Workflow Templates

This n8n is a daily analytics automation that calculates which lead sources generate actual revenue, not just leads. Provides ROI data, conversion rates, and budget allocation recommendations. Use Case: automates marketing ROI tracking by linking closed deals to their lead sources in Airtable, calculating revenue and ROI per channel, and sending daily insights to Slack. What It Does Runs nightly to analyze closed deals from last 30 days Matches deals to their original lead sources Calculates total revenue per source Computes ROI (revenue vs. cost per lead) Determines conversion rates by source Updates Lead Sources table with metrics Sends weekly reports to team How It Works Step 1: Schedule Trigger Runs daily at midnight Step 2: Fetch Closed Won Deals Gets all deals where: Stage = "Closed Won" Actual Close Date in last 30 days Step 3: Fetch Lead Sources Gets cost and lead count data from Lead Sources table Step 4: Calculate ROI (JavaScript) For each source: Total revenue = Sum of all deals from that source Total cost = Cost per lead × Total leads ROI = ((Revenue - Cost) / Cost) × 100 Conversion rate = Deals closed / Total leads × 100 Average deal size = Revenue / Deal count Step 5: Update Lead Sources Writes calculated metrics back to Airtable Step 6: Send Report Slack message with top 3 performing sources Business Impact Marketing ROI:** Know exactly which channels generate revenue Budget optimization:** Allocate spend to highest-ROI sources Data-driven decisions:** Stop guessing, start knowing Cost reduction:** Cut low-performing channels Revenue growth:** Double down on what works Technical Requirements n8n (self-hosted or cloud) Airtable (uses existing tables) Slack (for reports) Gmail for reminder incase CEO missed the report in the Slack channel (optional)

Supercharge your sales and marketing efforts with this powerful automation that transforms a list of LinkedIn profiles into a fully enriched, personalized outreach campaign. This workflow is designed for sales teams, growth marketers, and business development professionals looking to scale their lead generation without sacrificing personalization. It seamlessly integrates LinkedIn scraping, email enrichment with Hunter.io, AI-powered message generation with OpenAI, and data organization in Google Sheets. How It Works Start with Leads: The workflow begins with a list of target LinkedIn profile URLs. Scrape Profile Data: It automatically scrapes each LinkedIn profile to extract key professional information such as name, title, company, and location. A built-in delay helps manage rate limits. Find Verified Emails: Using the scraped company and name, the workflow queries ==Hunter.io to find a verified work email address== for the lead. AI-Powered Personalization: If an email is found, the lead's data is sent to OpenAI (GPT-4), which generates a highly personalized, conversational outreach message based on their role, company, and your value proposition. Sync to CRM/Sheet: Finally, all the enriched data—including the custom AI message—is neatly organized and saved as a new row in your designated Google Sheet. Stop wasting hours on manual lead research and generic outreach. Implement this automated workflow to focus on building relationships and closing deals.

