by Yaron Been
Comprehensive SEO Strategy with O3 Director & GPT-4 Specialist Team Trigger When chat message received → User submits an SEO request (e.g., “Help me rank for project management software”). The message goes straight to the SEO Director Agent. SEO Director Agent (O3) Acts like the head of SEO strategy. Uses the Think node to plan and decide which specialists to call. Delegates tasks to relevant agents. Specialist Agents (GPT-4.1-mini) Each agent has its own OpenAI model connection for lightweight cost-efficient execution. Tasks include: Keyword Research Specialist → Keyword discovery, clustering, competitor analysis. SEO Content Writer → Generates optimized blog posts, landing pages, etc. Technical SEO Specialist → Site audit, schema markup, crawling fixes. Link Building Strategist → Backlink strategies, outreach campaign ideas. Local SEO Specialist → Local citations, GMB optimization, geo-content. Analytics Specialist → Reports, performance insights, ranking metrics. Feedback Loop Each agent sends results back to the SEO Director. Director compiles insights into a comprehensive SEO campaign plan. ✅ Why This Setup Works Well O3 Model for Director** → Handles reasoning-heavy orchestration (strategy, delegation). GPT-4.1-mini for Specialists** → Cheap, fast, task-specific execution. Parallel Execution** → All specialists can run at the same time. Scalable & Modular** → You can add/remove agents depending on campaign needs. Sticky Notes** → Already document the workflow (great for onboarding & sharing).
by Oneclick AI Squad
This automated n8n workflow checks daily travel itineraries, syncs upcoming trips to Google Calendar, and sends reminder notifications to travelers via email or SMS. Perfect for travel agencies, tour operators, and organizations managing group trips to keep travelers informed about their schedules and bookings. What This Workflow Does Automatically checks travel itineraries every day Identifies today's trips and upcoming departures Syncs trip information to Google Calendar Sends personalized reminders to assigned travelers Tracks reminder delivery status and logs activities Handles both email and SMS notification preferences Provides pre-travel checklists and booking confirmations Manages multi-day trip schedules and activities Main Components Daily Travel Check** - Triggers daily to check travel itineraries Read Travel Itinerary** - Retrieves today's trips and bookings from database/Excel Filter Today's Trips** - Identifies trips departing today and upcoming activities Has Trips Today?** - Checks if there are any trips scheduled Read Traveler Contacts** - Gets traveler contact information for assigned trips Sync to Google Calendar** - Creates/updates trip events in Google Calendar Create Traveler Reminders** - Generates personalized reminder messages with travel details Split Into Batches** - Processes reminders in manageable batches Email or SMS?** - Routes based on traveler communication preferences Prepare Email Reminders** - Creates detailed email reminder content with checklists Prepare SMS Reminders** - Creates SMS reminder content optimized for text Read Reminder Log** - Checks previous reminder history Update Reminder Log** - Records sent reminders with timestamps Save Reminder Log** - Saves updated log data for audit trail Essential Prerequisites Travel itinerary database/Excel file with trip assignments Traveler contact database with email and phone numbers Google Calendar API access and credentials SMTP server for email notifications SMS service provider (Twilio, Nexmo, etc.) for text reminders Reminder log file for tracking sent notifications Booking confirmation system (flight, hotel, transport) Required Data Files trip_itinerary.xlsx: Trip ID | Trip Name | Date | Departure Time | Duration Departure Location | Destination | Hotel | Flight Number Assigned Travelers | Status | Booking Reference | Cost traveler_contacts.xlsx: Traveler ID | First Name | Last Name | Email | Phone Preferred Contact | Assigned Trips | Passport Number | Emergency Contact reminder_log.xlsx: Log ID | Date | Traveler ID | Trip ID | Contact Method Status | Sent Time | Message Preview | Confirmation Key Features ⏰ Daily Automation: Runs automatically every day at scheduled times 📅 Calendar Sync: Syncs trips to Google Calendar for easy viewing 📧 Smart Reminders: Sends email or SMS based on traveler preference 👥 Batch Processing: Handles multiple travelers efficiently 📊 Activity Logging: Tracks all reminder activities and delivery status 🔄 Duplicate Prevention: Avoids sending multiple reminders 📱 Multi-Channel: Supports both email and SMS notifications ✈️ Travel-Specific: Includes flight numbers, locations, accommodation details 📋 Pre-Travel Checklist: Provides comprehensive packing and document reminders 🌍 Multi-Destination: Manages complex multi-stop itineraries Quick Setup Import workflow JSON into n8n Configure daily trigger schedule (recommended: 6 AM and 6 PM) Set up trip itinerary and traveler contact files Connect Google Calendar API credentials Configure SMTP server for emails Set up SMS service provider (Twilio, Nexmo, or similar) Map Excel sheet columns to workflow variables Test with sample trip data Activate workflow Parameters to Configure schedule_file_path: Path to trip itinerary file contacts_file_path: Path to traveler contacts file reminder_hours: Hours before departure to send reminder (default: 24) google_calendar_id: Google Calendar ID for syncing trips google_api_credentials: Google Calendar API credentials smtp_host: Email server settings smtp_user: Email username smtp_password: Email password sms_api_key: SMS service API key sms_phone_number: SMS sender phone number reminder_log_path: Path to reminder log file Sample Reminder Messages Email Subject: "✈️ Travel Reminder: [Trip Name] Today at [Time]" Email Body: Hello [Traveler Name], Your trip is happening today! Here are your travel details: Trip: [Trip Name] Departure: [Departure Time] From: [Departure Location] To: [Destination] Flight/Transport: [Flight Number] Hotel: [Hotel Name] Duration: [X] days Pre-Travel Checklist: ☑ Passport and travel documents ☑ Travel insurance documents ☑ Hotel confirmations ☑ Medications and toiletries ☑ Weather-appropriate clothing ☑ Phone charger and adapters ⚠️ Please arrive at the departure point 2 hours early! Have a wonderful trip! SMS: "✈️ Travel Reminder: '[Trip Name]' departs at [Time] today from [Location]. Arrive 2 hours early! Flight: [Number]" Tomorrow Evening Preview (SMS): "📅 Tomorrow: '[Trip Name]' departs at [Time] from [Location]. Pack tonight! ([X] days)" Use Cases Daily trip departure reminders for travelers Last-minute itinerary change notifications Flight cancellation and delay alerts Hotel check-in and checkout reminders Travel document expiration warnings Group tour activity scheduling Adventure/hiking trip departure alerts Business travel itinerary updates Family vacation coordination Study abroad program notifications Multi-city tour route confirmations Transport connection reminders Advanced Features Reminder Escalation 24-hour reminder: Full details with checklist 6-hour reminder: Quick confirmation with transport details 2-hour reminder: Urgent departure notification Conditional Logic Different messages for single-day vs. multi-day trips Domestic vs. international travel variations Group size-based messaging Weather-based travel advisories Integration Capabilities Connect to airline APIs for real-time flight status Link to hotel management systems for check-in info Integrate weather services for destination forecasts Sync with payment systems for booking confirmations Troubleshooting | Issue | Solution | |-------|----------| | Reminders not sending | Check email/SMS credentials and service quotas | | Calendar sync failing | Verify Google Calendar API permissions | | Duplicate reminders | Check for overlapping reminder time windows | | Missing traveler data | Verify contact file formatting and column mapping | | Batch processing slow | Reduce batch size in Split Into Batches node | Security Considerations Store API credentials in n8n environment variables Use OAuth2 for Google Calendar authentication Encrypt sensitive data in reminder logs Implement role-based access to trip data Audit log all reminder activities Comply with GDPR/privacy regulations for traveler data Performance Metrics Processing Time**: ~2-5 seconds per 50 travelers Success Rate**: >99% for delivery logging Calendar Sync**: Real-time updates Batch Limit**: 10 travelers per batch (configurable) Support & Maintenance Review reminder logs weekly for delivery issues Update traveler contacts as needed Monitor email/SMS service quotas Test workflow after system updates Archive old reminder logs monthly
by n8n Automation Expert | Template Creator | 2+ Years Experience
🌤️ Automated Indonesian Weather Monitoring with Smart Notifications Stay ahead of weather changes with this comprehensive monitoring system that fetches real-time data from Indonesia's official meteorological agency (BMKG) and delivers beautiful, actionable weather reports directly to your Telegram. ⚡ What This Workflow Does This intelligent weather monitoring system automatically: Fetches Official Data**: Connects to BMKG's public weather API for accurate Indonesian forecasts Smart Processing**: Analyzes temperature, humidity, precipitation, and wind conditions Risk Assessment**: Generates contextual warnings for extreme weather conditions Automated Alerts**: Sends formatted weather reports to Telegram every 6 hours Error Handling**: Includes robust error detection and notification system 🎯 Perfect For Local Communities**: Keep neighborhoods informed about weather changes Business Operations**: Plan outdoor activities and logistics based on weather Emergency Preparedness**: Receive early warnings for extreme weather conditions Personal Planning**: Never get caught unprepared by sudden weather changes Agricultural Monitoring**: Track conditions affecting farming and outdoor work 🛠️ Key Features 🔄 Automated Scheduling**: Runs every 6 hours with manual trigger option 📊 Comprehensive Reports**: Current conditions + 6-hour detailed forecasts ⚠️ Smart Warnings**: Contextual alerts for temperature extremes and rain probability 🎨 Beautiful Formatting**: Rich Telegram messages with emojis and structured data 🔧 Error Recovery**: Automatic error handling with notification system 📍 Location-Aware**: Supports any Indonesian location via BMKG regional codes 📋 What You'll Get Each weather report includes: Current temperature, humidity, and weather conditions 6-hour detailed forecast with timestamps Wind speed and direction information Rain probability and visibility data Personalized warnings and recommendations Average daily statistics and trends 🚀 Setup Requirements Telegram Bot