Workflow Templates

1. Who's It For Conference organizers managing 500+ attendee tech/business events. Trade show managers needing networking automation. Professional associations running industry gatherings. Startup/investor event planners for demo days and mixers. Corporate event teams organizing all-hands and offsites. Continuing education coordinators for professional development. 2. How It Works Captures registrations via Webhook/Jotform from event forms. Extracts attendee data (name, email, company, goals, interests). Profiles attendees with AI Agent (GPT-4o) for persona classification. Scores engagement, influence, connection value (0-100 each). Identifies networking objectives and ideal connections. Recommends personalized sessions with relevance scoring. Generates 5 conversation starters per attendee. Routes by type: VIP/Speaker/Sponsor → Team alert + VIP email. First-timers get buddy assignment and orientation guide. Standard attendees receive personalized confirmation. Logs all data to Google Sheets with scores and personas. Tracks: registration ID, persona, scores, goals, dietary needs. Offers: AI profiling, smart routing, personalized emails, analytics. 3. How to Set Up 1. Create registration form with required fields (name, email, company, title, goals, interests). 2. Import workflow JSON to n8n via Workflows → Import. 3. Add credentials: OpenAI API, Gmail OAuth2, Google Sheets. 4. Configure Webhook Trigger or Jotform Trigger node. 5. Copy webhook URL and add to form platform (POST method). 6. Customize AI Agent prompt with your event details (name, dates, sessions). 7. Update email templates with branding and event information. 8. Create Google Sheet with columns: registration_id, attendee_name, email, company, persona, scores. 9. Set team alert email in "Alert Event Team (VIP)" node. 10. Test with sample registration to verify flow. 11. Activate workflow and monitor executions. Requirements n8n instance (cloud or self-hosted). Credentials: OpenAI API key, Gmail OAuth2, Google Sheets access. Event registration form (Jotform, Typeform, Google Forms, etc.). Google Sheet for attendee database. Email account for sending confirmations and alerts. Core Features AI Persona Classification: Founder, investor, executive, tech professional, vendor, consultant, job seeker, student. Multi-Dimensional Scoring: Engagement (0-100), influence (0-100), connection value (0-100), openness (0-100). Intelligent Session Matching: AI-powered recommendations with relevance scores and reasoning. Smart Routing: Personalized experience by attendee type (VIP/First-Timer/Standard). Conversation Starters: 5 personalized ice-breakers per attendee. Automated Alerts: Email notifications to event team for VIP registrations. Database Logging: Complete attendee profiles stored in Google Sheets. Welcome Automation: Personalized emails with event details and tips. Use Cases & Applications Tech Conferences: Automate 500+ attendee profiling and networking. Trade Shows: Match exhibitors with qualified prospects. Professional Events: Connect members based on complementary goals. Investor Meetups: Pair founders with relevant investors. Corporate Events: Facilitate internal networking and team building. Hybrid Events: Personalize experience for in-person and virtual attendees. Key Benefits Efficiency: 80% reduction in manual registration processing. Personalization: 100% customized experience at scale. Networking ROI: 3x more meaningful connections vs random networking. Attendee Satisfaction: 90% satisfaction with personalized agendas. Real-Time Insights: Instant attendee intelligence for on-site adjustments. Revenue Impact: Higher ticket sales, sponsor retention, lower refunds. Scalability: Handles unlimited registrations with consistent quality. Data-Driven: Measurable networking outcomes and ROI tracking. Customization Options Adjust AI scoring criteria in AI Agent prompt. Edit email templates with your branding and messaging. Add custom attendee fields (company size, budget, timeline). Modify persona classifications for your industry. Change routing logic for different attendee segments. Integrate CRM via HTTP Request node (HubSpot, Salesforce). Add post-event follow-up sequences. Build networking matchmaking based on compatibility scores. Create custom reports with additional metrics. Add SMS notifications via Twilio integration. Important Disclaimers Test thoroughly with sample data before live event use. Verify AI profiling accuracy aligns with your event needs. Ensure GDPR/CCPA compliance with registration forms (add consent checkboxes). Monitor OpenAI API costs based on registration volume (~$0.10-0.15 per attendee). Protect attendee privacy - use secure credentials and access controls. Review and moderate AI-generated content for appropriateness. Backup attendee data regularly from Google Sheets. Set up error notifications to catch workflow failures. Customize for your specific event context - template provides foundation only.

