Workflow Templates

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.

🔧 AI-Powered Auto-Maintenance System for n8n Transform your n8n instance management with this advanced automation system featuring artificial intelligence-driven workflow selection. This template provides comprehensive maintenance operations with smart filtering capabilities. ✨ Key Features 🤖 Artificial Intelligence Engine Multi-criteria scoring system for intelligent workflow selection Semantic analysis for business-critical pattern recognition Automated decision-making with configurable thresholds 🎯 Core Maintenance Operations Security Audits**: Automated vulnerability scanning with Google Sheets reporting Smart Pause/Resume**: Intelligent workflow suspension during maintenance windows AI Backup Creation**: Selective duplication of high-value workflows Intelligent Export**: Comprehensive system backups with metadata 🔐 Enterprise Security Token-based authentication with request validation Protected workflow safeguards (never modifies critical systems) Comprehensive error handling and logging ⚡ Automation & Scheduling Configurable maintenance schedules (daily, weekly, monthly) Webhook-driven operations for external integration Real-time monitoring and statistics 🎯 Perfect For DevOps Teams**: Streamline n8n maintenance operations Enterprise Users**: Manage large-scale workflow environments System Administrators**: Automated security and backup management Advanced Users**: Leverage AI for intelligent workflow management 🚀 Quick Setup Import the template Configure 4 credentials (n8n API, Google Sheets, Google Drive, Webhook Auth) Set your security token and Google Sheet ID Activate and enjoy automated maintenance! 🧠 AI Intelligence Highlights The system evaluates workflows using 6+ criteria including activity status, complexity, priority tags, business criticality, and recent updates. Workflows are automatically scored and selected based on intelligent thresholds. Selection Logic: Duplicate threshold: ≥3 points (smart backup selection) Export threshold: ≥5 points (comprehensive backup) System workflows always protected 📊 Includes 25+ configured nodes with emoji naming 4 detailed markdown documentation cards Pre-configured schedules and examples Comprehensive error handling Statistical reporting and monitoring Perfect for organizations looking to implement intelligent, automated n8n maintenance with minimal manual intervention.

Intelligent chatbot with custom knowledge base Who's it for Businesses, developers, and organizations who need a customizable AI chatbot for internal documentation access, customer support, e-commerce assistance, or any use case requiring intelligent conversation with access to specific knowledge bases. What it does This workflow creates a fully customizable AI chatbot that can be deployed on any platform supporting webhook triggers (websites, Slack, Teams, etc.). The chatbot accesses a personalized knowledge base stored in Supabase and can perform advanced actions like sending emails, scheduling appointments, or updating databases beyond simple conversation. How it works The workflow combines several powerful components: Webhook Trigger: Accepts messages from any platform that supports webhooks AI Agent: Processes user queries with customizable personality and instructions Vector Database: Searches relevant information from your Supabase knowledge base Memory System: Maintains conversation history for context and traceability Action Tools: Performs additional tasks like email sending or calendar booking Technical architecture Chat trigger connects directly to AI Agent Language model, memory, and vector store all connect as tools/components to the AI Agent Embeddings connect specifically to the Supabase Vector Store for similarity search Requirements Supabase account and project AI model API key (any LLM provider of your choice) OpenAI API key (for embeddings - this is covered in Cole Medin's tutorial) n8n built-in PostgreSQL access (for conversation memory) Platform-specific webhook configuration (optional) How to set up Step 1: Configure your trigger The template uses n8n's default chat trigger For external platforms: Replace with webhook trigger and configure your platform's webhook URL Supported platforms: Any service with webhook capabilities (websites, Slack, Teams, Discord, etc.) Step 2: Set up your knowledge base For creating and managing your vector