Token**: Create a bot via @BotFather Chat ID**: Your personal or group chat identifier BMKG Location Code**: Regional administrative code for your area 💡 Pro Tips Customize the location by changing the adm4 parameter in the HTTP request Adjust scheduling interval based on your monitoring needs Modify warning thresholds in the processing code Add multiple chat IDs for broader distribution Integrate with other n8n workflows for advanced automation 🌟 Why Choose This Template Production Ready**: Includes comprehensive error handling and logging Highly Customizable**: Easy to modify for different locations and preferences Official Data Source**: Uses Indonesia's trusted meteorological service User-Friendly Output**: Clean, readable reports perfect for daily use Scalable Design**: Easily extend for multiple locations or notification channels Transform your weather awareness with this professional-grade monitoring system that brings Indonesia's official weather data right to your fingertips! Keywords: weather monitoring, BMKG API, Telegram notifications, Indonesian weather, automated alerts, meteorological data, weather forecasting, n8n automation, weather API integration
by IranServer.com
Automate IP geolocation and HTTP port scanning with Google Sheets trigger This n8n template automatically enriches IP addresses with geolocation data and performs HTTP port scanning when new IPs are added to a Google Sheets document. Perfect for network monitoring, security research, or maintaining an IP intelligence database. Who's it for Network administrators, security researchers, and IT professionals who need to: Track IP geolocation information automatically Monitor HTTP service availability across multiple ports Maintain centralized IP intelligence in spreadsheets Automate repetitive network reconnaissance tasks How it works The workflow triggers whenever a new row containing an IP address is added to your Google Sheet. It then: Fetches geolocation data using the ip-api.com service to get country, city, coordinates, ISP, and organization information Updates the spreadsheet with the geolocation details Scans common HTTP ports (80, 443, 8080, 8000, 3000) to check service availability Records port status back to the same spreadsheet row, showing which services are accessible The workflow handles both successful connections and various error conditions, providing a comprehensive view of each IP's network profile. Requirements Google Sheets API access** - for reading triggers and updating data Google Sheets document** with at least an "IP" column header How to set up Create a Google Sheet with columns: IP, Country, City, Lat, Lon, ISP, Org, Port_80, Port_443, Port_8000, Port_8080, Port_3000 Configure Google Sheets credentials in both the trigger and update nodes Update the document ID in the Google Sheets Trigger and both Update nodes to point to your spreadsheet Test the workflow by adding an IP address to your sheet and verifying the automation runs How to customize the workflow Modify port list**: Edit the "Edit Fields" node to scan different ports by changing the ports array Add more geolocation fields**: The ip-api.com response includes additional fields like timezone, zip code, and AS number Change trigger frequency**: Adjust the polling interval in the Google Sheets Trigger for faster or slower monitoring Add notifications**: Insert Slack, email, or webhook nodes to alert when specific conditions are detected Filter results**: Add IF nodes to process only certain IP ranges or geolocation criteria
by Joseph LePage
n8n Creators Leaderboard Workflow Why Use This Workflow? The n8n Creators Leaderboard Workflow is a powerful tool for analyzing and presenting detailed statistics about workflow creators and their contributions within the n8n community. It provides users with actionable insights into popular workflows, community trends, and top contributors, all while automating the process of data retrieval and report generation. Benefits Discover Popular Workflows**: Identify workflows with the most unique visitors and inserters (weekly and monthly). Understand Community Trends**: Gain insights into what workflows are resonating with the community. Recognize Top Contributors**: Highlight impactful creators to foster collaboration and inspiration. Save Time with Automation**: Automates data fetching, processing, and reporting for efficiency. Use Cases For Workflow Creators**: Track performance metrics of your workflows to optimize them for better engagement. For Community Managers**: Identify trends and recognize top contributors to improve community resources. For New Users**: Explore popular workflows as inspiration for building your own automations. How It Works This workflow aggregates data from GitHub repositories containing statistics about workflow creators and their templates. It processes this data, filters it based on user input, and generates a detailed Markdown report using an AI agent. Key Features Data Aggregation: Fetches creator and workflow statistics from GitHub JSON files. Custom Filtering: Focuses on specific creators based on a username provided via chat. AI-Powered Reports: Generates comprehensive Markdown reports with summaries, tables, and insights. Output Flexibility: Saves reports locally with timestamps for easy access. Data Retrieval & Processing Creators Data**: Retrieved via an HTTP Request node from a JSON file