Description: Stay on top of your support pipeline with this Ticket Status Digest automation for Zendesk. Built in n8n, this workflow automatically fetches tickets from Zendesk, filters only open ones, enriches them with requester details, and saves them into Google Sheets. 📊 Instead of manually checking Zendesk, you get a real-time digest of pending tickets with full customer details—perfect for support leads who need a quick snapshot of unresolved cases. Whether you’re tracking team workload, prioritizing open issues, or preparing daily status reports, this automation ensures your support data is always structured, centralized, and up to date. 🚀 What This Template Does (Step-by-Step) 🔔 Trigger – Manual Start (or Schedule) Begin workflow with a manual trigger (ideal for testing). Can be switched to scheduled runs (daily, hourly) for automated digests. 🎫 Fetch All Tickets (Zendesk) Pulls all tickets from Zendesk API. Captures ticket ID, subject, description, status, priority, tags, and timestamps. 🔍 Filter Open Tickets Only Includes only tickets where status = open. Skips closed, solved, or pending tickets. 👤 User Information Enrichment Looks up requester details (name, email, organization). Converts raw IDs into human-readable contact info. 📊 Save to Google Sheets Appends/updates ticket rows in “Ticket status dummy → Sheet1”. Columns: Ticket No. | Description | Status | Owner | Email | Tag. Required Integrations: Zendesk API (OAuth or API Key) Google Sheets (OAuth2 credentials) Best For: 🧑‍💼 Support leads monitoring unresolved tickets 📈 Managers building daily ticket status dashboards 🤝 Teams that need centralized visibility of customer issues ⏱️ Anyone tired of manual Zendesk data exports Key Benefits: ✅ Automated ticket sync to Google Sheets ✅ Real-time visibility of open issues ✅ Centralized view with enriched requester details ✅ Reduces manual tracking and reporting ✅ Scalable for daily, weekly, or custom digest runs

Short Description Automatically scrape new Upwork job listings, save them to Google Sheets, and get real-time WhatsApp alerts when new matching jobs appear. This workflow helps freelancers and agencies track new opportunities instantly — without checking Upwork manually. Who’s it for For freelancers, agencies, and automation enthusiasts who want to monitor Upwork jobs automatically and receive instant notifications for relevant projects. How it works This workflow connects with RapidAPI to fetch new Upwork job listings, filters relevant ones, stores them in a Google Sheet, and sends WhatsApp alerts for matching results. It includes: Trigger node** for scheduled or webhook-based execution HTTP Request node** connected to RapidAPI for scraping Google Sheets node** to store job data Filter (IF) node** to select relevant jobs WhatsApp API node** to send alerts automatically How to set up Get an API key from RapidAPI and subscribe to an Upwork scraper API. Create a Google Sheet with columns like Title, Budget, Category, Link, and Description. Connect your Google account to n8n using Google Sheets credentials. Set up your WhatsApp API endpoint (e.g., via Waha API or WhatsApp Cloud API). Paste your API keys into the HTTP Request nodes and test the workflow. Schedule the workflow to run automatically (e.g., every hour or once daily). Requirements RapidAPI account (for Upwork scraper API) Google Sheets account WhatsApp API access (Waha / Cloud API) n8n cloud or self-hosted instance How to customize You can modify this workflow to: Track specific job categories or keywords (e.g., “automation”, “AI”, “n8n”) Send alerts to Telegram, Discord, or Slack instead of WhatsApp Add budget or client rating filters for higher-quality job leads Connect it with Airtable or Notion for advanced job tracking

AI-Powered LinkedIn Post Generator Workflow Overview This workflow is a two-part intelligent content creation system built in n8n, designed to generate professional and on-brand LinkedIn posts. It combines a conversational frontend agent that interacts naturally with users and a backend post generation engine powered by structured templates and Mistral Cloud AI models. Workflow Structure Frontend:** Conversational “LinkedIn Agent” that guides the user. Backend:** “Post Generator” engine that produces final, high-quality content using dynamic templates. LinkedIn Agent (Frontend Flow) Trigger:** When chat message received Starts the workflow whenever a user sends a message to the chatbot or embedded interface. Agent:** LinkedIn Agent Welcomes the user and lists 7 available post templates: Educational Promotional Discussion Case Study & Testimonial News Personal General Prompts the user to select a template number. Asks for a topic after the user’s choice. Sends both template number and topic to the backend using a Tool call. Memory:** Simple Memory1 Stores the last 10 messages to maintain conversational context. LLM Model:** Mistral Cloud Chat Model1 Used for reasoning, conversational responses, and user guidance. Tool Used:** template Invokes another trigger in the same workflow: When Executed by Another