated training data management If you have questions Feel free to contact me here: elijahmamuri@gmail.com elijahfxtrading@gmail.com
by Jitesh Dugar
Workshop Certificate Pre-Issuance System 🎯Description Transform your event registration process with this comprehensive automation that eliminates manual certificate creation and ensures only verified attendees receive credentials. ✨ What This Workflow Does This powerful automation takes workshop/event registrations from Jotform and: Validates Email Addresses - Real-time verification using VerifiEmail API to prevent bounced emails and spam registrations Generates Professional PDF Certificates - Creates beautifully designed certificates with attendee name, event details, and unique QR code Saves to Google Drive - Automatically organizes all certificates in a dedicated folder with searchable filenames Sends Confirmation Emails - Delivers professional HTML emails with embedded certificate preview and download link Maintains Complete Records - Logs all successful and failed registrations in Google Sheets for reporting and follow-up 🎯 Perfect For Workshop Organizers** - Pre-issue attendance confirmations Training Companies** - Automate enrollment certificates Conference Managers** - Streamline attendee credentialing Event Planners** - Reduce check-in time with QR codes Educational Institutions** - Issue course registration confirmations Webinar Hosts** - Send instant confirmation certificates 💡 Key Features 🔒 Email Verification Validates deliverability before issuing certificates Detects disposable/temporary emails Prevents spam and fake registrations Reduces bounce rates to near-zero 🎨 Beautiful PDF Certificates Professional Georgia serif design Customizable colors and branding Unique QR code for event check-in Unique certificate ID for tracking Print-ready A4 format 📧 Professional Email Delivery Mobile-responsive HTML design Embedded QR code preview Direct link to Google Drive PDF Branded confirmation message Event details and instructions 📊 Complete Tracking All registrations logged in Google Sheets Separate tracking for failed validations Export data for check-in lists Real-time registration counts Deduplication by email ⚡ Lightning Fast Average execution: 15-30 seconds Instant delivery after registration No manual intervention required Scales automatically 🔧 Technical Highlights Conditional Logic** - Smart routing based on email validity Data Transformation** - Clean formatting of form data Error Handling** - Graceful handling of invalid emails Merge Operations** - Combines form data with verification results Dynamic QR Codes** - Generated with verification URLs Secure Storage** - Certificates backed up in Google Drive 📦 What You'll Need Required Services: Jotform - For registration forms VerifiEmail API - Email verification service Google Account - For Gmail, Drive, and Sheets HTMLCSStoPDF - PDF generation service Estimated Setup Time: 20 minutes 🚀 Use Cases Workshop Series Issue certificates immediately after registration Reduce no-shows with professional confirmation Easy check-in with QR code scanning Virtual Events Instant confirmation for webinar attendees Digital certificates for participants Automated follow-up communication Training Programs Pre-enrollment certificates Attendance confirmations Course registration verification Conferences & Meetups Early bird confirmation certificates Attendee badge preparation Venue capacity management 📈 Benefits ✅ Save Hours of Manual Work - No more creating certificates one by one ✅ Increase Attendance - Professional confirmations boost show-up rates ✅ Prevent Fraud - Email verification stops fake registrations ✅ Improve Experience - Instant delivery delights attendees ✅ Stay Organized - All data tracked in one central location ✅ Scale Effortlessly - Handle 10 or 10,000 registrations the same way 🎨 Customization Options The workflow is fully customizable: Certificate Design** - Modify HTML template colors, fonts, layout Email Template** - Adjust branding and messaging Form Fields** - Adapt to your specific registration needs QR Code Content** - Customize verification data Storage Location** - Choose different Drive folders Tracking Fields** - Add custom data to Google Sheets 🔐 Privacy & Security Email addresses verified before certificate issuance Secure OAuth2 authentication for all Google services No sensitive data stored in workflow GDPR-compliant data handling Certificates stored in private Google Drive 📱 Mobile Responsive Professional emails display perfectly on all devices QR codes optimized for mobile scanning Certificates viewable on phones and tablets Download links work seamlessly everywhere 🏆 Why This Workflow Stands Out Unlike basic registration confirmations, this workflow: Validates emails before generating certificates** (saves resources) Creates actual PDF documents** (not just email confirmations) Includes QR codes for event check-in** (reduces venue queues) Maintains dual tracking** (successful + failed attempts) Provides