containing aggregated statistics about creators. Workflows Data**: Pulled from another JSON file with workflow metrics like visitor counts and inserter statistics. Data Merging**: Combines creator and workflow data by matching usernames to provide enriched statistics. Report Generation The AI agent generates a Markdown report that includes: A summary of the creator’s contributions. A table of workflows with key metrics (e.g., unique visitors, inserters). Insights into trends or community feedback. The report is saved locally as a file with a timestamp for tracking purposes. Quick Start Guide Prerequisites Ensure your n8n instance is running. Verify that the GitHub base URL and file variables are correctly set in the Global Variables node. Confirm that your OpenAI credentials are configured for the AI Agent node. How to Start Activate the Workflow: Make sure the workflow is active in your n8n environment. Trigger via Chat: Use the Chat Trigger node to initiate the workflow by sending a message like: show me stats for username [desired_username] Replace [desired_username] with the username you want to analyze. Processing & Report Generation: The workflow fetches data, processes it, and generates a Markdown report. View Output: The final report is saved locally as a file (with a timestamp), which you can review to explore leaderboard insights.
by Juan Carlos Cavero Gracia
This automation template is an AI-powered booking agent that schedules property viewings and reserves restaurant tables for you, all coordinated through Telegram. It checks your calendar to avoid conflicts, places the calls on your behalf, negotiates times, confirms details, and delivers a crisp summary back to Telegram—hands-free. Note: This workflow uses a voice-calling provider for outbound calls, your calendar for availability, and Telegram for notifications. Usage costs depend on your telephony provider, call duration, and any API usage.* Who Is This For? Home Buyers & Renters:** Queue up and confirm viewings without calling around. Real Estate Agents & Property Managers:** Automate client viewing scheduling and confirmations. Relocation Specialists & Assistants:** Coordinate multi-property tours with calendar-aware logic. Busy Professionals:** Let AI handle restaurant bookings and post-viewing meals. Concierge & Ops Teams:** Standardize bookings with structured logs and Telegram updates. What Problem Does This Workflow Solve? Scheduling property viewings and restaurant tables often means endless calls, conflicts, and coordination. This workflow removes the friction by: AI Phone Calls on Your Behalf:** Natural voice calls to agents/venues to secure slots. Calendar-Aware Booking:** Checks your real-time availability and avoids overlaps. Preference Handling:** Location, budget, party size, time windows, language, and notes. Instant Telegram Summaries:** Clear outcomes (confirmed, waitlist, action needed) and quick next steps. Scalable Coordination:** Handles multiple properties and dining options with fallback logic. How It Works Intent Capture (Telegram): You send a simple message (e.g., “Viewings tomorrow 17:00–20:00, Eixample, 2-bed; table for 4 at 21:30 near there”). Calendar Check: Reads free/busy blocks and suggests viable windows or alternatives. AI Calling: Places outbound calls to listing agents/restaurants, negotiates slots, and confirms. Result Parsing: Extracts confirmed time, address, contact name, reservation name, and special instructions. Telegram Delivery: Sends a concise recap plus optional quick-reply buttons (confirm/cancel/map/nav). Optional Calendar Hold: Adds confirmed bookings to your calendar and blocks time. Logging (Optional): Writes outcomes to a sheet/database for tracking and analytics. Setup Telephony Provider: Connect your AI calling service (API key). Configure voice/language. Calendar Access: Link Google Calendar (or similar). Grant read (and optionally write) access. Telegram Bot: Create a bot with BotFather and add the bot token to credentials. Environment/Credentials: Store calling API token, calendar credentials, Telegram token in n8n. Preferences: Set defaults for viewings (areas, price range, time windows) and dining (party size, cuisine, budget). Test Run: Trial a single booking to verify calling, calendar sync, and Telegram delivery. Requirements Accounts:** n8n, telephony provider, calendar account, Telegram bot. API Keys:** Telephony API token, Calendar credentials, Telegram bot token. Permissions:** Calendar read (and write if auto-blocking); outbound calls enabled. Budget:** Telephony per-minute fees and minor API costs where applicable. Features Dual-Domain Booking:** Property viewings + restaurant tables in one flow. Calendar Intelligence:** Checks conflicts and proposes best-fit time slots. Telegram-Native UX:** Simple prompts, instant confirmations, and quick actions. Preference Profiles:** Time windows, neighborhoods, max budget, language, and notes. Fallbacks & Alternatives:** Suggests nearby times/venues if first choice is unavailable. Multilingual Voice:** Configure voice and language to match region/venue. Structured Logs:** Optional recording of outcomes for reporting and audits. Extensible:** Add CRM, maps, SMS, or payment links as needed. Automate your day from tours to tables: message your intent on Telegram, and let the AI book, confirm, and keep your calendar clean—so you just show up on time.