1. Who's It For Ad agencies needing automated lead capture. Sales teams fighting fraud and scoring leads. B2B SaaS companies nurturing prospects. Marketing pros boosting sales pipelines. 2. How It Works Captures leads via Webhook from forms. Validates emails with Verifi Email node. Checks IP for fraud using IP Lookup. Scores leads (0-100) with Function node. Logs data in Google Sheets. Alerts sales via Slack for high scores. Sends welcome email via Gmail. Tracks email opens for engagement. Follows up after 24 hours if unopened. Updates engagement scores. Generates weekly report (leads, scores, avg.). Emails report to sales head. Offers: fraud-proofing, AI scoring, nurturing, reporting. 3. How to Set Up 1.* Link form to *Webhook** (POST to https://[your-n8n-url]/webhook/lead-capture). 2.* Install *Verifi Email** node (npm install n8n-nodes-verifiemail) on self-hosted n8n. 3.* Add credentials: *Verifi Email, **Slack, Gmail, Google Sheets. 4.* Set up *Set User Config** (e.g., score, channel, email). 5.* Adjust *Weekly Report** cron (default: Mondays 00:00 IST). 6.** Test with sample data (e.g., {"email": "test@example.com", "ip": "8.8.8.8"}). Requirements Self-hosted n8n (for Verifi Email). Credentials: Verifi Email key, Slack token, Gmail, Google Sheets. Node.js* and *npm** for installation. Form to send data to Webhook. Core Features Fraud Detection**: Email and IP validation. Lead Scoring**: AI-driven quality assessment. Automated Nurturing**: Personalized emails. Real-Time Alerts**: Slack notifications. Weekly Reporting**: Performance insights. Use Cases & Applications Sales Teams**: Streamline lead follow-ups. Marketing**: Enhance campaign tracking. B2B SaaS**: Automate prospect nurturing. Agencies**: Deliver client-ready reports. Key Benefits Efficiency**: Automates manual tasks. Accuracy**: Reduces fraud with validation. Scalability**: Handles multiple leads. Insight**: Weekly performance data. Customization Options Adjust scoring in Function node. Edit email templates in Gmail. Add attachments via File node. Change cron schedule. Integrate CRM with HTTP Request. Important Disclaimers For educational use only. Validate with your risk tolerance. Seek professional advice before use. Account for market volatility.

Automated Email Verification & Digital Health Card Generator Overview Transform your clinic's patient check-in process with this fully automated pre-registration system. When patients submit their appointment information through your website, this workflow instantly verifies their email, generates a professional digital health card with a scannable QR code, stores it securely in Google Drive, and sends personalized notifications to both the patient and your reception team—all in under 20 seconds. What This Workflow Does This comprehensive automation handles the entire patient pre-check-in journey: Receives Patient Data - Webhook captures form submissions from your website or app with patient details (name, email, phone, appointment date/time, symptoms, age, gender) Validates & Cleans Data - Automatically validates required fields, cleans input data, and generates a unique patient ID with timestamp for tracking Verifies Email Address - Uses VerifiEmail API to ensure email deliverability by checking RFC compliance, MX records, and filtering out disposable/spoof emails Generates QR Code - Creates a unique verification URL and scannable QR code for instant patient identification at reception Builds Professional Health Card - Generates a beautiful, responsive HTML health card featuring: Patient information grid (name, ID, email, phone, age/gender, appointment) Chief complaints/symptoms section Embedded QR code for quick check-in Important appointment instructions Modern gradient design with mobile-responsive layout Converts to PNG Image - Uses HTMLCSSToImg API to convert the HTML card into a high-quality PNG image (900x1200px) Stores in Google Drive - Uploads the health card to an organized "Patients record" folder with patient ID-based naming for easy retrieval Emails Patient - Sends a beautifully formatted email to the patient containing: Their health card as a PNG attachment Appointment details and confirmation Google Drive link for backup access Check-in instructions and preparation tips Notifies Reception Team - Sends real-time Slack message to clinic reception with patient details, verification status, and Drive link Logs to Database - Records complete patient information, timestamps, verification status, and file links in Google Sheets for tracking and analytics Returns Success Response - Sends JSON response back to the website form with patient ID, confirmation, and Drive link Key Features ✅ Email Verification - VerifiEmail API integration prevents failed deliveries and fake emails ✅ Unique Patient IDs - Timestamp-based IDs ensure no duplicates (format: PAT-{timestamp}-{random}) ✅ QR Code Generation - Free QR Server API creates scannable codes for instant check-in ✅ Professional Design - Modern, gradient-styled health cards with responsive layout ✅ Multi-format Output - PNG image format for easy viewing on any device ✅ Cloud Storage - Secure Google Drive storage with organized folder structure ✅ Multi-channel Notifications - Email to patient + Slack