Workflow. Passes the user’s chosen template and topic to the backend. Post Generation Engine (Backend Flow) Trigger:** When Executed by Another Workflow Receives payload from the template tool (template ID + topic). Router Node:** Switch between templates Directs flow to the correct post template logic based on user’s choice (1–7). Example: 1 → Knowledge & Educational 2 → Promotion 3 → Discussion 4 → Case Study & Testimonial etc. Prompt Template Nodes:** Each Set node defines a large, structured prompt containing: Specific tone, audience, and purpose rules Example hooks and CTAs Layout and line formatting instructions “FORBIDDEN PHRASES” list (e.g., no “game-changer”, “revolutionary”) Expert Writer Agent:** post generator A specialized agent node that receives the selected prompt template. Generates the final LinkedIn post text using strict formatting and tone rules. Model: Mistral Cloud Chat Model Output:** The generated post text is sent back to the template tool and displayed to the user in chat. Integrations Used | Service | Purpose | Credential | |----------|----------|-------------| | Mistral Cloud | LLM & post generation | Mistral Cloud account dbt | | n8n Agent Framework | Multi-agent orchestration | Native | | Chat UI / Webhook | Frontend interaction | Custom embedded UI or webhook trigger | Agent System Prompt Summary > “You are an intelligent LinkedIn assistant that helps users craft posts. List available templates, guide them to select one, and collect a topic. Then use the provided template tool to request the backend writer to generate a final post.” Backend writer’s system prompt: > “You are an expert LinkedIn marketing leader. Generate structured, professional posts for AI/automation topics. Avoid hype, buzzwords, and clichés. Keep sentences short, tone confident, and use strong openers.” Key Features Dual-agent architecture (Frontend Assistant + Backend Writer) 7 dynamic content templates for flexibility Conversational chat interface for ease of use Strict brand tone enforcement with style run Fully automated generation and return of final post in chat Summary > A modular, agent-based n8n workflow for automated LinkedIn post creation, featuring conversational input, structured templates, and AI-generated output powered by Mistral Cloud. Perfect for content teams, social media managers, and AI automation startups. Need Help or More Workflows? Want to customize this workflow for your business. Our team at Digital Biz Tech can tailor it precisely to your use case — from automation logic to AI-powered content engines. We can help you set it up for free — from connecting credentials to deploying it live. Contact: shilpa.raju@digitalbiz.tech Website: https://www.digitalbiz.tech LinkedIn: https://www.linkedin.com/company/digital-biz-tech/ You can also DM us on LinkedIn for any help.

This n8n template implements an AI-Powered Chatbot for Automated WHMCS Support Ticket Creation Who's it for This template is designed for web hosting companies, domain registrars, and IT service providers who want to automate their customer support ticket creation process. It's perfect for businesses looking to streamline support operations by automatically converting customer chat conversations into structured WHMCS support tickets while maintaining professional, empathetic customer interactions. How it works / What it does This workflow creates an AI-powered chatbot that automatically converts customer chat messages into structured support tickets within the WHMCS system. The AI agent automatically: Receives customer queries through a webhook endpoint Processes natural language requests using Google Gemini AI Extracts key information from customer conversations: Customer name and email Issue description and subject Appropriate support department Priority level (Low, Medium, High) Fetches valid support departments from WHMCS using the GetSupportDepartments API Creates structured support tickets via WHMCS OpenTicket API Maintains conversation context with session-based memory Provides professional responses while gathering necessary information The system ensures 100% accuracy by always mapping to valid WHMCS departments and never inventing ticket fields, maintaining data integrity and proper ticket routing. How to set up 1. Configure Google Gemini API Set up your Google Gemini API credentials in the Google Gemini Chat Model node Ensure you have sufficient API quota for your expected usage 2. Configure WHMCS API Update the WHMCS API credentials in both HTTP Request Tool nodes Replace https://WHMCS_URL.com/includes/api.php with your actual WHMCS API endpoint Ensure your WHMCS API has the necessary permissions for: GetSupportDepartments action OpenTicket action 3. Customize AI Agent Behavior Modify the system message in the AI Agent node to match your company's tone and policies Adjust the agent's response style and ticket creation workflow Customize department mapping and priority assignment logic 4. Set up the Webhook The workflow creates a unique webhook endpoint for receiving customer queries Use this endpoint URL in your