database, follow this comprehensive guide: Watch Cole Medin's tutorial on document vectorization This video shows how to build a complete knowledge base on Supabase The tutorial covers document processing, embedding creation, and database optimization Important: The video explains the OpenAI embeddings configuration required for vector search Step 3: Configure the AI agent Define your prompt: Customize the agent's personality and role Example: "You are the virtual assistant for example.com. Help users by answering their questions about our products and services." Select your language model: Choose any AI provider you prefer (OpenAI, Anthropic, Google, etc.) Set behavior parameters: Define response style, tone, and limitations Step 4: Connect Supabase Vector Store Add the "Supabase Vector Store" tool to your agent Configure your Supabase project credentials Mode: Set to "retrieve-as-tool" for automatic agent integration Tool Description: Customize description (default: "Database") to describe your knowledge base Table configuration: Specify the table containing your knowledge base (example shows "growth_ai_documents") Ensure your table name matches your actual knowledge base structure Multiple tables: You can connect several tables for organized data structure The agent will automatically decide when to search the knowledge base based on user queries Step 5: Set up conversation memory (recommended) Use "Postgres Chat Memory" with n8n's built-in PostgreSQL credentials Configure table name: Choose a name for your chat history table (will be auto-created) Context Window Length: Set to 20 messages by default (adjustable based on your needs) Benefits: Conversation traceability and analytics Context retention across messages Unique conversation IDs for user sessions Stored in n8n's database, not Supabase How to customize the workflow Basic conversation features Response style: Modify prompts to change personality and tone Knowledge scope: Update Supabase tables to expand or focus the knowledge base Language support: Configure for multiple languages Response length: Set limits for concise or detailed answers Memory retention: Adjust context window length for longer or shorter conversation memory Advanced action capabilities The chatbot can be extended with additional tools for: Email automation: Send support emails when users request assistance Calendar integration: Book appointments directly in Google Calendar Database updates: Modify Airtable or other databases based on user interactions API integrations: Connect to external services and systems File handling: Process and analyze uploaded documents Platform-specific deployments Website integration Replace chat trigger with webhook trigger Configure your website's chat widget to send messages to the n8n webhook URL Handle response formatting for your specific chat interface Slack/Teams deployment Set up webhook trigger with Slack/Teams webhook URL Configure response formatting for platform-specific message structures Add platform-specific features (mentions, channels, etc.) E-commerce integration Connect to product databases Add order tracking capabilities Integrate with payment systems Configure support ticket creation Results interpretation Conversation management Chat history: All conversations stored in n8n's PostgreSQL database with unique IDs Context tracking: Agent maintains conversation flow and references previous messages Analytics potential: Historical data available for analysis and improvement Knowledge retrieval Semantic search: Vector database returns most relevant information based on meaning, not just keywords Automatic decision: Agent automatically determines when to search the knowledge base Source tracking: Ability to trace answers back to source documents Accuracy improvement: Continuously refine knowledge base based on user queries Use cases Internal applications Developer documentation: Quick access to technical guides and APIs HR support: Employee handbook and policy questions IT helpdesk: Troubleshooting guides and system information Training assistant: Learning materials and procedure guidance External customer service E-commerce support: Product information and order assistance Technical support: User manuals and troubleshooting Sales assistance: Product recommendations and pricing FAQ automation: Common questions and instant responses Specialized implementations Lead qualification: