Workflow Templates

This workflow enables users to perform web searches directly from Telegram using the Brave search engine. By simply sending the command /brave followed by a query, the workflow retrieves search results from Brave and returns them as a Telegram message. This workflow is ideal for users who want a quick and private way to search the web without switching between apps. 🚀 This workflow is a powerful tool for automating interactions with Brave tools through Telegram, providing users with quick and easy access to information directly in their chat. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to process user queries from Telegram, execute a Brave tool via the MCP Client, and send the results back to the user. Here's how it works: Telegram Trigger: The workflow starts with the Telegram Trigger node, which listens for new messages in a Telegram chat. When a message is received, the workflow checks if it starts with the command /brave. Filter Messages: The If node filters messages that start with /brave. If the message doesn't start with /brave, the workflow stops. Edit Fields: The Edit Fields node extracts the text of the message for further processing. Clean Query: The Clean Query node removes the /brave command from the message, leaving only the user's query. List Brave Tools: The List Brave Tools node retrieves the list of available tools from the MCP Client. Execute Brave Tool: The Exec Brave Tool node executes the first tool in the list using the cleaned query as input. Send Message: The Send Message node sends the result of the Brave tool execution back to the user in the Telegram chat. 2. Preliminary Steps Access to an n8n self-hosted instance and install the Community node "n8n-nodes-mcp". Please see this easy guide Get your Brave Search API Key: https://brave.com/search/api/ Telegram Bot Access Token In "List Brave Tools" create new credential as shown in this image In Environment field set this value: BRAVE_API_KEY=your-api-key 3. Set Up Steps To set up and use this workflow in n8n, follow these steps: Telegram Configuration: Set up Telegram credentials in n8n for the Telegram Trigger and Send Message nodes. Ensure the Telegram bot is authorized to read messages and send responses in the chat. MCP Client Configuration: Set up MCP Client credentials in n8n for the List Brave Tools and Exec Brave Tool nodes. Ensure the MCP Client is configured to interact with Brave tools. Test the Workflow: Send a message starting with /brave followed by a query (e.g., /brave search for AI tools) to the Telegram chat. The workflow will: Process the query. Execute the Brave tool via the MCP Client. Send the result back to the Telegram chat. Optional Customization: Modify the workflow to include additional features, such as: Adding more commands or tools. Integrating with other APIs or services for advanced use cases. Sending notifications via other channels (e.g., email, Slack) Need help customizing? Contact me for consulting and support or add me on Linkedin.

📄 Convert Parquet, Feather, ORC & Avro Files with ParquetReader This workflow allows you to upload and inspect Parquet, Feather, ORC, or Avro files via the ParquetReader API. It instantly returns a structured JSON preview of your data — including rows, schema, and metadata — without needing to write any custom code. ✅ Perfect For Validating schema and structure before syncing or transformation Previewing raw columnar files on the fly Automating QA, ETL, or CI/CD workflows Converting Parquet, Avro, Feather, or ORC to JSON ⚙️ Use Cases Catch schema mismatches before pipeline runs Automate column audits in incoming data files Enrich metadata catalogs with real-time schema detection Integrate file validation into automated workflows 🚀 How to Use This Workflow 📥 Trigger via File Upload You can trigger this flow by sending a POST request with a file using curl, Postman, or from another n8n flow. 