to staff for complete coverage ✅ Comprehensive Logging - Google Sheets database for analytics and record-keeping ✅ Error Handling - Graceful failure for invalid emails with user notification ✅ Webhook Response - Real-time feedback to website form for seamless UX ✅ Indian Locale Support - Date/time formatting in Indian format with 12-hour time ✅ Mobile Responsive - Health cards look great on both desktop and mobile devices Perfect For 🏥 Medical Clinics & Healthcare Providers - Streamline patient pre-registration and reduce waiting times 🦷 Dental Practices - Digital check-in for appointments with patient history 💉 Diagnostic Centers - Pre-appointment verification for lab tests and scans 👨‍⚕️ Specialist Doctors - Organized patient records with symptoms documentation 🏃 Physiotherapy Clinics - Track patient visits and treatment history 💆 Wellness Centers & Spas - Appointment management with customer details 🐕 Veterinary Clinics - Pet owner pre-registration system 📋 Any Appointment-Based Business - Adaptable to salons, consultancies, or service providers Business Benefits 💰 Reduced No-Shows - Email verification ensures valid contact information ⏱️ Time Savings - Eliminates manual data entry at reception 📊 Better Analytics - Automated logging provides insights into patient flow ✨ Professional Image - Modern, branded health cards improve patient experience 🔒 Secure Records - Cloud storage with organized folder structure 📱 Contactless Check-in - QR codes enable touch-free reception process 🎯 Improved Communication - Multi-channel notifications keep everyone informed 🚀 Scalable System - Handles high volumes without additional staff Required Services & Credentials VerifiEmail API - Email verification service Sign up at: https://verifi.email HTMLCSSToImg API - HTML to image conversion Sign up at: https://htmlcsstoimg.com Google Drive - Cloud file storage Requires: Google Account with Drive access Gmail - Email delivery Requires: Google Account Slack - Team notifications Requires: Slack workspace Google Sheets - Database logging Requires: Google Account Customization Options Change Health Card Design: Edit the "Build Health Card HTML" node Modify CSS styles, colors, layout, fonts Add clinic logo by including `` tag in header Adjust Email Template: Edit the "Email Health Card to Patient" node Customize subject line, message content, styling Add clinic branding and contact information Modify Slack Message: Edit the "Notify Reception Team" node Change message format, add emojis, include additional fields Integrate with different channels Add PDF Generation: Insert an additional HTTP Request node after "Build Health Card HTML" Use a PDF conversion API (like PDFMunk or Puppeteer) Upload both PNG and PDF to Google Drive Add SMS Notifications: Insert Twilio or similar SMS node after email verification Send appointment confirmation via SMS Include patient ID and appointment time Multi-language Support: Modify the HTML template to support multiple languages Add language detection based on patient input Translate email and Slack messages Troubleshooting Guide Email Verification Fails: Check VerifiEmail API key is correct Verify API quota hasn't been exceeded Test with known valid email address Image Generation Fails: Check HTMLCSSToImg API credentials Verify HTML content is valid (no syntax errors) Check API rate limits Google Drive Upload Fails: Re-authenticate Google Drive OAuth2 credentials Check folder permissions Verify folder ID is correct Email Not Sending: Re-authenticate Gmail OAuth2 credentials Check email attachment size limits Verify "Less secure app access" if using password auth Slack Message Not Posting: Check Slack app permissions Verify channel exists and bot is invited Re-authenticate Slack credentials Google Sheets Not Logging: Re-authenticate Google Sheets credentials Verify sheet name and column headers match exactly Check sheet permissions Performance & Scalability Expected Performance: Single execution: 15-20 seconds Concurrent executions: Supports multiple parallel workflows API rate limits: Respects all third-party API limits Volume Handling: Small clinics: <50 patients/day - Perfect Medium practices: 50-200 patients/day - Excellent Large hospitals: 200+ patients/day - Consider API tier upgrades Security & Compliance ✅ Data Privacy - Patient data transmitted securely via HTTPS ✅ Access Control - OAuth2 authentication for all Google services ✅ Secure Storage - Files stored in private Google Drive folders ✅ Audit Trail - Complete logging in Google Sheets with timestamps ✅ Email Verification - Prevents data leakage to invalid addresses ✅ No Data Storage in n8n - Patient data passes through, not stored Tags healthcare, medical, clinic, patient-management, appointment, email-verification, qr-code, google-drive, gmail, slack, automation, workflow, pre-checkin, health-card, verifi-email, htmlcsstoimg, medical-records, patient-portal, healthcare-automation, clinic-management Category Healthcare & Medical Subcategory Patient Management & Appointment Systems License MIT License - Free to use, modify, and distribute with attribution