Gather customer information and schedule sales calls Appointment booking: Healthcare, consulting, or service appointments Order processing: Take orders and update inventory systems Multi-language support: Global customer service with language detection Workflow limitations Knowledge base dependency: Quality depends on source documentation and embedding setup Memory storage: Requires active n8n PostgreSQL connection for conversation history Platform restrictions: Some platforms may have webhook limitations Response time: Vector search may add slight delay to responses Token limits: Large context windows may increase API costs Embedding costs: OpenAI embeddings required for vector search functionality

Analyzes influencer profiles and scores authenticity before brand partnership approval. Detects fake followers, bot accounts, and suspicious engagement patterns using AI-powered behavioral analysis. 🎯 How It Works Simple 7-Node Workflow: Input → Submit influencer username and platform (Instagram/Twitter/TikTok) Fetch → Retrieve complete profile data and engagement metrics Analyze → Examine follower patterns, ratios, growth velocity, engagement AI Check → Deep behavioral analysis with Claude AI Report → Generate comprehensive fraud assessment Notify → Send detailed email report to partnership team Log → Save to database for tracking 📊 Detection Capabilities Follower Authenticity**: Analyzes follower-to-following ratio (red flag if < 0.5) Engagement Quality**: Calculates engagement rate (industry avg: 1-5%) Growth Patterns**: Detects suspicious rapid follower spikes Content Consistency**: Evaluates posting frequency and regularity Profile Completeness**: Checks verification, bio, activity AI Behavioral Analysis**: Deep pattern recognition for sophisticated fraud ⚙️ Setup Instructions 1. Configure API Access Social Platform APIs: Instagram**: Get Graph API access token from Meta for Developers Twitter**: OAuth 2.0 credentials from Twitter Developer Portal TikTok**: Business API credentials (optional) AI Analysis: Anthropic Claude API**: Get key from console.anthropic.com Used for advanced behavioral fraud detection 2. Setup Notifications Configure SMTP in "Send Report" node Update recipient email (partnerships@company.com) Customize HTML template if needed 3. Database (Optional) Create PostgreSQL table (schema below) Add database credentials to final node Skip if you don't need historical tracking Database Schema CREATE TABLE partnerships.influencer_fraud_reports ( id SERIAL PRIMARY KEY, report_id VARCHAR(255) UNIQUE, username VARCHAR(255), platform VARCHAR(50), profile_url TEXT, followers BIGINT, following BIGINT, posts INTEGER, verified BOOLEAN, authenticity_score INTEGER, risk_level VARCHAR(50), final_decision TEXT, partnership_recommendation VARCHAR(100), ai_verdict VARCHAR(50), ai_confidence VARCHAR(20), red_flags JSONB, fake_follower_estimate VARCHAR(20), detailed_analysis JSONB, created_at TIMESTAMP ); 🚀 How to Use Webhook Endpoint: POST /webhook/influencer-fraud-check Request Body: { "username": "influencer_handle", "platform": "instagram" // or "twitter", "tiktok" } Example: curl -X POST https://your-n8n.com/webhook/influencer-fraud-check \ -H "Content-Type: application/json" \ -d '{"username":"example_user","platform":"instagram"}' 📈 Scoring System Overall Authenticity Score (0-100): 80-100**: LOW RISK → Approved for partnership 60-79**: MEDIUM RISK → Requires manual review 40-59**: HIGH RISK → Caution advised 0-39**: CRITICAL RISK → Rejected Weighted Components: Follower Quality (25%) Engagement Quality (35%) Content Consistency (15%) Growth Pattern (15%) Profile Completeness (10%) Final Score = 70% Automated + 30% AI Analysis 🚩 Red Flags Detected Following-to-follower ratio > 2:1 Engagement rate < 0.5% Rapid growth (>50K followers/month) Large following with <10 posts No verification with >100K followers Bot-like comment patterns Suspicious audience demographics 💰 Cost Estimate Instagram/Twitter API**: Free tier usually sufficient Claude AI**: ~$0.10-0.20 per analysis Estimated**: $5-10/month for 50 checks 💡 Best Practices Always verify HIGH and MEDIUM risk profiles manually Cross-reference with other influencer databases Request media kit and past campaign results Trial campaigns before large commitments Monitor performance metrics post-partnership Update detection thresholds based on your findings 🎯 What You Get Detailed Report Includes: Overall authenticity score (0-100) Risk level classification Partnership recommendation (APPROVE/REVIEW/REJECT) Engagement quality analysis Fake follower percentage estimate AI behavioral insights Specific red flags and concerns Next steps and recommendations