🔧 Example (via curl): curl -X POST http://localhost:5678/webhook-test/convert \ -F "file=@converted.parquet" > Replace converted.parquet with your local file path. You can also send Avro, ORC or Feather files. 🔁 Reuse from Other Flows You can reuse this flow by calling the webhook from another n8n workflow using an HTTP Request node. Make sure to send the file as form-data with the field name file. 🔍 What This Flow Does: Receives the uploaded file via webhook (file) Sends it to https://api.parquetreader.com/parquet as multipart/form-data (field name: file) Receives parsed data (rows), schema, and metadata in JSON format 🧪 Example JSON Response from this flow { "data": [ { "full_name": "Pamela Cabrera", "email": "bobbyharrison@example.net", "age": "24", "active": "True", "latitude": "-36.1577385", "longitude": "63.014954", "company": "Carter, Shaw and Parks", "country": "Honduras" } ], "meta_data": { "created_by": "pyarrow", "num_columns": 21, "num_rows": 10, "serialized_size": 7598, "format_version": "0.12" }, "schema": [ { "column_name": "full_name", "column_type": "string" }, { "column_name": "email", "column_type": "string" }, { "column_name": "age", "column_type": "int64" }, { "column_name": "active", "column_type": "bool" }, { "column_name": "latitude", "column_type": "double" }, { "column_name": "longitude", "column_type": "double" }, { "column_name": "company", "column_type": "string" }, { "column_name": "country", "column_type": "string" } ] } 🔐 API Info Authentication: None required Supported formats: .parquet, .avro, .orc, .feather Free usage: No signup needed; API is currently open to the public Limits: Usage and file size limits may apply in the future (TBD)

About The Airtop Automation Are you tired of being shocked by unexpectedly high energy bills? With this automation using Airtop and n8n, you can take control of your daily energy costs and ensure you’re always informed. How to monitor your daily energy consumption With this automation, we’ll walk you through setting up an automation that retrieves your PG&E (Pacific Gas and Electric) energy usage data, calculates costs, and emails you the details—all without manual effort. What You’ll Need To get started, make sure you have the following: A free Airtop API Key PG&E Account Credentials - with minor adaptations, this will also work with other providers An Email Address - To receive the energy cost updates Estimated setup time: 5 minutes Understanding the Process This automation works by: Logging into your PG&E account using your credentials Navigating to your energy usage data Extracting relevant details about energy consumption and costs Emailing the daily summary directly to your inbox The automation is straightforward and ensures you have real-time insights into your energy usage, empowering you to adjust your habits and save money. Setting Up Your Automation We’ve created a step-by-step guide to help you set up this workflow. Here’s how: Insert Your Credentials: In the tools section, add your PG&E login details as variables In Airtop, add your Airtop API Key Configure your email address to receive the updates Run the Automation: Start the scenario, and watch as the automation retrieves your energy data and sends you a detailed email summary. Customization Options While the default setup works seamlessly, you can tweak it to suit your needs: Data Storage: Store energy usage data in a database for long-term tracking and analysis Visualization: Plot graphs of your energy usage trends over time for better insights Notifications: Change the automation to only send alerts on high usage instead of a daily email Real-World Applications This automation isn’t just about monitoring energy usage and taking control. Here are some practical applications: Daily Energy Management: Receive updates every morning and adjust your energy consumption based on costs Smart Home Integration: Use the data to automate appliances during off-peak hours Budgeting: Track energy expenses over weeks or months to plan your budget more effectively Happy automating!