by Rahi
WABA Message Journey Flow Documentation This document outlines the automated workflow for sending WhatsApp messages to contacts, triggered hourly and managed through disposition and message count logic. The workflow is designed to ensure contacts receive messages based on their status and the frequency of previous interactions. Trigger and Data Retrieval The journey begins with a time-based trigger and data retrieval from the Supabase contacts table. Trigger: A "Schedule Trigger3" node initiates the workflow every hour. This ensures that the system regularly checks for contacts requiring messages. Get Contacts: The "Get many rows1" node (Supabase) then retrieves all relevant contact data from the contacts_ampere table in Supabase. This brings in contact details such as name, phone, Disposition, Count, and last_message_sent. Disposition-Based Segregation After retrieving the contacts, the workflow segregates them based on their Disposition status. Disposition Switch: The "Disposition Switch" node acts as the primary routing mechanism. It evaluates the Disposition field of each contact and directs them to different branches of the workflow based on predefined categories. Case 0: new_lead: Contacts with the disposition new_lead are routed to the "Count Switch" for further processing. Cases 1-4: The workflow also includes branches for test_ride, Booking, walk_in, and Sale dispositions, though the detailed logic for these branches is not fully laid out in the provided JSON beyond the switch nodes ("Switch2", "Switch3", "Switch4", "Switch5"). The documentation focuses on the new_lead disposition's detailed flow, which can be replicated for others. Message Count Logic (for new_lead Disposition) For contacts identified as new_lead, the workflow uses a "Count Switch" to determine which message in the sequence should be sent. Count Switch: This node evaluates the Count field for each new_lead contact. This Count likely represents the number of messages already sent to the contact within this specific journey. Count = 0: Directs to "Loop Over Items1" (first message in sequence). Count = 1: Directs to "Loop Over Items2" (second message in sequence). Count = 2: Directs to "Loop Over Items3" (third message in sequence). Count = 3: Directs to "Loop Over Items4" (fourth message in sequence). Looping and Interval Check Each "Loop Over Items" node processes contacts in batches and incorporates an "If Interval" check (except for Loop Over Items1). Loop Over Items (e.g., "Loop Over Items1", "Loop Over Items2", "Loop Over Items3", "Loop Over Items4"): These nodes iterate through the contacts received from the "Count Switch" output. Interval Logic: "If Interval" (for Count = 1 from "Loop Over Items2"): Checks if the interval is greater than or equal to 4. This interval value is handled by a separate Supabase cron job, which updates it every minute based on Current time - last api hit time in hours. "If Interval1" (for Count = 2 from "Loop Over Items3"): Checks if the interval is exactly 24 hours. "If2" (for Count = 3 from "Loop Over Items4"): Checks if the interval is exactly 24 hours. Sending WhatsApp Messages If a contact passes the interval check (or immediately for Count = 0), a WhatsApp message is sent using the Gallabox API. HTTP Request Nodes (e.g., "new_lead_0", "new_lead_", "new_lead_3", "new_lead_2"): These nodes are responsible for sending the actual WhatsApp messages via the Gallabox API. They are configured with: Method: POST URL: https://server.gallabox.com/devapi/messages/whatsapp Authentication: apiKey and apiSecret are used in the headers. Body: Contains channelId, channelType (whatsapp), and recipient (including name and phone). WhatsApp Message Content: Includes type: "template" and templateName (e.g., testing_rahi, wu_2, testing_rahi_1). The bodyValues dynamically insert the contact's name and other details. Some messages also include buttonValues for quick replies (e.g., "Show me Brochure"). Logging and Updating Contact Status After a message is sent (or attempted), the workflow logs the interaction and updates the contact's record. Create Logs (e.g., "Create Logs", "Create Logs1", "Create Logs2", "Create Logs3"): These Supabase nodes record details of the message send attempt into the logs_nurture_ampere table. This includes: message_id (from the Gallabox API response body) phone and name of the contact disposition and mes_count (which is Count + 1 from the contacts table) last_sent (timestamp from Gallabox API response headers) status_code and status_message (from Gallabox API response or error). These nodes are configured to "continueRegularOutput" on error, meaning the workflow will attempt to proceed even if logging fails. Status Code Check (e.g., "If StatusCode", "If StatusCode 202", "If