AI-powered alt text generation from Google Sheets to WordPress media Who's it for WordPress site owners, content managers, and accessibility advocates who need to efficiently add alt text descriptions to multiple images for better SEO and web accessibility compliance. What it does This workflow automates the process of generating and updating alt text for WordPress media files using AI analysis. It reads image URLs from a Google Sheet, analyzes each image with Claude AI to generate accessibility-compliant descriptions, updates the sheet with the generated alt text, and automatically applies the descriptions to the corresponding WordPress media files. The workflow includes error handling to skip unsupported media formats and continue processing. How it works Input: Provide a Google Sheets URL containing image URLs and WordPress media IDs Authentication: Retrieves WordPress credentials from a separate sheet and generates Base64 authentication Processing: Loops through each image URL in the sheet AI Analysis: Claude AI analyzes each image and generates concise, accessible alt text (max 125 characters) Error Handling: Automatically skips unsupported media formats and continues with the next item Update Sheet: Writes the generated alt text back to the Google Sheet WordPress Update: Updates the WordPress media library with the new alt text via REST API Requirements Google Sheets with image URLs and WordPress media IDs WordPress site with Application Passwords enabled Claude AI (Anthropic) API credentials WordPress admin credentials stored in Google Sheets Export Media URLs WordPress plugin for generating the media list How to set up Step 1: Export your WordPress media URLs Install the "Export Media URLs" plugin on your WordPress site Go to the plugin settings and check both ID and URL columns for export (these are mandatory for the workflow) Export your media list to get the required data Step 2: Configure WordPress Application Passwords Go to WordPress Admin → Users → Your Profile Scroll down to "Application Passwords" section Enter application name (e.g., "n8n API") Click "Add New Application Password" Copy the generated password immediately (it won't be shown again) Step 3: Set up Google Sheets Duplicate this Google Sheets template to get the correct structure. The template includes two sheets: Sheet 1: "Export media" - Paste your exported media data with columns: ID (WordPress media ID) URL (image URL) Alt text (will be populated by the workflow) Sheet 2: "Infos client" - Add your WordPress credentials: Admin Name: Your WordPress username KEY: The application password you generated Domaine: Your site URL without https:// (format: "example.com") Step 4: Configure API credentials Add your Anthropic API credentials to the Claude node Connect your Google Sheets account to the Google Sheets nodes How to customize Language: The Claude prompt is in French - modify it in the "Analyze image" node for other languages Alt text length: Adjust the 125-character limit in the Claude prompt Batch processing: Change the batch size in the Split in Batches node Error handling: The workflow automatically handles unsupported formats, but you can modify the error handling logic Authentication: Customize for different WordPress authentication methods This workflow is perfect for managing accessibility compliance across large WordPress media libraries while maintaining consistent, AI-generated descriptions. It's built to be resilient and will continue processing even when encountering unsupported media formats.

This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primary_keywords, seo_strength_score, keyword_density_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors** → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection** → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report** → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization** → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs** → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo** for intelligent web scraping OpenAI GPT-4.1-mini** for keyword and SEO analysis Google Sheets** for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.