Tags: Automation, AI, Marketing, Content Creation Context I’m a Supply Chain Data Scientist and content creator who writes regularly about data-driven optimization, logistics, and sustainability. Promoting blog articles on LinkedIn used to be a manual task — until I decided to automate it with N8N and GPT-4o. This workflow lets you automatically extract blog posts, clean the content, and generate a professional LinkedIn post using an AI Agent powered by GPT-4o — all in one seamless automation. >Save hours of repetitive work and boost your reach with AI. 📬 For business inquiries, you can add me on LinkedIn Who is this template for? This template is perfect for: Bloggers and writers** who want to promote their content on LinkedIn Marketing teams** looking to automate professional post-generation Content creators** using Ghost platforms It generates polished LinkedIn posts with: A hook A quick summary A call-to-action A signature to drive readers to your contact page How does it work? This workflow runs in N8N and performs the following steps: 🚀 Triggers manually or you can add a scheduler 📰 Pulls recent blog posts from your Ghost site (via API) 🧼 Cleans the HTML content for AI input 🤖 Sends content to GPT-4o with a tailored prompt to create a LinkedIn post 📄 Records all data (post content + LinkedIn output) in a Google Sheet What do I need to start? You don’t need to write a single line of code. Prerequisites: A Ghost CMS account with blog content A Google Sheet to store generated posts An OpenAI API Key Google Sheets API** connected via OAuth2 Next Steps Use the sticky notes in the workflow to understand how to: Add your Ghost API credentials Link your Google Sheet Customize the AI prompt (e.g., change the author name or tone) Optionally add auto-posting to LinkedIn using tools like Buffer or Make 🎥 Watch My Tutorial 🚀 Want to explore how automation can scale your brand or business? 📬 Let’s connect on LinkedIn Notes You can adapt this template for Twitter, Facebook, or even email newsletters by adjusting the prompt and output channel. This workflow was built using n8n 1.85.4 Submitted: April 9th, 2025

LinkedIn Hiring Signal Scraper — Jobs & Prospecting Using Bright Data Purpose: Discover recent job posts from LinkedIn using Bright Data's Dataset API, clean the results, and log them into Google Sheets — for both job hunting and identifying high-intent B2B leads based on hiring activity. Use Cases: Job Seekers** – Spot relevant openings filtered by role, city, and country. Sales & Prospecting** – Use job posts as buying signals. If a company is hiring for a role you support (e.g. marketers, developers, ops) — it's the perfect time to reach out and offer your services. Tools Needed: n8n Nodes:** Form Trigger HTTP Request Wait If Code Google Sheets Sticky Notes (for embedded guidance) External Services:** Bright Data (Dataset API) Google Sheets API Keys & Authentication Required: Bright Data API Key** → Add in the HTTP Request headers: Authorization: Bearer YOUR_BRIGHTDATA_API_KEY Google Sheets OAuth2** → Connect your account in n8n to allow read/write access to the spreadsheet. General Guidelines: Use descriptive names for all nodes. Include retry logic in polling to avoid infinite loops. Flatten nested fields (like job_poster and base_salary). Strip out HTML tags from job descriptions for clean output. Things to be Aware Of: Bright Data snapshots take ~1–3 minutes — use a Wait node and polling. Form filters affect output significantly: 🔍 We recommend filtering by "Last 7 days" or "Past 24 hours" for fresher data. Avoid hardcoding values in the form — leave optional filters empty if unsure. Post-Processing & Outreach: After data lands in Google Sheets, you can use it to: Personalize cold emails based on job titles, locations, and hiring signals. Send thoughtful LinkedIn messages (e.g., "Saw you're hiring a CMO...") Prioritize outreach to companies actively growing in your niche. Additional Notes: 📄 Copy the Google Sheet Template: Click here to make your copy → Rename for each campaign or client. Form fields include: Job Location (city or region) Keyword (e.g., CMO, Backend Developer) Country (2-letter code, e.g., US, UK) This workflow gives you a competitive edge — 📌 For candidates: Be first to apply. 