shareable Drive links** (easy resending) Works 24/7 automatically** (no manual intervention) 🎓 Learning Opportunities This workflow demonstrates: Conditional branching based on API responses Data merging from multiple sources HTML to PDF conversion Dynamic content generation Error handling and logging Professional email template design QR code integration Cloud storage automation 💬 Support & Customization Perfect for n8n beginners and experts alike: Detailed sticky notes** explain every step Clear node naming** makes it easy to understand Modular design** allows easy modifications Well-documented code** in function nodes Example data** included for testing 🌟 Get Started Import the workflow JSON Connect your credentials (Jotform, VerifiEmail, Google) Create your registration form Customize the certificate design Test with a sample registration Activate and watch it work! Tags: #events #certificates #automation #email-verification #pdf-generation #registration #workshops #training #conferences #qr-codes Category: Marketing & Events Difficulty: Intermediate
by Kirill Khatkevich
This workflow transforms your Meta Ads creatives into a rich dataset of actionable insights. It's designed for data-driven marketers, performance agencies, and analysts who want to move beyond basic metrics and understand the specific visual and textual elements that drive ad performance. By automatically analyzing every video and image with Google's powerful AI (Video Intelligence and Vision APIs), it systematically deconstructs your creatives into labeled data, ready for correlation with campaign results. Use Case You know some ads perform better than others, but do you know why? Is it the presence of a person, a specific object, the on-screen text, or the spoken words in a video? Answering these questions manually is nearly impossible at scale. This workflow automates the deep analysis process, allowing you to: Automate Creative Analysis:** Stop guessing and start making data-backed decisions about your creative strategy. Uncover Hidden Performance Drivers:** Identify which objects, themes, text, or spoken phrases correlate with higher engagement and conversions. Build a Structured Creative Database:** Create a detailed, searchable log of every element within your ads for long-term analysis and trend-spotting. Save Countless Hours:** Eliminate the tedious manual process of watching, tagging, and logging creative assets. How it Works The workflow is triggered on a schedule and follows a clear, structured path: 1. Configuration & Ad Ingestion: The workflow begins on a schedule (e.g., weekly on Monday at 10 AM). It starts by fetching all active ads from a specific Meta Ads Campaign, which you define in the Set Campaign ID node. 2. Intelligent Branching (Video vs. Image): An IF node inspects each creative to determine its type. Video creatives** are routed to the Google Video Intelligence API pipeline. Image creatives** are routed to the Google Vision API pipeline. 3. The Video Analysis Pipeline: For each video, the workflow gets a direct source URL, downloads the file, and converts it to a Base64 string. It then initiates an asynchronous analysis job in the Google Video Intelligence API, requesting LABEL_DETECTION, SPEECH_TRANSCRIPTION, and TEXT_DETECTION. A loop with a wait timer periodically checks the job status until the analysis is complete. Finally, a Code node parses the complex JSON response, structuring the annotations (like detected objects with timestamps or full speech transcripts) into clean rows. 4. The Image Analysis Pipeline: For each image, the file is downloaded, converted to Base64, and sent to the Google Vision API. It requests a wide range of features, including label, text, logo, and object detection. A Code node parses the response and formats the annotations into a standardized structure. 5. Data Logging & Robust Error Handling: All successfully analyzed data from both pipelines is appended to a primary Google Sheet. The workflow is built to be resilient. If an error occurs (e.g., a video fails to be processed by the API, or an image URL is missing), a detailed error report is logged to a separate errors sheet in your Google Sheet, ensuring no data is lost and problems are easy to track. Setup Instructions To use this template, you need to configure a few key nodes. 1. Credentials: Connect your Meta Ads account. Connect your Google account. This account needs access to Google Sheets and must have the Google Cloud Vision API and Google Cloud Video Intelligence API enabled in your GCP project. 2. The Set Campaign ID Node: This is the primary configuration step. Open this Set node and replace the placeholder value with the ID of the Meta Ads campaign you want to analyze. 