This automated n8n workflow transforms uploaded radiology images into professional, patient-friendly PDF reports. It uses AI-powered image analysis to interpret medical scans, simplify technical terms, and produce clear explanations. The reports are formatted, converted to PDF, stored in a database, and sent directly to patients via email, ensuring both accuracy and accessibility. 🏥 Workflow Overview: Simple Process Flow: Upload Image → 2. AI Analysis → 3. Generate Report → 4. Send to Patient 🔧 How It Works: Webhook Trigger - Receives image uploads via POST request Extract Image Data - Processes patient info and image data AI Image Analysis - Uses GPT-4 Vision to analyze the radiology image Process Analysis - Structures the AI response into readable sections Generate PDF Report - Creates a beautiful HTML report Convert to PDF - Converts HTML to downloadable PDF Save to Database - Logs all reports in Google Sheets Email Patient - Sends the report via email Return Response - Confirms successful processing 📊 Key Features: AI-Powered Analysis** using GPT-4 Vision Patient-Friendly Language** (no medical jargon) Professional PDF Reports** with clear sections Email Delivery** with report attachment Database Logging** for record keeping Simple Webhook Interface** for easy integration 🚀 Usage Example: Send POST request to webhook with: { "patient_name": "John Smith", "patient_id": "P12345", "scan_type": "X-Ray", "body_part": "Chest", "image_url": "https://example.com/xray.jpg", "doctor_name": "Dr. Johnson", "patient_email": "john@email.com" } ⚙️ Required Setup: OpenAI API - For GPT-4 Vision image analysis PDF Conversion Service - HTML to PDF converter Gmail Account - For sending reports Google Sheets - For logging reports Replace YOUR_REPORTS_SHEET_ID with your actual sheet ID Want a tailored workflow for your business? Our experts can craft it quickly Contact our team

This n8n template demonstrates how to capture website leads via a webhook, validate the data, optionally enrich it, store it in your CRM (HubSpot) or a simple Google Sheet, and instantly notify your team via email and Slack. This is ideal for agencies, freelancers, SaaS founders, and small sales teams who want every lead recorded and followed up automatically within seconds. Good to know The workflow supports two storage options: HubSpot or Google Sheets (choose one branch). Enrichment (Clearbit/Hunter) is optional and can be disabled with a single toggle/IF branch. Consider adding anti-spam (honeypot/captcha) if your form gets abused. How it works Webhook receives the lead Your website form sends a POST request to the Webhook URL with lead fields (name, email, message, etc.). Validation & normalization The workflow trims and normalizes fields (like lowercasing email) and checks required fields. If invalid, it returns a Optional enrichment (Clearbit/Hunter) If enrichment is enabled, the workflow calls an enrichment API and merges results into the lead object (industry, company size, domain, etc.). If enrichment fails, the workflow continues (doesn’t block lead capture). Save lead to CRM (Choose one) HubSpot branch**: find contact by email → create or update the contact record Google Sheets branch**: lookup row by email → update if found → otherwise append a new row Instant notifications Posts a Slack message to a channel, optionally including a CRM/Sheet link Success response to the website Returns a #### How to use? Import the workflow into n8n. Configure the Webhook node and copy the production URL into your website form submit action. Choose your storage path: Enable HubSpot nodes OR Enable Google Sheets nodes Add credentials: Slack credential (Optional) HubSpot / Google Sheets (Optional) Clearbit/Hunter keys in the HTTP Request node Send a test lead from your website and confirm: Lead saved correctly Email received Slack notification posted Website receives a 200 response Requirements An n8n instance (cloud or self-hosted) One of: HubSpot account (for CRM storage), or Google account + Google Sheets (for spreadsheet storage) Slack workspace + Slack credentials Optional: Clearbit/Hunter account for enrichment

Who’s it for Women creators, homemakers-turned-entrepreneurs, and feminine lifestyle brands who want a graceful, low-lift way to keep an eye on competitor content and spark weekly ideas. What it does On a weekly schedule, this workflow crawls your competitor URLs with Firecrawl (HTTP Request), summarizes each page with OpenAI, brainstorms carousel/pin ideas with Gemini, appends results to Google Sheets (Date, URL, Title, Summary, Ideas), and sends you a single email digest (optional Telegram alert). It includes basic error notifications and a setup-friendly config node. Requirements HTTP credentials** for Firecrawl, OpenAI, and Gemini (no keys in nodes) Google Sheets** OAuth credential A Sheets document with a target sheet/range (e.g., Digest!A:F) (Optional) Telegram bot + chat ID How to set up Open Set: Configuration (edit me) and fill: competitorUrls (one per line), sheetsSpreadsheetId, sheetsRange, ownerEmail, emailTo, geminiModel, openaiModel Attach credentials to the HTTP and Sheets nodes. Test by switching Cron to Every minute, then revert to weekly. How it works Cron → Firecrawl (per URL) → Normalize → OpenAI (summary) + Gemini (ideas) → Merge → Compile Row → Google Sheets append → Build one digest → Email (+ optional Telegram). How to customize Add/remove competitors or change the weekly send time. Tweak the OpenAI/Gemini prompts for your brand voice. Expand columns in Sheets (e.g., category, tone, CTA). Swap email/Telegram for Slack/Notion, or add persistent logs.