📌 For sellers: Be first to pitch. All based on live hiring signals from LinkedIn. STEP-BY-STEP WALKTHROUGH Step 1: Set up your Google Sheet Open this template Go to File → Make a copy You'll use this copy as the destination for the scraped job posts Step 2: Fill out the Input Form in n8n The form allows you to define what kind of job posts you want to scrape. Fields: Job Location** → e.g. New York, Berlin, Remote Keyword** → e.g. CMO, AI Architect, Ecommerce Manager Country Code (2-letter)** → e.g. US, UK, IL 💡 Pro Tip: For best results, set the filter inside the workflow to: time_range = "Past 24 hours" or "Last 7 days" This keeps results relevant and fresh. Step 3: Trigger Bright Data Snapshot The workflow sends a request to Bright Data with your input. Example API Call Body: [ { "location": "New York", "keyword": "Marketing Manager", "country": "US", "time_range": "Past 24 hours", "job_type": "Part-time", "experience_level": "", "remote": "", "company": "" } ] Bright Data will start preparing the dataset in the background. Step 4: Wait for the Snapshot to Complete The workflow includes a Wait Node and Polling Loop that checks every few minutes until the data is ready. You don't need to do anything here — it's all automated. Step 5: Clean Up the Results Once Bright Data responds with the full job post list: ✔️ Nested fields like job_poster and base_salary are flattened ✔️ HTML in job descriptions is removed ✔️ Final data is formatted for export Step 6: Export to Google Sheets The final cleaned list is added to your Google Sheet (first tab). Each row = one job post, with columns like: job_title, company_name, location, salary_min, apply_link, job_description_plain Step 7: Use the Data for Outreach or Research Example for Job Seekers: You search for: Location: Berlin Keyword: Product Designer Country: DE Time range: Past 7 days Now you've got a live list of roles — with salary, recruiter info, and apply links. → Use it to apply faster than others. Example for Prospecting (Sales / SDR): You search for: Location: London Keyword: Growth Marketing Country: UK And find companies hiring growth marketers. → That's your signal to offer help with media buying, SEO, CRO, or your relevant service. Use the data to: Write personalized cold emails ("Saw you're hiring a Growth Marketer…") Start warm LinkedIn outreach Build lead lists of companies actively expanding in your niche API Credentials Required: Bright Data API Key** Used in HTTP headers: Authorization: Bearer YOUR_BRIGHTDATA_API_KEY Google Sheets OAuth2** Allows n8n to read/write to your spreadsheet Adjustments & Customization Tips: Modify the HTTP Request body to add more filters (e.g. job_type, remote, company) Increase or reduce polling wait time depending on Bright Data speed Add scoring logic to prioritize listings based on title or location Final Notes: 📄 Google Sheet Template: Make your copy here ⚙️ Bright Data Dataset API: Visit BrightData.com 📬 Personalization works best when you act quickly. Use the freshest data to reach out with context — not generic pitches. This workflow turns LinkedIn job posts into sales insights and job leads. All in one click. Fully automated. Ready for your next move.

The purpose of this n8n workflow is to automate the process of identifying incoming Gmail emails that are requesting an appointment, evaluating their content, checking calendar availability, and then composing and sending a response email. Note that to use this template, you need to be on n8n version 1.19.4 or later.

Detailed Title "Triathlon Coach AI Workflow: Strava Data Analysis and Personalized Training Insights using n8n" Description This n8n workflow enables you to build an AI-driven virtual triathlon coach that seamlessly integrates with Strava to analyze activity data and provide athletes with actionable training insights. The workflow processes data from activities like swimming, cycling, and running, delivers personalized feedback, and sends motivational and performance improvement advice via email or WhatsApp. Workflow Details Trigger: Strava Activity Updates Node:** Strava Trigger Purpose:** Captures updates from Strava whenever an activity is recorded or modified. The data includes metrics like distance, pace, elevation, heart rate, and more. Integration:** Uses Strava API for real-time synchronization. Step 1: Data Preprocessing Node:** Code Purpose:** Combines and flattens the raw Strava activity data into a structured format for easier processing in subsequent nodes. Logic:** A recursive function flattens JSON input to create a clean and readable structure. Step 2: AI Analysis with Google Gemini Node:** Google Gemini Chat Model Purpose:** Leverages Google Gemini's advanced language model to analyze the activity data. Functionality:** Identifies key performance metrics. Provides feedback and insights specific to the type of activity (e.g., running, swimming, or cycling). Offers tailored recommendations and motivational advice. Step 3: Generate Structured Output Node:** Structure Output Purpose:** Processes the AI-generated response to create a structured format, such as headings, paragraphs, and bullet lists. Output:** Formats the response for clear communication. Step 4: Convert to HTML Node:** Convert to HTML Purpose:** Converts