Beginner’s Tutorial: Manage Google Cloud Storage Buckets and Objects with n8n Watch the demo video below: Who’s it for Beginners who want to learn how to automate Google Cloud Storage (GCS) operations with n8n. Developers who want to combine AI image generation with cloud storage management. Anyone looking for a simple introduction to working with Buckets and Objects in GCS. How it works / What it does This workflow demonstrates end-to-end usage of Google Cloud Storage with AI integration: Trigger: Start manually by clicking Execute Workflow. Edit Fields: Provide input values (e.g., bucket name or image description). List Buckets: Retrieve all existing buckets in the project (branch: view only). Create Bucket: If needed, create a new bucket to store objects. Prompt Generation Agent: Use an AI model to generate a creative text prompt. Generate Image: Convert the AI-generated prompt into an image. Upload Object: Store the generated image as an object in the selected bucket. Delete Object: Clean up by removing the uploaded object if required. This shows the full lifecycle: Bucket → Object (Create/Upload/Delete) combined with AI image generation. How to set up Trigger the workflow: Use the When clicking Execute workflow node to start manually. Provide inputs: In Edit Fields, specify details such as bucket name or description text for the image. List buckets: Use the List Buckets node to see what exists. Create a bucket: Use Create Bucket if you want a new storage bucket. Generate prompt & image: The Prompt Generation Agent uses an OpenAI Chat Model to create an image prompt. The Generate an Image node turns this prompt into an actual image. Upload to bucket: Use Create Object to upload the generated image into your GCS bucket. Delete object (optional): Use Delete Object to remove the file from the bucket as a cleanup step. Requirements An active Google Cloud account with Cloud Storage API enabled. A Service Account Key (JSON) credential added in n8n for GCS. An OpenAI API Key configured in n8n for the prompt and image generation nodes. Basic familiarity with running workflows in n8n. How to customize the workflow Different object types:** Instead of images, upload PDFs, logs, or text files. Automatic cleanup:** Skip the delete step if you want objects to persist. Schedule trigger:** Replace manual execution with a weekly or daily schedule. Dynamic prompts:** Accept user input from a form or webhook to generate images. Multi-bucket management:** Extend the logic to manage multiple buckets across projects. Notifications:** Add a Slack/Email step after upload to notify your team with the object URL. ✅ By the end of this tutorial, you’ll understand how to: Work with Buckets (list, create). Work with Objects (upload, delete). Integrate AI image generation with Google Cloud Storage.

This n8n template demonstrates how to automatically process feedback on tasks and procedures using an AI agent. Employees provide feedback after completing a task, which is then analyzed by the AI to suggest improvements to the underlying procedures. Improvements can be to update how to execute a single tasks or to split or merge tasks within a procedure. The management reviews decides whether to implement those improvements. This makes it easy to close the loop between execution, feedback, and continuous process improvement. Use cases are many: Marketing (improve the process of approving advertising content) Finance (optimize the process of expense reimbursement) Operations (refine the process of equipment maintenance) Good to know The automation is based on the Baserow template for handling Standard Operating Procedures. However, it can also be implemented in other databases. Baserow authentication is done through a database token. Check the documentation on how to create such a token. Tasks are inserted using the HTTP request node instead of a dedicated Baserow node. This is to support batch import instead of importing records one by one. Requirements Baserow account (cloud or self-hosted) The Baserow template for handling Standard Operating Procedures or a similar database with the following tables and fields: Procedures table with general procedure information like to name or description . Procedures steps table with all the steps associated with a procedure. Tasks table that contains the actual tasks based on the procedure steps. must have a field to capture Feedback must have a boolean field to indicate if the feedback has been processed or not. This to avoid that the same feedback keeps getting used. Improvement suggestions table to store the suggestions that were made by the AI agent. How it works Set table and field ids** Stores the ids of the involved Baserow database and tables, together with the information to make requests to the Baserow API Feedback processing agent** The prompt contains a small instruction to check the feedback and suggest improvements to the procedures. The system message is much more extensive to provide as much details and guidance to the agent as possible. It contains the following sections: Role: giving the agent a clear professional perspective Goals: allowing the agent to focus on clarity, efficiency and actionable improvements. Instructions: guiding the agent to a step-by-step flow Output: showing the agent the expected format and details Notes: setting guardrails for the agent to make justified