Scheduled Backup Automation – Mailgun & Box This workflow automatically schedules, packages, and uploads backups of your databases, files, or configuration exports to Box cloud storage, then sends a completion email via Mailgun. It is ideal for small-to-medium businesses or solo developers who want hands-off, verifiable backups without writing custom scripts. Pre-conditions/Requirements Prerequisites n8n instance (self-hosted or n8n.cloud) Box account with a folder dedicated to backups Mailgun account & verified domain Access to the target database/server you intend to back up Basic knowledge of environment variables to store secrets Required Credentials Box OAuth2** – For uploading the backup file(s) Mailgun API Key** – For sending backup status notifications (Optional) Database Credentials** – Only if the backup includes a DB dump triggered from inside n8n Specific Setup Requirements | Variable | Example | Purpose | |-------------------------|------------------------------------------|---------------------------------------| | BOX_FOLDER_ID | 1234567890 | ID of the Box folder that stores backups | | MAILGUN_DOMAIN | mg.example.com | Mailgun domain used for sending email | | MAILGUN_FROM | Backups <backup@mg.example.com> | “From” address in status emails | | NOTIFY_EMAIL | admin@example.com | Recipient of backup status emails | How it works This workflow automatically schedules, packages, and uploads backups of your databases, files, or configuration exports to Box cloud storage, then sends a completion email via Mailgun. It is ideal for small-to-medium businesses or solo developers who want hands-off, verifiable backups without writing custom scripts. Key Steps: Webhook (Scheduler Trigger)**: Triggers the workflow on a CRON schedule or external call. Code (DB/File Dump)**: Executes bash or Node.js commands to create a tar/zip or SQL dump. Move Binary Data**: Converts the created file into n8n binary format. Set**: Attaches metadata (timestamp, file name). Split In Batches* *(optional): Splits multiple backup files for sequential uploads. Box Node**: Uploads each backup file into the specified Box folder. HTTP Request (Verify Upload)**: Calls Box API to confirm upload success. If**: Branches on success vs failure. Mailgun Node**: Sends confirmation or error report email. Sticky Notes**: Provide inline documentation inside the workflow canvas. Set up steps Setup Time: 15-20 minutes Clone or import the workflow JSON into your n8n instance. Create credentials: Box OAuth2: paste Client ID, Client Secret, perform OAuth handshake. Mailgun API: add Private API key and domain. Update environment variables (BOX_FOLDER_ID, MAILGUN_DOMAIN, etc.) or edit the relevant Set node. Modify the Code node to run your specific backup command, e.g.: pg_dump -U $DB_USER -h $DB_HOST $DB_NAME > /tmp/db_backup.sql tar -czf /tmp/full_backup_{{new Date().toISOString()}}.tar.gz /etc/nginx /var/www /tmp/db_backup.sql Set the CRON schedule inside the Webhook node (or replace with a Cron node) to your desired frequency (daily, weekly, etc.). Execute once manually to verify the Box upload and email notification. Enable the workflow. Node Descriptions Core Workflow Nodes: Webhook / Cron** – Acts as the time-based trigger for backups. Code** – Creates the actual backup archive (tar, zip, SQL dump). Move Binary Data** – Moves the generated file into binary property. Set** – Adds filename and timestamp metadata for Box. Split In Batches** – Handles multiple files when necessary. Box** – Uploads the backup file to Box. HTTP Request** – Optional re-check to ensure the file exists in Box. If** – Routes the flow based on success or error. Mailgun** – Sends success/failure notifications. Sticky Note** – Explains credential handling and customization points. Data Flow: Webhook/Cron → Code → Move Binary Data → Set → Split In Batches → Box → HTTP Request → If → Mailgun Customization Examples Add Retention Policy (Auto-delete old backups) // In a Code node before upload const retentionDays = 30; const cutoff = Date.now() - retentionDays * 246060*1000; items = items.filter(item => { return item.json.modifiedAt > cutoff; // keep only recent files }); return items; Parallel Upload to S3 // Duplicate the Box node, replace with AWS S3 node // Use Merge node to combine results before the HTTP Request verification Data Output Format The workflow outputs structured JSON data: { "fileName": "full_backup_2023-10-31T00-00-00Z.tar.gz", "boxFileId": "9876543210", "uploadStatus": "success", "timestamp": "2023-10-31T00:05:12Z", "emailNotification": "sent" } Troubleshooting Common Issues “Invalid Box Folder ID” – Verify BOX_FOLDER_ID and ensure the OAuth user has write permissions. Mailgun 401 Unauthorized – Check that you used the Private API key and the domain is verified. Backup file too large – Enable chunked upload in Box node or increase client_max_body_size on reverse proxy. Performance Tips Compress backups with gzip or zstd to reduce upload time. Run the database dump on the same host as n8n to avoid network overhead. Pro Tips: Store secrets as environment variables and reference them in Code nodes (process.env.MY_SECRET). Chain backups with version numbers (YYYYMMDD_HHmm) for easy sorting. Use n8n’s built-in execution logging to audit backup history. This is a community workflow template provided “as-is” without warranty. Adapt and test in a safe environment before using in production.

Classify YouTube Trends and Generate Email Summaries with GPT-4 and Gmail Monitor YouTube channels, fetch stats, classify videos as viral (≥ 1000 likes) or normal, and auto‑generate LinkedIn/email summaries with GPT‑4. Deliver via Gmail or SMTP. Clear node names, examples, and auditable fields. 🎯 Overview This template monitors YouTube channels via RSS or the YouTube Data API, retrieves video stats, classifies each video as viral (≥ 1000 likes) or normal, and produces concise LinkedIn/email summaries with OpenAI (GPT‑4 family). It can send a compact weekly briefing via Gmail (OAuth2) or SMTP. Built for creators, marketing teams, and agencies who want automated trend alerts and ready‑to‑use content. This screenshot shows the Gmail-ready weekly briefing generated by the Generate Weekly Briefing (HTML) node in my YouTube Trend Detector workflow, confirming the end-to-end pipeline: RSS/API → stats → like-based classification (≥ 1000 = viral) → LLM summaries → HTML email. 🧭 How It Works (Node Map) Manual Run – ad‑hoc execution Set Channel IDs – provide one or more YouTube channelId values Split Channels – process channels one by one Fetch Latest Videos (RSS) – pull recent uploads via channel RSS Filter: Published in Last 72h – only recent items are kept Get Video Stats (YouTube API) – request snippet,statistics for likes and details Classify by Likes (Code) – sets classification to viral or normal Branch: Normal / Branch: Viral – separate LLM prompts per relevance Write Post (Normal / Viral) – generate LinkedIn‑style notes via OpenAI Aggregate Posts for Briefing – merge all texts into one block Generate Weekly Briefing (HTML) – produce a Gmail‑robust HTML email via GPT Send Weekly Briefing (Gmail/SMTP) – deliver briefing (you set recipients) ⚙️ Quick Start (≈ 3 minutes) Import the sanitized JSON into n8n (Menu → Import). Create credentials (use exact names): YouTube_API_Key — Generic credential (field: apiKey) OpenAi account — OpenAI API Key Gmail account (OAuth2) or SMTP_Default (SMTP) Configure channels: In Set Channel IDs, list your YouTube channelId values (e.g., UC…). Set recipients: In Send Weekly Briefing, add your target email(s). Test: Run Execute Workflow and review outputs from the LLM and send nodes. 🔑 Required Credentials YouTube_API_Key** — YouTube Data API v3 key (field apiKey) OpenAi account** — OpenAI API key for LLM nodes Gmail account* (OAuth2, recommended) *or* *SMTP_Default** (server/port/TLS + app password if 2FA) 🧩 Key Parameters & Adjustments Viral threshold:** In Classify by Likes (Code) → const THRESHOLD = 1000; YouTube API parts:** Use part=snippet,statistics to obtain likeCount Time window:* The filter keeps videos from the *last 72 hours** 🧪 Troubleshooting Missing likeCount / classification = "unknown"** → ensure part=statistics and a valid API key credential. Gmail OAuth redirect_mismatch / access_denied** → redirect must be https://<your-n8n-host>/rest/oauth2-credential/callback and test users added if restricted. SMTP auth issues** → set correct server/port/TLS and use an app password when 2FA is enabled. Empty LLM output** → verify OpenAI key/quota and inspect node logs. 