3. Google Sheets Nodes: You need to configure two Google Sheets nodes: Add Segments data:** Select your spreadsheet and the specific sheet where you want to save the successful analysis results. Ensure your sheet has the following headers: campaign_id, ad_id, creative_id, video_id, file_name, image_url, source, annotation_type, label_or_text, category, full_transcript, confidence, start_time_s, end_time_s, language_code, processed_at_utc. Add errors:** Select your spreadsheet and the sheet you want to use for logging errors (e.g., a sheet named "errors"). Ensure this sheet has headers like: error_type, error_message, campaign_id, ad_id, creative_id, file_name, processed_at_utc. 4. Activate the Workflow: Set your desired frequency in the Run Weekly on Monday at 10 AM (Schedule Trigger) node. Save and activate the workflow. Further Ideas & Customization This workflow provides the "what" inside your creatives. The next step is to connect it to performance. Build a Performance Analysis Workflow:** Create a second workflow that reads this Google Sheet, fetches performance data (spend, clicks, conversions) for each ad_id from the Meta Ads API, and merges the two datasets. This will allow you to see which labels correlate with the best performance. Create Dashboards:** Use the structured data in your Google Sheet as a source for a Looker Studio or Tableau dashboard to visualize creative trends. Incorporate Generative AI:** Add a final step that sends the combined performance and annotation data to an LLM (like in the example you provided) to automatically generate qualitative summaries and recommendations for each creative. Add Notifications:** Use the Slack or Email nodes to send a summary after each run, reporting how many creatives were analyzed and if any errors occurred.
by Growth AI
Who's it for Marketing teams, business intelligence professionals, competitive analysts, and executives who need consistent industry monitoring with AI-powered analysis and automated team distribution via Discord. What it does This intelligent workflow automatically monitors multiple industry topics, scrapes and analyzes relevant news articles using Claude AI, and delivers professionally formatted intelligence reports to your Discord channel. The system provides weekly automated monitoring cycles with personalized bot communication and comprehensive content analysis. How it works The workflow follows a sophisticated 7-phase automation process: Scheduled Activation: Triggers weekly monitoring cycles (default: Mondays at 9 AM) Query Management: Retrieves monitoring topics from centralized Google Sheets configuration News Discovery: Executes comprehensive Google News searches using SerpAPI for each configured topic Content Extraction: Scrapes full article content from top 3 sources per topic using Firecrawl AI Analysis: Processes scraped content using Claude 4 Sonnet for intelligent synthesis and formatting Discord Optimization: Automatically segments content to comply with Discord's 2000-character message limits Automated Delivery: Posts formatted intelligence reports to Discord channel with branded "Claptrap" bot personality Requirements Google Sheets account for query management SerpAPI account for Google News access Firecrawl account for article content extraction Anthropic API access for Claude 4 Sonnet Discord bot with proper channel permissions Scheduled execution capability (cron-based trigger) How to set up Step 1: Configure Google Sheets query management Create monitoring sheet: Set up Google Sheets document with "Query" sheet Add search topics: Include industry keywords, competitor names, and relevant search terms Sheet structure: Simple column format with "Query" header containing search terms Access permissions: Ensure n8n has read access to the Google Sheets document Step 2: Configure API credentials Set up the following credentials in n8n: Google Sheets OAuth2: For accessing query configuration sheet SerpAPI: For Google News search functionality with proper rate limits Firecrawl API: For reliable article content extraction across various websites Anthropic API: For Claude 4 Sonnet access with sufficient token limits Discord Bot API: With message posting permissions in target channel Step 3: Customize scheduling settings Cron expression: Default set to "0 9 * * 1" (Mondays at 9 AM) Frequency options: Adjust for daily, weekly, or custom monitoring cycles Timezone considerations: Configure according to team's working hours Execution timing: Ensure adequate processing time for multiple topics Step 4: Configure Discord integration Set up Discord delivery settings: Guild ID: Target Discord server (currently: 919951151888236595) Channel ID: Specific monitoring channel (currently: 1334455789284364309) Bot permissions: Message posting, embed suppression capabilities Brand personality: Customize "Claptrap" bot messaging style and tone Step 5: Customize content analysis Configure AI analysis parameters: Analysis depth: Currently processes top 3 articles per topic Content format: Structured markdown format with consistent styling Language settings: Currently configured for French output (easily customizable) Quality controls: Error handling for inaccessible articles and content How to customize the