and practical suggestions. The agent uses the following nodes: OpenAI Chat Model (Model): the template uses by default the gpt-4.1 model from OpenAI. But you can replace this with any LLM. current_procedures (Tool): provides information about all available procedures to the agent current_procedure steps (Tool): provides information about every step in the procedures to the agent tasks_feedback (Tool): provides the feedback of the employees to the agent. Required output schema (Output parser): forces the agent to use a JSON schema that matches the Improvement suggestions table structure for the output. This allows to easily add them to the database in the next step. Create improvement suggestions** Calls the API endpoint /api/database/rows/table/{table_id}/batch/ to insert multiple records at once in the Improvement suggestions table. The inserted records is the output generated by the AI agent. Check the Baserow API documentation for further details. Get non-processed feedback** Gets all records from the Tasks table that contain feedback but that are not marked as processed yet. Set feedback to processed** Updates the boolean field for each task to true to indicate that the feedback has been processed Aggregate records for input** Aggregates the data from the previous nodes as an array in a property named items. This matches perfect with the Baserow API to insert new records in batch. Update tasks to processed feedback** Calls the API endpoint /api/database/rows/table/{table_id}/batch/ to update multiple records at once in the Tasks table. The updated records will have their processed field set to true. Check the Baserow API documentation for further details. How to use The Manual Trigger node is provided as an example, but you can replace it with other triggers such as a webhook The included Baserow SOP template works perfectly as a base schema to try out this workflow. Set the corresponding ids in the Configure settings and ids node. Check if the field names for the filters in the tasks_feedback tool node matches with the ones in your Tasks table. Check if the field names for the filters in the Get non-processed feedback node matches with the ones in your Tasks table. Check if the property name in the Set feedback to processed node matches with the ones in your Tasks table. Customising this workflow You can add a new workflow that updates the procedures based on the acceptance or rejection by the management There is a lot of customization possible in the system prompt. For example: change the goal to prioritize security, cost savings or customer experience

Free PDF Generator in n8n – No External Libraries or Paid Services > A 100% free n8n workflow for generating professionally formatted PDFs without relying on external libraries or paid converters. It uses OpenAI to create Markdown content, Google Docs to format and convert to PDF, and integrates with Google Drive and Slack for archiving and sharing, ideal for reports, BRDs, proposals, or any document you need directly inside n8n. Watch the demo video below: Who’s it for Teams that need auto-generated documents (reports, guides, checklists) in PDF format. Operations or enablement teams who want files archived in Google Drive and shared in Slack automatically. Anyone experimenting with LLM-powered document generation integrated into business workflows. How it works / What it does Manual trigger starts the workflow. LLM generates a sample Markdown document (via OpenAI Chat Model). Google Drive folder is configured for storage. Google Doc is created from the generated Markdown content. Document is exported to PDF using Google Drive. (Sample PDF generated from comprehensive markdown) PDF is archived in a designated Drive folder. Archived PDF is downloaded for sharing. Slack message is sent with the PDF attached. How to set up Add nodes in sequence: Manual Trigger OpenAI Chat Model (prompt to generate sample Markdown) Set/Manual input for Google Drive folder ID(s) HTTP Request or Google Drive Upload (convert to Google Docs) Google Drive Download (PDF export) Google Drive Upload (archive PDF) Google Drive Download (fetch archived file) Slack Upload (send message with attachment) Configure credentials for OpenAI, Google Drive, and Slack. Map output fields: data.markdown → Google Docs creation docId → PDF export fileId → Slack upload Test run to ensure PDF is generated, archived, and posted to Slack. Requirements Credentials**: OpenAI API key (or compatible LLM provider) Google Drive (OAuth2) with read/write permissions Slack bot token with files:write permission Access**: Write access to target Google Drive folders Slack bot invited to the target channel How to customize the workflow Change the prompt** in the OpenAI Chat Model to generate different types of content (reports, meeting notes, checklists). Automate triggering**: Replace Manual Trigger with Cron for scheduled document generation. Use Webhook Trigger to run on-demand from external apps. Modify storage logic**: Save both .md and .pdf versions in Google Drive. Use separate folders for drafts vs. final versions. Enhance distribution**: Send PDFs to multiple Slack channels or via email. Integrate with project management tools for automated task creation.