customer-facing chat interface Ensure proper security measures for webhook access 5. Test Department Integration Verify that the GetSupportDepartments API call returns your actual support departments Test ticket creation with various customer scenarios Ensure proper error handling for API failures Requirements Google Gemini API account** with appropriate credentials n8n instance** (self-hosted or cloud) WHMCS installation** with API access enabled Support department structure** already configured in WHMCS Customer chat interface** or messaging system How to customize the workflow Modify AI Agent Behavior Edit the system message in the AI Agent node to change the bot's personality and response style Adjust ticket creation logic and required field validation Customize priority assignment algorithms based on keywords or urgency indicators Enhance Ticket Creation Add custom fields to the ticket creation process Implement ticket categorization based on conversation content Add automatic assignment to specific support staff members Improve Customer Experience Add ticket confirmation and tracking information Implement follow-up message scheduling Add customer satisfaction surveys after ticket resolution Security Enhancements Implement API key rotation and monitoring Add request validation and sanitization Set up usage analytics and abuse prevention Key Features Automatic ticket creation** from natural language conversations Intelligent department mapping** using WHMCS API Professional customer interaction** with empathetic responses Session-based memory** for contextual conversations Structured ticket data** with proper validation Priority assignment** based on conversation analysis Scalable webhook architecture** for high-volume usage Direct WHMCS integration** for seamless ticket management Use Cases 24/7 automated support ticket creation** for web hosting companies Customer service automation** with human-like interaction Support team efficiency** by reducing manual ticket entry Consistent ticket formatting** across all customer interactions Improved response times** through immediate ticket creation Customer self-service** with professional guidance Chat Session Management The workflow automatically manages chat sessions with the following features: Unique Session IDs** for each customer conversation Automatic information extraction** from customer messages Conversation history tracking** with chronological message storage Session persistence** across multiple interactions Contextual responses** based on conversation history Example Customer Interactions The AI agent can handle various customer scenarios: Technical Issues**: "My website is down" → Creates ticket in Technical Support department Billing Questions**: "I need help with my invoice" → Creates ticket in Billing department Domain Services**: "I want to transfer my domain" → Creates ticket in Domain Services department General Support**: "I have a question about my hosting plan" → Creates ticket in General Support department Ticket Creation Process The workflow follows a structured approach: Information Gathering: The AI agent identifies missing required information (email, name, etc.) Department Selection: Fetches available departments from WHMCS and maps customer needs appropriately Priority Assessment: Determines ticket priority based on urgency indicators in the conversation Ticket Creation: Generates a well-structured ticket with clear subject and detailed message Confirmation: Provides customer with ticket creation confirmation and next steps This template transforms your web hosting business by providing instant, automated support ticket creation while maintaining the personal touch that customers expect from professional service providers. The AI agent becomes an extension of your support team, handling routine inquiries and ensuring no customer request goes unaddressed.

This n8n template implements a Customer Support Chat Agent for Web Hosting Companies with Google Gemini, Google Sheets Knowledge base and WHMCS API to Check Domain Name Availability Who's it for This template is designed for web hosting companies, domain registrars, and IT service providers who want to automate their customer support with an AI-powered chatbot. It's perfect for businesses looking to provide 24/7 customer assistance for hosting plans, domain services, and technical support while maintaining a professional, human-like interaction experience. How it works / What it does This workflow creates an AI-powered customer support chatbot that provides comprehensive assistance for web hosting and domain services. The AI agent (named Matt) automatically: Receives customer queries through a webhook endpoint Captures customer information (name and email) at the start of each session Processes natural language requests using Google Gemini AI Accesses real-time information from multiple Google Sheets knowledge bases: Shared Hosting Plans (pricing, features, specifications) Domain Prices (registration, transfer, renewal costs) Hosting Features (technical capabilities and