the structured output into an HTML format suitable for email or other presentation methods. Output:** Ensures the response is visually appealing and easy to understand. Step 5: Send Email with Training Insights Node:** Send Email Purpose:** Sends a detailed email to the athlete with performance insights, training recommendations, and motivational messages. Integration:** Utilizes Gmail or SMTP for secure and efficient email delivery. Optional Step: WhatsApp Notifications Node:** WhatsApp Business Cloud Purpose:** Sends a summary of the activity analysis and key recommendations via WhatsApp for instant access. Integration:** Connects to WhatsApp Business Cloud for automated messaging. Additional Notes Customization: You can modify the AI prompt to adapt the recommendations to the athlete's specific goals or fitness levels. The workflow is flexible and can accommodate additional nodes for more advanced analysis or output formats. Scalability: Ideal for individual athletes or coaches managing multiple athletes. Can be expanded to include additional metrics or insights based on user preferences. Performance Metrics Handled: Swimming: SWOLF, stroke count, pace. Cycling: Cadence, power zones, elevation. Running: Pacing, stride length, heart rate zones. Implementation Steps Set Up Strava API Key: Log in to Strava Developers to generate your API key. Integrate the API key into the Strava Trigger node. Configure Google Gemini Integration: Use your Google Gemini (PaLM) API credentials in the Google Gemini Chat Model node. Customize Email and WhatsApp Messaging: Update the Send Email and WhatsApp Business Cloud nodes with the recipient’s details. Automate Execution: Deploy the workflow and use n8n's scheduling features or cron jobs for periodic execution. GET n8n Now N8N COURSE n8n Book Developer Notes Author:** Amjid Ali improvements. Resources:** See in Action: Syncbricks Youtube PayPal: Support the Developer Courses : SyncBricks LMS By using this workflow, triathletes and coaches can elevate training to the next level with AI-powered insights and actionable recommendations.

AI Customer-Support Assistant that auto-maps any business site, answers WhatsApp in real time, and lets you earn or save thousands by replacing pricey SaaS chat tools. ⚡ What the workflow does Live “AI employee”* - the bot crawls pages on demand (products, policies, FAQs) so you *never** upload documents or fine-tune a model. No-code setup** - Drop in API keys, paste your domain, publish the webhook—ready in \~15 min. Chat memory** - each conversation turn is written to Supabase/Postgres and automatically replayed into the next prompt, letting the assistant remember context so follow-up questions feel natural and coherent even across long sessions. WhatsApp ready** - Free-form replies inside the 24-hour service window, automatically switches to a template when required (recommended by Meta). 🚀 Why you’ll love it | Benefit | Impact | | ------------------------- | --------------------------------------------------------------------- | | Zero content training | Point the AI Agent at any domain → go live. | | Save or earn money | Replace pricey SaaS chat tools or sell white-label bots to clients. | | Channel-agnostic | Ships with WhatsApp; swap one node for Telegram, Slack, or web chat. | | Flexible voice | Adjust tone & language by editing one prompt line. | 🧰 Prerequisites (all free-tier friendly) OpenAI key Meta WhatsApp Cloud API number + permanent token (easy setup) Supabase (or Postgres) URL for chat memory (easy setup) 🛠 5-step setup Import the template into n8n. Add credentials for OpenAI, WhatsApp, and Supabase. Enter your root domain in the root\_url variable. Point Meta’s Webhook to the n8n URL. Hit Execute Trigger and send “Hi” from WhatsApp—watch the bot answer with live data. 🔄 Easy to extend Voice & language** – change wording in the System Prompt. Escalation** – add an “If fallback” branch → Zendesk, email, live agents. Extra channels** – duplicate the reply node for Telegram or Slack. Commerce API hooks** – plug in Shopify, Woo, Stripe for order status or payments. 💡 Monetization ideas Replace costly SaaS seats.* Deploy the bot on your own server and *stop paying \$300–\$500 every month for third-party “AI support” platforms. Sell it as a service.* Spin up a branded instance for local shops, clinics, or e-commerce stores and *charge each client \$300–\$500 per month**—setup time is under 15 minutes. Upsell premium coverage (24/7 human hand-off) once the bot handles routine questions. Embed product links in answers and earn affiliate or upsell revenue automatically. Spin it up, connect a domain and a phone number, and you—or your customers—get enterprise-grade support without code, training, or ongoing licence fees.