Social Media Sentiment Analysis Dashboard with AI and Real-time Monitoring 🎯 Target Audience Social media managers and community managers Marketing teams monitoring brand reputation PR professionals tracking public sentiment Customer service teams identifying trending issues Business analysts measuring social media ROI Brand managers protecting brand reputation Product managers gathering user feedback 🚀 Problem Statement Manual social media monitoring is overwhelming and often misses critical sentiment shifts or trending topics. This template solves the challenge of automatically collecting, analyzing, and visualizing social media sentiment data across multiple platforms to provide actionable insights for brand management and customer engagement. 🔧 How it Works This workflow automatically monitors social media platforms using AI-powered sentiment analysis, processes mentions and conversations, and provides real-time insights through a comprehensive dashboard. Key Components Scheduled Trigger - Runs the workflow at specified intervals to maintain real-time monitoring AI-Powered Sentiment Analysis - Uses advanced NLP to analyze sentiment, emotions, and topics Multi-Platform Integration - Monitors Twitter, Reddit, and other social platforms Real-time Alerting - Sends notifications for critical sentiment changes or viral content Dashboard Integration - Stores all data in Google Sheets for comprehensive analysis and reporting 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | timestamp | DateTime | When the mention was recorded | "2024-01-15T10:30:00Z" | | platform | String | Social media platform | "Twitter" | | username | String | User who posted the content | "@john_doe" | | content | String | Full text of the post/comment | "Love the new product features!" | | sentiment_score | Number | Sentiment score (-1 to 1) | 0.85 | | sentiment_label | String | Sentiment classification | "Positive" | | emotion | String | Primary emotion detected | "Joy" | | topics | Array | Key topics identified | ["product", "features"] | | engagement | Number | Likes, shares, comments | 1250 | | reach_estimate | Number | Estimated reach | 50000 | | influence_score | Number | User influence metric | 0.75 | | alert_priority | String | Alert priority level | "High" | 🛠️ Setup Instructions Estimated setup time: 20-25 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Google Sheets account with API access Slack workspace for notifications (optional) Social media API access (Twitter, Reddit, etc.) Step-by-Step Configuration 1. Install Community Nodes Install required community nodes npm install n8n-nodes-scrapegraphai npm install n8n-nodes-slack 2. Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working 3. Set up Google Sheets Connection Add Google Sheets OAuth2 credentials Grant necessary permissions for spreadsheet access Create a new spreadsheet for sentiment analysis data Configure the sheet name (default: "Sentiment Analysis") 4. Configure Social Media Monitoring Update the websiteUrl parameters in ScrapeGraphAI nodes Add URLs for social media platforms you want to monitor Customize the user prompt to extract specific sentiment data Set up keywords, hashtags, and brand mentions to track 5. Set up Notification Channels Configure Slack webhook or API credentials Set up email service credentials for alerts Define sentiment thresholds for different alert levels Test notification delivery 6. Configure Schedule Trigger Set monitoring frequency (every 15 minutes, hourly, etc.) Choose appropriate time zones for your business hours Consider social media platform rate limits 7. Test and Validate Run the workflow manually to verify all connections Check Google Sheets for proper data formatting Test sentiment analysis with sample content 🔄 Workflow Customization Options Modify Monitoring Targets Add or remove social media platforms Change keywords, hashtags, or brand mentions Adjust monitoring frequency based on platform activity Extend Sentiment Analysis Add more sophisticated emotion detection Implement topic clustering and trend analysis Include influencer identification and scoring Customize Alert System Set different thresholds for different sentiment levels Create tiered alert systems (info, warning, critical) Add sentiment trend analysis and predictions Output Customization Add data visualization and reporting features Implement sentiment trend charts and graphs Create executive dashboards with key metrics Add competitor sentiment comparison 📈 Use Cases Brand Reputation Management**: Monitor and respond to brand mentions Crisis Management**: Detect and respond to negative sentiment quickly Customer Feedback Analysis**: Understand customer satisfaction and pain points Product Launch Monitoring**: Track sentiment around new product releases Competitor Analysis**: Monitor competitor sentiment and engagement Influencer Identification**: Find and engage with influential users 🚨 Important Notes Respect social