workflow Query management expansion Topic categories: Organize queries by industry, competitor, or strategic focus areas Keyword optimization: Refine search terms based on result quality and relevance Dynamic queries: Implement time-based or event-triggered query modifications Multi-language support: Add international keyword variations for global monitoring Advanced content processing Article quantity: Modify from 3 to more articles per topic based on analysis needs Content filtering: Add quality scoring and relevance filtering for article selection Source preferences: Implement preferred publisher lists or source quality weighting Content enrichment: Add sentiment analysis, trend identification, or competitive positioning Discord delivery enhancements Rich formatting: Implement Discord embeds, reactions, or interactive elements Multi-channel distribution: Route different topics to specialized Discord channels Alert levels: Add priority-based messaging for urgent industry developments Archive functionality: Create searchable message threads or database storage Integration expansions Slack compatibility: Replace or supplement Discord with Slack notifications Email reports: Add formatted email distribution for executive summaries Database storage: Implement persistent storage for historical analysis and trending API endpoints: Create webhook endpoints for third-party system integration AI analysis customization Analysis templates: Create topic-specific analysis frameworks and formatting Competitive focus: Enhance competitor mention detection and analysis depth Trend identification: Implement cross-topic trend analysis and strategic insights Summary levels: Create executive summaries alongside detailed technical analysis Advanced monitoring features Intelligent content curation The system provides sophisticated content management: Relevance scoring: Automatic ranking of articles by topic relevance and publication authority Duplicate detection: Prevents redundant coverage of the same story across different sources Content quality assessment: Filters low-quality or promotional content automatically Source diversity: Ensures coverage from multiple perspectives and publication types Error handling and reliability Graceful degradation: Continues processing even if individual articles fail to scrape Retry mechanisms: Automatic retry logic for temporary API failures or network issues Content fallbacks: Uses article snippets when full content extraction fails Notification continuity: Ensures Discord delivery even with partial content processing Results interpretation Intelligence report structure Each monitoring cycle delivers: Topic-specific summaries: Individual analysis for each configured search query Source attribution: Complete citation with publication date, source, and URL Structured formatting: Consistent presentation optimized for quick scanning Professional analysis: AI-generated insights maintaining factual accuracy and business context Performance analytics Monitor system effectiveness through: Processing metrics: Track successful article extraction and analysis rates Content quality: Assess relevance and usefulness of delivered intelligence Team engagement: Monitor Discord channel activity and report utilization System reliability: Track execution success rates and error patterns Use cases Competitive intelligence Market monitoring: Track competitor announcements, product launches, and strategic moves Industry trends: Identify emerging technologies, regulatory changes, and market shifts Partnership tracking: Monitor alliance formations, acquisitions, and strategic partnerships Leadership changes: Track executive movements and organizational restructuring Strategic planning support Market research: Continuous intelligence gathering for strategic decision-making Risk assessment: Early warning system for industry disruptions and regulatory changes Opportunity identification: Spot emerging markets, technologies, and business opportunities Brand monitoring: Track industry perception and competitive positioning Team collaboration enhancement Knowledge sharing: Centralized distribution of relevant industry intelligence Discussion facilitation: Provide common information baseline for strategic discussions Decision support: Deliver timely intelligence for business planning and strategy sessions Competitive awareness: Keep teams informed about competitive landscape changes Workflow limitations Language dependency: Currently optimized for French analysis output (easily customizable) Processing capacity: Limited to 3 articles per query (configurable based on API limits) Platform specificity: Configured for Discord delivery (adaptable to other platforms) Scheduling constraints: Fixed weekly schedule (customizable via cron expressions) Content access: Dependent on article accessibility and website compatibility with Firecrawl API dependencies: Requires active subscriptions and proper rate limit management for all integrated services