🎯 Project Purpose This project automates the process of collecting and managing new leads submitted through a web form. It eliminates the need for manual data entry and ensures that each lead is: Properly recorded and time-stamped in a structured format Automatically communicated to the sales or support team Ready for follow-up, with a reminder system in place It’s a lightweight but effective solution suitable for freelancers, small teams, and growing businesses that want to streamline their lead intake process. 🛠️ Tools & Technologies Used Google Forms / Web Form** – Frontend for capturing leads Google Sheets** – Central database for storing lead information n8n** – Automation platform that connects and coordinates all services Gmail** – Handles email notifications for new leads Slack* *(optional) – Provides instant team notifications Date & Time nodes** – Tracks and manages lead response timing Conditional (IF) nodes** – Filters out duplicate and incomplete entries 🔄 Workflow Overview ✨ Key Features ✅ No-code integration using n8n ✅ Instant alerts via Gmail and/or Slack ✅ Google Sheets as an easily accessible backend ✅ Modular design — easy to expand with CRM tools (like HubSpot) ✅ Clean JSON structure and logic, beginner-friendly 📈 Possible Improvements Add email validation via external API (e.g., NeverBounce, Hunter) Integrate with a CRM for deeper automation Add lead scoring based on answers Include automatic follow-up emails after X days Schedule weekly summary reports via email 🧑🏻‍💻 Creator Information Developed by: Adem Tasin Adem T. 🌐 Website: Dataplusminus+- 📧 Email:dataplusminuss@gmail.com 💼 LinkedIn: Adem Tasin

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This automated n8n workflow streamlines the process of screening CVs and validating candidate information using AI and email parsing. The system listens for new emails with CV attachments, extracts and processes the data, and either saves valid CVs to a target directory or notifies HR of invalid submissions. Good to Know The workflow improves efficiency by automating CV screening and validation. Ensures only CVs with essential fields (e.g., name, email, skills) are processed further. Email notifications alert HR to incomplete or invalid CVs for timely follow-up. The system pauses until all CV data is fully loaded to avoid processing errors. How It Works Trigger on New CV Email - Detects new emails with CV attachments. Extract Text from PDF CV - Parses content from attached PDF files. Ensure All CV Data Loaded - Waits until all data is ready for processing. Parse & Structure CV Information - Extracts structured details like name, skills, and experience using AI or custom logic. Check CV for Required Fields - Verifies the presence of essential fields (e.g., name, email, skills). Save Valid CV to Folder - Stores successfully validated CVs into a target directory. Notify HR of Invalid CV - Sends an email alert for incomplete or invalid CVs. Data Sources The workflow processes data from email attachments: CV PDF Files** - Contains candidate information in PDF format. How to Use Import the workflow into n8n. Configure email account credentials for monitoring new CV emails. Set up a target directory for storing validated CVs. Test with sample CV PDFs to verify extraction and validation. Adjust AI or custom logic based on specific required fields. Monitor email notifications for invalid CVs and refine the process as needed. Requirements Email account access with IMAP/POP3 support. PDF parsing capabilities (e.g., OCR or text extraction tools). AI or custom logic for data extraction and validation. A target directory for storing validated CVs. Customizing This Workflow Modify the "Check CV for Required Fields" node to include additional required fields (e.g., education, certifications). Adjust the email notification format to include more details about invalid CVs. Integrate with HR software for seamless candidate tracking. Details The workflow ensures efficient CV screening by automating repetitive tasks. Notifications help maintain a high-quality candidate pool by addressing issues early.