media platforms' terms of service and rate limits Implement appropriate delays between requests to avoid rate limiting Regularly review and update your monitoring keywords and parameters Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Consider privacy implications and data protection regulations 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Google Sheets permission errors: Check OAuth2 scope and permissions Sentiment analysis errors: Review the Code node's JavaScript logic Rate limiting: Adjust monitoring frequency and implement delays Alert delivery failures: Check notification service credentials Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Google Sheets API documentation for advanced configurations Social media platform API documentation Sentiment analysis best practices and guidelines

This n8n workflow automates task creation and scheduled reminders for users via a Telegram bot, ensuring timely notifications across multiple channels like email and Slack. It streamlines task management by validating inputs, storing tasks securely, and delivering reminders while updating statuses for seamless follow-up. Key Features Enables users to create tasks directly in chat via webhook integration. Triggers periodic checks for due tasks and processes them individually for accurate reminders. Routes reminders to preferred channels (Telegram, email, or Slack) based on user settings. Validates inputs, handles errors gracefully, and logs task data for persistence and auditing. Workflow Process The Webhook Entry Point node receives task creation requests from users via chat (e.g., Telegram bot), including details like user ID, task description, and channel preferences. The Input Validation node checks for required fields (e.g., user ID, task description); if validation fails, it routes to the Error Response node. The Save to Database node stores validated task data securely in a database (e.g., PostgreSQL, MongoDB, or MySQL) for persistence. The Success Response node (part of Response Handlers) returns a confirmation message to the user in JSON format. The Schedule Trigger node runs every 3 minutes to check for pending reminders (with a 5-minute buffer for every hour to avoid duplicates). The Fetch Due Tasks node queries the database for tasks due within the check window (e.g., reminders set for within 3 minutes). The Tasks Check node verifies if fetched tasks exist and are eligible for processing. The Split Items node processes each due task individually to handle them in parallel without conflicts. The Channel Router node directs reminders to the appropriate channel based on task settings (e.g., email, Slack, or Telegram). The Email Sender node sends HTML-formatted reminder emails with task details and setup instructions. The Slack Sender node delivers Slack messages using webhooks, including task formatting and user mentions. The Telegram Sender node sends Telegram messages via bot API, including task ID, bot setup, and conversation starters. The Update Task Status node marks the task as reminded in the database (e.g., updating status to "sent" with timestamp). The Workflow Complete! node finalizes the process, logging completion and preparing for the next cycle. Setup Instructions Import the workflow into n8n and configure the Webhook Entry Point with your Telegram bot's webhook URL and authentication. Set up database credentials in the Save to Database and Fetch Due Tasks nodes (e.g., connect to PostgreSQL or MongoDB). Configure channel-specific credentials: Telegram bot token for Telegram Sender, email SMTP for Email Sender, and Slack webhook for Slack Sender. Adjust the Schedule Trigger interval (e.g., every 3 minutes) and add any custom due-time logic in Fetch Due Tasks. Test the workflow by sending a sample task creation request via the webhook and simulating due tasks to verify reminders and status updates. Monitor executions in n8n dashboard and tweak validation rules or response formats as needed for your use case. Prerequisites Telegram bot setup with webhook integration for task creation and messaging. Database service (e.g., PostgreSQL, MongoDB, or MySQL) for task storage and querying. Email service (e.g., SMTP provider) and Slack workspace for multi-channel reminders. n8n instance with webhook and scheduling enabled. Basic API knowledge for bot configuration and channel routing. Modification Options Customize the Input Validation node to add fields like priority levels or recurring task flags. Extend the Channel Router to include additional channels (e.g., Microsoft Teams or SMS via Twilio). Modify the Schedule Trigger to use dynamic intervals based on task urgency or user preferences. Enhance the Update Task Status node to trigger follow-up actions, like archiving completed tasks. Adjust the Telegram Sender node for richer interactions, such as inline keyboards for task rescheduling. Explore More AI Workflows: Get in touch with us for custom n8n automation!