StatusCode 203", "If StatusCode 204"): Immediately after attempting to create a log, an "If" node checks if the status_code from the message send attempt is "202" (indicating acceptance by the messaging service). Update Contact Row (e.g., "Update a row1", "Update a row2", "Update a row3", "Update a row4"): If the status code is 202, these Supabase nodes update the contacts_ampere table for the specific contact. The Count for the contact is incremented by 1 (Count + 1). The last_message_sent field is updated with the date from the Gallabox API response headers. These nodes are also configured to "continueRegularOutput" on error. This structured flow ensures that contacts are nurtured through a sequence of WhatsApp messages, with each interaction logged and the contact's status updated for future reference and continuation of the journey.
by Rahul Joshi
📘 Description: This workflow automates sales performance tracking and motivational updates by integrating HighLevel CRM, Notion, GPT-4o, and Slack. It pulls all deals from HighLevel, cleans and summarizes sales data per representative, creates performance dashboards in Notion, and uses GPT-powered AI to generate personalized motivational Slack messages. It eliminates manual leaderboard tracking and boosts sales engagement with real-time insights and daily motivation — ensuring every sales rep stays informed, recognized, and inspired. What This Workflow Does (Step-by-Step) 🟢 Manual Trigger – Starts the automation manually for data refresh or testing. 📦 Fetch All Deals from HighLevel CRM – Retrieves all opportunities from HighLevel CRM, including deal names, reps, values, and stages for full visibility. 🔍 Validate Deal Fetch Success (IF Node) – Verifies that fetched data contains valid deal IDs. ✅ True Path: Continues to data cleaning. ❌ False Path: Logs failed records to Google Sheets for debugging. 🧹 Clean & Structure Deal Data – Normalizes raw deal data into a consistent schema (deal ID, rep ID, client name, value, status). Ensures clean inputs for analytics. 📊 Summarize Sales by Representative – Aggregates deals per sales rep and computes: Total deals handled Total deal value Total deals won Average deal value 🧾 Generate Notion Performance Dashboard – Creates personalized Notion dashboards for each rep with daily updated performance summaries and motivation metrics. ⚙️ Transform Data for AI Input – Converts summarized data into AI-readable format for GPT-4o processing. 🧠 GPT-4o Model Configuration – Sets up Azure OpenAI GPT-4o model to generate motivational and contextual Slack messages. 🤖 AI-Generated Motivational Slack Messages – Uses LangChain + GPT-4o to create energetic, emoji-filled messages that celebrate rep achievements and encourage improvement. 💬 Notify Sales Team in Slack – Sends the AI-generated performance summaries and motivational blurbs directly to each rep or the team Slack channel for transparency and engagement. 🚨 Log Fetch or Validation Errors (Error Handling) – Records any fetch or validation failures in the Google Sheets “error log sheet” for easy review and error management. Prerequisites HighLevel CRM API credentials Google Sheets for “Error Log” tracking Notion API integration for dashboards Azure OpenAI (GPT-4o) credentials Slack API connection for notifications Key Benefits ✅ Fully automated daily performance tracking ✅ Personalized AI-powered motivation in Slack ✅ Transparent visibility for managers and reps ✅ Improved accountability and sales performance ✅ Seamless integration across CRM, Notion, and Slack 👥 Perfect For Sales teams seeking real-time motivation and transparency Managers who want automated performance dashboards Teams using HighLevel CRM and Slack for daily operations Companies aiming to gamify sales productivity
by noda
Price Anomaly Detection & News Alert (Marketstack + HN + DeepL + Slack) Overview This workflow monitors a stock’s closing price via Marketstack. It computes a 20-day moving average and standard deviation (±2σ). If the latest close is outside ±2σ, it flags an anomaly, fetches related headlines from Hacker News, translates them to Japanese with DeepL, and posts both original and translated text to Slack. When no anomaly is detected, it sends a concise “normal” report. How it works 1) Daily trigger at 09:00 JST 2) Marketstack: fetch EOD data 3) Code: compute mean/σ and classify (normal/high/low) 4) IF: anomaly? → yes = news path / no = normal report 5) Hacker News: search related items 6) DeepL: translate EN → JA 7) Slack: send bilingual notification Requirements Marketstack API key DeepL API key Slack OAuth2 (bot token / channel permission) Notes Edit the ticker in Get Stock Data. Adjust N (days) and k (sigma multiplier) in Calculate Deviation. Keep credentials out of HTTP nodes (use n8n Credentials).