This workflow provides automated access to the Fire Part Crafter AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for image generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete image generation process using the Fire Part Crafter model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: PartCrafter is a structured 3D mesh generation model that creates multiple parts and objects from a single RGB image. Key Capabilities High-quality image generation from text prompts** Advanced AI-powered visual content creation** Customizable image parameters and styles** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Fire/part-crafter AI model Fire Part Crafter**: The core AI model for image generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Image Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Creation**: Generate unique images for blogs, social media, and marketing materials Design Prototyping**: Create visual concepts and mockups for design projects Art & Creativity**: Produce artistic images for personal or commercial use Marketing Materials**: Generate eye-catching visuals for campaigns and advertisements Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #imagegeneration #aiart #texttoimage #visualcontent #aiimages #generativeart #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

Stop manually checking keyword rankings and let automation do the work for you. This comprehensive SEO monitoring workflow automatically tracks your keyword positions, compares them against your target URLs, and instantly alerts your team via Slack whenever rankings change - ensuring you never miss critical SEO movements. ✨ What This Workflow Does: 📊 Automated Rank Checking**: Continuously monitors keywords stored in Airtable 🔍 Real-Time SERP Analysis**: Uses Firecrawl API to fetch current search rankings 📈 Intelligent Comparison**: Compares current vs. previous rankings automatically 📝 Database Updates**: Updates Airtable records with new ranking data 🚨 Instant Alerts**: Sends Slack notifications only when rankings change 🎯 Target URL Matching**: Specifically tracks your domain's position in search results 🔧 Key Features: Trigger-based automation** that activates when Airtable data changes Smart rank comparison** logic that prevents false alerts Conditional notifications** - only alerts on actual ranking changes Clean data management** with automatic Airtable updates Team collaboration** through Slack integration Scalable monitoring** for unlimited keywords 📋 Prerequisites: Airtable account with Personal Access Token Firecrawl API key for SERP data Slack workspace with API access Basic Airtable setup with keyword data 🎯 Perfect For: SEO agencies managing multiple client campaigns Digital marketing teams tracking organic performance Content creators monitoring content rankings E-commerce businesses tracking product visibility Startups needing cost-effective SEO monitoring Any business serious about search visibility 💡 How It Works: Data Collection: Fetches keywords, target URLs, and current ranks from Airtable SERP Analysis: Queries Firecrawl API for real-time search results Rank Detection: Searches results for your target URL and determines position Smart Comparison: Compares new ranking against stored data Database Update: Updates Airtable with latest ranking information Conditional Alert: Sends Slack notification only if ranking changed Team Notification: Delivers actionable ranking updates to your team 📦 What You Get: Complete n8n workflow with all integrations configured Airtable template with proper field structure Firecrawl API integration setup Slack notification templates Comprehensive setup documentation Sample keyword data for testing 🚀 Benefits: Save Hours Weekly**: Eliminate manual rank checking Never Miss Changes**: Get instant alerts on ranking movements Team Alignment**: Keep everyone informed via Slack Historical Tracking**: Maintain ranking history in Airtable Cost Effective**: Replace expensive SEO tools with automation Scalable Solution**: Monitor unlimited keywords effortlessly 💡 Need Help or Want to Learn More? Created by Yaron Been 📧 Support: Yaron@nofluff.online 🎥 YouTube Tutorials: https://www.youtube.com/@YaronBeen/videos 💼 LinkedIn: https://www.linkedin.com/in/yaronbeen/ Discover more SEO automation workflows and digital marketing tutorials on my channels! 🏷️ Tags: SEO, Keyword Tracking, Airtable, Slack, Firecrawl, SERP, Automation, Rank Monitoring, Digital Marketing, Search Rankings