🧾 Example Outputs 1) Classification (single video) { "videoId": "abc123XYZ", "title": "How to Ship an n8n Workflow with OpenAI", "likeCount": 1587, "classification": "viral", "needsStatsFetch": false } 2) LinkedIn draft (viral) Did you know how much faster prompt workflows get with structured inputs? • Setup: n8n + YouTube API + OpenAI for auto-briefs • Tip: include part=statistics for reliable like counts Useful for teams tracking trending how-to content. What’s your best “viral” signal besides likes? #n8n #YouTubeAPI #OpenAI #Automation #Growth 3) Plain‑text email preview Subject: Weekly AI Briefing — YouTube Trend Highlights Hi team, Highlights from our tracked channels: • Viral: “How to Ship an n8n Workflow with OpenAI” (1.6k likes) • Normal: “RSS vs API: What’s Best for Monitoring?” Generated via n8n + GPT‑4. ✅ Submission Checklist (meets the guidelines) Title clarity:* Mentions *GPT‑4* and *Gmail** Language:* Entire document in *English** Node naming:** Descriptive, non‑generic labels HTML → Markdown:* No HTML in this description; badges are *Markdown images** Examples:** Included (JSON, LinkedIn draft, email) Security:** No secrets in JSON; uses credentials by name 📸 Suggested Screenshots (optional) Full canvas overview (entire workflow) LLM output (expanded) showing generated summary Send‑node result with messageId/status Optional: aggregated briefing preview 📜 License & Support License: MIT Support/Contact: kaihoelters@yahoo.de

Automated Weekly Newsletter with AI Research, Editorial Drafting, and Approval Flow This n8n template demonstrates how to automate the full production cycle of a professional weekly newsletter. It combines AI-powered market research, editorial drafting, compliance validation, and an approval loop — all before creating a final Gmail draft ready for distribution. Use cases are many: Wealth managers sending weekly market updates to clients Startups producing recurring research digests Teams creating automated newsletters for marketing or content distribution Good to know At time of writing, each AI call (research, editorial, QC) consumes API tokens from Perplexity and OpenAI. See provider pricing for updated info. Gmail integration requires OAuth setup with your account. You can adapt the prompts to any domain — from finance to tech to education. How it works Schedule Trigger runs every week and sets the date window. Research LLM fetches structured JSON market data using Perplexity. Editorial LLM transforms research into a polished ~2,000 word client-ready newsletter. QC LLM validates factual accuracy and compliance risks before approval. Preview Email is sent with Approve/Revise buttons. Clicking opens a secure n8n-hosted approval form. Final Draft Creation: Once approved, the workflow generates a clean Gmail draft, ready to send. How to use Replace the demo schedule trigger with your own (weekly, daily, or event-based). Set up Gmail OAuth credentials to enable email previews and final drafts. Update branding (logo, disclaimer, signature) in the HTML builder node. Adjust prompts to your audience — e.g., simplify tone for marketing, or keep institutional tone for financial clients. Requirements Perplexity account for research API (or your LLM of choice) OpenAI for editorial and QC steps (or your LLM of choice) Gmail account with OAuth credentials Optional: your own domain to host the approval webhook Customising this workflow This workflow can be extended beyond financial newsletters. Try: Content marketing: Automate weekly digests or trend reports Education: Generate curriculum summaries with approval loops for teachers Internal comms: Automate compliance-checked company updates