specifications) FAQs (common questions and answers) Payment Method Details (accepted payment options) Company Offerings (available products and services) Checks domain availability via WHMCS API integration Provides accurate, contextual responses based on the knowledge base Maintains conversation history with session-based memory Stores complete chat sessions in Google Sheets for analysis and follow-up The system ensures 100% accuracy by only providing information that exists in the knowledge base, eliminating guesswork and maintaining brand consistency. How to set up 1. Configure Google Sheets Knowledge Base Set up a Google Sheets document with the following sheets: Shared_Hosting_Plans: Hosting plan details, pricing, and specifications Domain_Prices: Domain registration and renewal pricing Hosting_Features: Technical features and capabilities FAQs: Frequently asked questions and answers Payment_Method_Details: Payment options and instructions Offerings: Available products and services Update the Google Sheets credentials in each tool node 2. Set up Google Gemini API Configure your Google Gemini API credentials in the Google Gemini Chat Model node Ensure you have sufficient API quota for your expected usage 3. Configure WHMCS API (Optional) Replace Your_WHMCS_Identifier with your actual WHMCS API identifier Replace Your_WHMCS_Secret with your actual WHMCS API secret Update https://your_whmcs_url.com/includes/api.php with your WHMCS domain This enables domain availability checking for customers 4. Set up Chat Storage Create a Google Sheet for storing chat inquiries Update the document ID and credentials in the Chat_Inquiries node This will automatically store all customer conversations for analysis 5. Deploy the Webhook The workflow creates a unique webhook endpoint for receiving customer queries Use this endpoint URL in your customer-facing application or chat interface Requirements Google Sheets account** with the knowledge base set up Google Gemini API account** with appropriate credentials n8n instance** (self-hosted or cloud) WHMCS installation** (optional, for domain availability checking) Web hosting or domain services business** How to customize the workflow Modify AI Agent Behavior Edit the system message in the AI Agent node to change the bot's personality and response style Adjust response length and tone to match your brand voice Customize the agent's name (currently "Matt") Enhance Knowledge Base Add more Google Sheets tools for additional information sources Include product catalogs, pricing tables, or technical documentation Add multi-language support for international customers Improve Customer Experience Add domain suggestion algorithms based on customer input Integrate with your existing customer database for personalized recommendations Add notification systems (email, Slack, SMS) for high-value inquiries Security Enhancements Implement API key rotation and monitoring Add request validation and sanitization Set up usage analytics and abuse prevention Key Features Real-time information access** from Google Sheets knowledge base AI-powered natural language processing** for customer queries Session-based memory** for contextual conversations Automatic domain availability checking** via WHMCS API Professional, customer-focused responses** that maintain brand standards Complete chat history storage** for analysis and follow-up Scalable webhook architecture** for high-volume usage Multi-tool integration** for comprehensive customer support Use Cases 24/7 customer support automation** for web hosting companies Sales team assistance** with real-time product information Customer self-service portals** with intelligent assistance Lead generation** through proactive service recommendations Customer retention** via improved support experience Support ticket reduction** by handling common queries automatically Chat Session Management The workflow automatically manages chat sessions with the following features: Unique Session IDs** for each customer conversation Automatic customer information capture** (name and email) Conversation history tracking** with chronological message storage Session persistence** across multiple interactions Data export** to Google Sheets for analysis and follow-up Example Customer Interactions The AI agent can handle various customer scenarios: Hosting Plan Inquiries**: Detailed information about shared hosting plans, features, and pricing Domain Services**: Domain availability checking, pricing, and registration guidance Technical Support**: Feature explanations, setup guidance, and troubleshooting Payment Information**: Accepted payment methods and transaction processes General Support**: Company information, service offerings, and FAQ responses This template transforms your web hosting business by providing instant, accurate customer support while maintaining the personal touch that customers expect from professional service providers. The AI agent becomes an extension of your support team, handling routine inquiries and allowing human agents to focus on complex technical issues.