by Rahul Joshi
📘 Description: This workflow automates the Developer Q&A Classification and Documentation process using Slack, Azure OpenAI GPT-4o, Notion, Airtable, and Google Sheets. Whenever a new message is posted in a specific Slack channel, the workflow automatically: Captures and validates the message data Uses GPT-4o (Azure OpenAI) to check if the question matches any existing internal FAQs Logs answered questions into Notion as new FAQ entries Sends unanswered ones to Airtable for human follow-up Records any workflow or API errors into Google Sheets This ensures that every developer query is instantly categorized, documented, and tracked, turning daily Slack discussions into a continuously improving knowledge base. ⚙️ What This Workflow Does (Step-by-Step) 🟢 Slack Channel Trigger – Developer Q&A Triggers the workflow whenever a new message is posted in a specific Slack channel. Captures message text, user ID, timestamp, and channel info. 🧩 Validate Slack Message Payload (IF Node) Ensures the incoming message payload contains valid user and text data. ✅ True Path → Continues to extract and process the message ❌ False Path → Logs error to Google Sheets 💻 Extract Question Metadata (JavaScript) Cleans and structures the Slack message into a standardized JSON format — removing unnecessary characters and preparing a clean “question object” for AI processing. 🧠 Classify Developer Question (AI) (Powered by Azure OpenAI GPT-4o) Uses GPT-4o to semantically compare the question with an internal FAQ dataset. If a match is found → Marks as answered and generates a canonical response If not → Flags it as unanswered 🧾 Parse AI JSON Output (Code Node) Converts GPT-4o’s text output into structured JSON so that workflow logic can reference fields like status, answer_quality, and canonical_answer. ⚖️ Check If Question Was Answered (IF Node) If status == "answered", the question is routed to Notion for documentation; otherwise, it’s logged in Airtable for review. 📘 Save Answered Question to Notion FAQ Creates a new Notion page under the “FAQ” database containing the question, AI’s canonical answer, and answer quality rating — automatically building a self-updating internal FAQ. 📋 Log Unanswered Question to Airtable Adds unresolved or new questions into Airtable for manual review by the developer support team. These records later feed back into the FAQ training loop. 🚨 Log Workflow Errors to Google Sheets Any missing payloads, parsing errors, or failed integrations are logged in Google Sheets (error log sheet) for transparent tracking and debugging. 🧩 Prerequisites: Slack API credentials (for message trigger) Azure OpenAI GPT-4o API credentials Notion API connection (for FAQ database) Airtable API credentials (for unresolved questions) Google Sheets OAuth connection (for error logging) 💡 Key Benefits: ✅ Automates Slack Q&A classification ✅ Builds and updates internal FAQs with zero manual input ✅ Ensures all developer queries are tracked ✅ Reduces redundant questions in Slack ✅ Maintains transparency with error logs 👥 Perfect For: Engineering or support teams using Slack for developer communication Organizations maintaining internal FAQs in Notion Teams wanting to automatically capture and reuse knowledge from real developer interactions
by Rahul Joshi
Description Automatically detect customer churn risks from Zendesk tickets, log them into Google Sheets for tracking, and send instant Slack alerts to your customer success team. This workflow helps you spot unhappy customers early and take proactive action to reduce churn. 🚨📊💬 What This Template Does Fetches Zendesk tickets daily on schedule (8:00 PM). ⏰ Processes and formats ticket data into clean JSON (priority, age, urgency). 🧠 Identifies churn risks based on negative satisfaction ratings. ⚠️ Logs churn risk tickets into Google Sheets for analysis and reporting. 📈 Sends formatted Slack alerts with ticket details to the CS team channel. 📢 Key Benefits Detects unhappy customers before they churn. 🚨 Centralized churn tracking for reporting and team reviews. 🧾 Proactive alerts to reduce response delays. ⏱️ Clean, structured ticket data for analytics and filtering. 🔄 Strengthens customer success strategy with real-time visibility. 🌐 Features Schedule Trigger – Runs every weekday at 8:00 PM. 🗓️ Zendesk Integration – Fetches all tickets automatically. 