WP Category Toolkit automates mapping content topics to your WordPress category IDs using your WordPress REST API and a GPT-5mini model. It replaces manual copy-paste and guesswork when assigning categories, speeds up publishing, and reduces tagging errors so your site stays organized and search friendly without you learning new dev magic (just a bit of prompt craft). 💡 Why Use WP Category Toolkit? Saves time:** Cuts hours of manual category lookup and mapping—deploy batches of posts in minutes, not coffee breaks. Stops messy tagging:** Eliminates inconsistent category assignments so your archive and SEO behave themselves. Measurable improvement:** Expect faster publish cycles and fewer category fixes (reduce manual mapping errors by ~90%). Competitive edge:** Uses an LLM to interpret topic intent, so your categories align with content meaning, not guesswork—like having a librarian who understands your jokes. ⚡ Perfect For Content Managers:** Keep large WordPress catalogs neat without the spreadsheet gymnastics. Agencies:** Onboard client sites faster by automating taxonomy mapping across projects. Developers & Automators:** Add an LLM-powered mapping step to content pipelines without building custom classifiers. 🔧 How It Works ⏱ Trigger: Manual start (kick it off when you’re ready to map categories). 📎 Process: Pull all site categories from your WordPress REST endpoint, aggregate the list, and feed the source content + current topic into the mapping step. 🤖 Smart Logic: A Chain LLM node (Category-Mapping) uses a small prompt to decide which WordPress category IDs match the content topic (GPT5-mini handles the reasoning). 💌 Output: A clean category ID mapping you can paste into your Body Post WordPress node or use to patch posts automatically. 🔐 Quick Setup Import JSON file to your n8n instances → n8n Import Link Add credentials: WordPress API credential & Azure OpenAI (GPT5-mini) credential or you can use usual open AI node Update: Replace the WP endpoint URLand any post-body endpoints you’ll write back to Test: Run with a sample post and copy the output mapping into your Body Post WordPress node to confirm IDs match expected categories 🧩 You'll Need Active n8n instances → n8n Partner Link WordPress REST API access and credentials (wp-json access) Azure OpenAI account with access to GPT5-mini Integrations: WordPress API node, Chain LLM / Azure OpenAI node (Optional) Staging WordPress site to test mappings safely 🛠️ Level Up Ideas Auto-write category descriptions based on mapped content using the LLM. (It’ll sound smarter than your coffee.) Patch posts automatically after mapping so mapping becomes truly zero-touch. Add fallback heuristics: if the LLM is uncertain, route to a Slack/Microsoft Teams approval step. Made by: Khairul Tags: WordPress, Categories, AI, n8n Category: WordPress Need custom work? Contact me

Automatically Upload Expenses to QuickBooks from Google Sheets What It Does This n8n workflow template automates the process of uploading categorized expenses from Google Sheets into QuickBooks Online. It leverages your Google Sheets data to create expense entries in QuickBooks with minimal manual effort, streamlining the accounting process. Prerequisites QuickBooks Online Credential**: Set up your QuickBooks Online connection in n8n for expense creation. Google Sheets Credential**: Set up your Google Sheets connection in n8n to read and write data. How It Works Refresh Google Sheets Data: The workflow will first refresh the list of vendors and chart of accounts from your Google Sheets template. Import Bank Transactions: Open the provided Google Sheets template and copy-paste your transactions from your online banking CSV file. Categorize Transactions: Quickly categorize the transactions in Google Sheets, or assign this task to a team member. Run the Workflow: Once the transactions are categorized, run the workflow again, and each expense will be created automatically in QuickBooks Online. Example Use Cases Small Business Owners**: Automatically track and upload monthly expenses to QuickBooks Online without manually entering data. Accountants**: Automate the transfer of bank transactions to QuickBooks, streamlining the financial process. Bookkeepers**: Quickly categorize and upload business expenses to QuickBooks with minimal effort. Setup Instructions Connect Your Google Sheets and QuickBooks Credentials: In n8n, connect your Google Sheets and QuickBooks accounts. Follow the credential setup instructions for both services. Setup the Google Sheets Node: Link the specific Google Sheet that contains your expense data. Make sure the sheet includes the correct columns for transactions, vendors, and accounts. Setup the QuickBooks Node: Configure the QuickBooks Online node to create expense entries in QuickBooks from the data in your Google Sheets. Setup the HTTP Node for API Calls: Use the HTTP node to make custom API calls to QuickBooks Configure the QuickBooks Realm ID: Obtain the QuickBooks Realm ID from your QuickBooks Online Developer account to use for custom API calls. This ensures the workflow targets the correct QuickBooks instance. How to Use Import Transactions: Copy and paste your bank transactions from the CSV into the provided Google Sheets template. Categorize Transactions: Manually categorize the transactions in the sheet, or delegate this task to another person to ensure they’re correctly tagged (e.g., Utilities, Office Supplies, Travel). Run the Workflow: Execute the workflow to automatically upload the categorized expenses into QuickBooks. Verify in QuickBooks: After the workflow runs, log into QuickBooks Online to confirm the expenses have been created and categorized correctly. Free Google Sheets Template To get started quickly, download my free Google Sheets template that includes pre-configured sheets for bank transactions, vendors, and chart of accounts. This template will make it easier for you to import and categorize your expenses before running the n8n workflow. Download the Free Google Sheets Template Customization Options Category Mapping**: Customize how categories in Google Sheets are mapped to QuickBooks expense types. Additional API Calls**: Add custom API calls if you need extra functionality, such as creating custom reports or syncing additional data. Notifications**: Configure email or Slack notifications to alert you when the expenses have been successfully uploaded. Why It's Useful Time-Saving**: Automatically upload and categorize expenses in QuickBooks without needing to enter them manually. Error Reduction**: Minimize human error by automating the process of uploading and categorizing transactions. Efficiency**: Connects Google Sheets to QuickBooks, making it easy to manage expenses in one place without having to toggle between multiple apps. Accuracy**: Syncs data between Google Sheets and QuickBooks in a structured, automated way for consistent and reliable financial reporting. Flexibility**: Allow external users or lower-permission employees to categorize financial transactions without providing direct access to QBO

How It Works: The 5-Node Monitoring Flow This concise workflow efficiently captures, filters, and delivers crucial cybersecurity-related mentions. 1. Monitor: Cybersecurity Keywords (X/Twitter Trigger) This is the entry point of your workflow. It actively searches X (formerly Twitter) for tweets containing the specific keywords you define. Function:** Continuously polls X for tweets that match your specified queries (e.g., your company name, "Log4j," "CVE-2024-XXXX," "ransomware"). Process:** As soon as a matching tweet is found, it triggers the workflow to begin processing that information. 2. Format Notification (Code Node) This node prepares the raw tweet data, transforming it into a clean, actionable message for your alerts. Function:** Extracts key details from the raw tweet and structures them into a clear, concise message. Process:** It pulls out the tweet's text, the user's handle (@screen_name), and the direct URL to the tweet. These pieces are then combined into a user-friendly notificationMessage. You can also include basic filtering logic here if needed. 3. Valid Mention? (If Node) This node acts as a quick filter to help reduce noise and prevent irrelevant alerts from reaching your team. Function:** Serves as a simple conditional check to validate the mention's relevance. Process:** It evaluates the notificationMessage against specific criteria (e.g., ensuring it doesn't contain common spam words like "bot"). If the mention passes this basic validation, the workflow continues. Otherwise, it quietly ends for that particular tweet. 4. Send Notification (Slack Node) This is the delivery mechanism for your alerts, ensuring your team receives instant, visible notifications. Function:** Delivers the formatted alert message directly to your designated communication channel. Process:* The notificationMessage is sent straight to your specified *Slack channel** (e.g., #cyber-alerts or #security-ops). 5. End Workflow (No-Op Node) This node simply marks the successful completion of the workflow's execution path. Function:** Indicates the end of the workflow's process for a given trigger. How to Set Up Implementing this simple cybersecurity monitor in your n8n instance is quick and straightforward. 1. Prepare Your Credentials Before building the workflow, ensure all necessary accounts are set up and their respective credentials are ready for n8n. X (Twitter) API:* You'll need an X (Twitter) developer account to create an application and obtain your Consumer Key/Secret and Access Token/Secret. Use these to set up your *Twitter credential** in n8n. Slack API:* Set up your *Slack credential* in n8n. You'll also need the *Channel ID** of the Slack channel where you want your security alerts to be posted (e.g., #security-alerts or #it-ops). 2. Import the Workflow JSON Get the workflow structure into your n8n instance. Import:** In your n8n instance, go to the "Workflows" section. Click the "New" or "+" icon, then select "Import from JSON." Paste the provided JSON code (from the previous response) into the import dialog and import the workflow. 3. Configure the Nodes Customize the imported workflow to fit your specific monitoring needs. Monitor: Cybersecurity Keywords (X/Twitter):** Click on this node. Select your newly created Twitter Credential. CRITICAL: Modify the "Query" parameter to include your specific brand names, relevant CVEs, or general cybersecurity terms. For example: "YourCompany" OR "CVE-2024-1234" OR "phishing alert". Use OR to combine multiple terms. Send Notification (Slack):** Click on this node. Select your Slack Credential. Replace "YOUR_SLACK_CHANNEL_ID" with the actual Channel ID you noted earlier for your security alerts. (Optional: You can adjust the "Valid Mention?" node's condition if you find specific patterns of false positives in your search results that you want to filter out.) 4. Test and Activate Verify that your workflow is working correctly before setting it live. Manual Test:** Click the "Test Workflow" button (usually in the top right corner of the n8n editor). This will execute the workflow once. Verify Output:** Check your specified Slack channel to confirm that any detected mentions are sent as notifications in the correct format. If no matching tweets are found, you won't see a notification, which is expected. Activate:** Once you're satisfied with the test results, toggle the "Active" switch (usually in the top right corner of the editor) to ON. Your workflow will now automatically monitor X (Twitter) at the specified polling interval.