🎫 Smart Data Processing – Adds ticket age, urgency, and priority mapping. 🧮 Churn Risk Filter – Flags tickets with negative satisfaction scores. 🚩 Google Sheets Logging – Saves churn risk details with metadata. 📊 Slack Alerts – Sends formatted messages with ID, subject, rating, and action steps. 💬 Requirements n8n instance (cloud or self-hosted). Zendesk API credentials with ticket read access. Google Sheets OAuth2 credentials with write permissions. Slack Bot API credentials with channel posting permissions. Pre-configured Google Sheet for churn risk logging. Target Audience Customer Success teams monitoring churn risk. 👩💻 SaaS companies tracking customer health. 🚀 Support managers who want proactive churn alerts. 🛠️ SMBs improving retention through automation. 🏢 Remote CS teams needing instant notifications. 🌐 Step-by-Step Setup Instructions Connect your Zendesk, Google Sheets, and Slack credentials in n8n. 🔑 Update the Schedule Trigger (default: daily at 8:00 PM) if needed. ⏰ Replace the Google Sheet ID with your churn risk tracking sheet. 📊 Confirm the Slack channel ID for alerts (default: zendesk-churn-alerts). 💬 Adjust churn filter logic (default: satisfaction_score = "bad"). 🎯 Run a test to fetch Zendesk tickets and validate Sheets + Slack outputs. ✅
by Rahul Joshi
📘 Description: This workflow automates the incident response lifecycle — from creation to communication and archival. It instantly creates Jira tickets for new incidents, alerts the on-call Slack team, generates timeline reports, logs the status in Google Sheets, and archives documentation to Google Drive — all automatically. It helps engineering and DevOps teams respond faster, maintain audit trails, and ensure no incident details are lost, even after Slack or Jira history expires. ⚙️ What This Workflow Does (Step-by-Step) 🟢 Manual Trigger – Start the incident creation and alerting process manually on demand. 🏷️ Define Incident Metadata – Sets up standardized incident data (Service, Severity, Description) used across Jira, Slack, and Sheets for consistent processing. 🎫 Create Jira Incident Ticket – Automatically creates a Jira task with service, severity, and description fields. Returns a unique Jira key and link for tracking. ✅ Validate Jira Ticket Creation Success – Confirms the Jira ticket was successfully created before continuing. True Path: Proceeds to Slack alerts and documentation flow. False Path: Logs the failure details to Google Sheets for debugging. 🚨 Log Jira Creation Failures to Error Sheet – Records any Jira API errors, permission issues, or timeouts to an error log sheet for reliability monitoring. 🔗 Combine Incident & Jira Data – Merges incident context with Jira ticket data to ensure all details are unified for downstream notifications. 💬 Format Incident Alert for Slack – Generates a rich Slack message containing Jira key, service, severity, and description with clickable Jira links. 📢 Alert On-Call Team in Slack – Posts the formatted message directly to the #oncall Slack channel to instantly notify engineers. 📋 Generate Incident Timeline Report – Parses Slack message content to create a detailed incident timeline including timestamps, service, severity, and placeholders for postmortem tracking. 📄 Convert Timeline to Text File – Converts the generated timeline into a structured .txt file for archival and compliance. ☁️ Archive Incident Timeline to Drive – Uploads the finalized incident report to Google Drive (“Incident Reports” folder) with timestamped filenames for traceability. 📊 Log Incident to Status Tracking Sheet – Appends Jira key, service, severity, and timestamp to the “status update” Google Sheet to build a live incident dashboard and enable SLA tracking. 🧩 Prerequisites Jira account with API access Google Sheets for “status update” and “error log” tracking Slack workspace connected via API credentials Google Drive access for archival 💡 Key Benefits ✅ Instant Slack alerts for new incidents ✅ Centralized Jira ticketing and tracking ✅ Automated timeline documentation for audits ✅ Seamless Google Drive archival and status logging ✅ Reduced MTTR through faster communication 👥 Perfect For DevOps and SRE teams managing production incidents Engineering managers overseeing uptime and reliability Organizations needing automated post-incident documentation Teams focused on SLA adherence and compliance reporting