📄 What this workflow does This workflow turns your n8n into an automated product-video generator powered by Google Sheets. When a new row is added with status = run, it: Downloads the product image from Google Drive. Converts the image to base64 and sends it to Gemini, which creates a branded ad-style variant. Saves the generated image back into a designated Google Drive folder. Sends the image to FAL (image-to-video) to generate a short promotional video clip. Polls FAL’s response_url until the video is ready. Uploads the video to Google Drive (videos folder). Updates the original Google Sheet row with the video link and sets status = finished. Handles API latency via wait/polling and logs failures into the sheet if needed. 👤 Who is this for Marketing teams automating creative asset production. E-commerce businesses needing quick product promo videos. Agencies creating branded ad content at scale. ✅ Requirements An n8n instance. A Google Sheet with at least these columns: STT, link_image, note, status, link_video. Google Sheets & Google Drive OAuth2 credentials connected in n8n. Gemini API key (for ad-style image generation). FAL API key (for image-to-video). ⚙️ How to set up Import the provided workflow JSON into n8n. Connect Google Sheets credentials and point to your sheet (documentId + gid). Connect Google Drive credentials and update folder IDs in the two Upload File nodes (images/videos). Add Gemini and FAL API keys in the respective HTTP Request headers (via Credentials). Test: add a row with link_image, note, and status = run. The workflow should generate and save a video, then update the sheet with the link. 🔁 How it works Trigger → Google Sheets Trigger fires on rowAdded where status = run. Pre-processing → Download the product image from Google Drive → extract base64. LLM Image Generation → Gemini generates an ad-style variant based on note. Storage → Upload the generated image into the “images” Drive folder. Video Creation → FAL converts the branded image into a short video. Polling → Wait node + HTTP Request check job status until video is completed. Write-back → Upload final video into the “videos” Drive folder, update the sheet with the link_video, and set status = finished.

How it works This workflow automates LinkedIn community engagement by monitoring post comments, filtering new ones, generating AI-powered replies, and posting responses directly on LinkedIn. It also logs all interactions into Google Sheets for tracking and analytics. Step-by-step Trigger & Fetch A Schedule Trigger runs the workflow every 10 minutes. The workflow fetches the latest comments on a specific LinkedIn post using LinkedIn’s API with token-based authentication. Filter for New Comments Retrieves the timestamp of the last processed comment from Google Sheets. Filters out previously handled comments, ensuring only fresh interactions are processed. AI-Powered Reply Generation Sends the new comment to OpenAI GPT-3.5 Turbo with a structured prompt. AI generates a professional, concise, and engaging LinkedIn-appropriate reply (max 2–3 sentences). Post Back to LinkedIn Automatically posts the AI-generated reply under the original comment thread. Maintains consistent formatting and actor identity. Data Logging Appends the original comment, AI response, and metadata into Google Sheets. Enables tracking, review, and future engagement analysis. Benefits Saves time by automating LinkedIn comment replies. Ensures responses are timely, professional, and on-brand. Maintains authentic engagement without manual effort. Prevents duplicate replies by filtering with timestamps. Creates a structured log in Google Sheets for auditing and analytics.