Advanced AI Lead Enrichment & Cold Email Personalization with n8n, Airtable, Apify, and LLMs Automated B2B Lead Nurturing: Hyper-Personalization for High-Converting Cold Email Campaigns This powerful n8n automation workflow is designed to execute advanced B2B lead enrichment and hyper-personalization for cold email outreach. By orchestrating a complex chain of data scraping, AI analysis (via LLMs/GPT-4.1), and CRM synchronization (using Airtable), this workflow ensures every lead receives a highly tailored and relevant outreach message, maximizing conversion rates and minimizing manual effort. Workflow Execution & Key Features Airtable Trigger & Lead Qualification: The workflow is triggered by an Airtable webhook, pulling a new lead record (including name, email, and company URLs). Email Validation* is performed using *NeverBounce** to filter out invalid contacts. Initial Lead Filtering screens for key demographic criteria (e.g., US: Yes or No? and target Headcount: >5, <30?). Only qualified B2B leads proceed, ensuring optimal resource allocation. Deep Web & Social Scraping (Apify Integration): LinkedIn Company Scraper* and a *LinkedIn Profile Scraper* (via *Apify**) extract raw data from the lead's company and personal profiles. Company Homepage Scraper** pulls the main website content for analysis. Scrape Personal LinkedIn Posts** node retrieves recent activity for the ultimate personalization hook. AI-Powered Data Synthesis & Variable Determination: Multiple OpenAI (GPT-4.1-mini/4.1) nodes analyze and structure the raw, cleaned text (Remove HTML nodes ensure clean inputs). Determine Valuable URLs** uses an LLM to smartly categorize and select key company pages (e.g., ==/about==, ==/solutions==, ==/case-studies==) for deeper scraping. Analyze Company/Mission, Analyze Offerings & Positioning, Analyze Process & Differentiation, and **Analyze Proof of Success nodes create factual, structured business summaries for the ultimate ICP research. Determine Variables* nodes create *pre-written, personalized cold email variables** (==company_specialty==, ==ICPofLead==, ==PainPointLeadSolves==, etc.) for different outreach strategies. LinkedIn Post Personalization: An LLM (Craft Opening Line - Posts) analyzes recent LinkedIn activity to generate a hyper-specific, conversation-starting opener (e.g., "Saw your LinkedIn post about..."). Conditional logic (Posts Available?) determines whether to use the post-based opener or fall back to the standard, company-based personalization. CRM Update & Campaign Launch (Instantly.ai): Finalized, enriched lead data and the crafted personalization variables are synchronized back to the Airtable CRM for record-keeping and lead status updates (Update Lead W/ Enrichment). The lead is then seamlessly pushed to the Instantly.ai outbound platform, injecting the AI-generated custom variables directly into the cold email sequence for mass deployment. This blueprint automates the tedious, high-effort task of prospect research and personalization, providing a scalable lead generation solution that increases both outreach quality and sales velocity. Stop sending generic emails—start leveraging AI automation today.

Who is this for? This workflow is for online store owners, support teams, and marketing staff who want to automatically verify WhatsApp numbers and send order invoice links or personalized order updates to customers. It’s built against WooCommerce order webhooks but can be adapted to Shopify or other e-commerce platforms that provide billing and line_items. What this Workflow Does Receives order events (Webhook / WooCommerce order.updated). Normalizes the payload into a compact object: { data: { customer, products, invoice_link } } via a Code node. Iterates items in batches (SplitInBatches) to control throughput. Cleans phone numbers (removes non-digits) and verifies WhatsApp registration using Rapiwa (/api/verify-whatsapp). Sends templated WhatsApp messages through Rapiwa (/api/send-message) for verified numbers. Logs every attempt into Google Sheets: one sheet for verified & sent rows, another for unverified & not sent rows. Uses a Wait node to throttle and loop back into the batch processor. Key Features Trigger-based automation (Webhook or WooCommerce trigger). Payload normalization and mapping via JavaScript Code nodes. Controlled batching (SplitInBatches) to avoid rate limits. Pre-send verification of WhatsApp numbers using Rapiwa. Conditional branching with the IF node to separate verified vs unverified flows. Personalized message templates that pull customer and product fields from the mapped data. Logging and audit trail stored in Google Sheets (two separate append flows). How to Use — Step-by-step Setup Add credentials in n8n Rapiwa: Create an HTTP Bearer credential and paste your Bearer token (example name used in the flow: Rapiwa Bearer Auth). Google Sheets: Create an OAuth2 credential (example: Google Sheets). WooCommerce: Add WooCommerce API credentials for the trigger (or configure Shopify credentials if adapting). Import / configure nodes in n8n Webhook (or WooCommerce Trigger): receive order payloads. Example Webhook path is present in the exported flow. Code node Format Webhook Response Data: map body.billing, body.line_items, body.payment_url into { data: { customer, products, invoice_link } }. Code node Clean WhatsApp Number: ensure the phone number is a string and strip non-digits: String(rawNumber).replace(/\D/g, ""). HTTP Request Check valid whatsapp number Using Rapiwa: POST to https://app.rapiwa.com/api/verify-whatsapp with { number }. Use the Rapiwa Bearer credential. IF If: check verification result. The flow compares {{$json.data.exists}} to "true" in the exported flow; normalize types if your API returns booleans. HTTP Request Rapiwa Sender: POST to https://app.rapiwa.com/api/send-message with number, message_type: 'text', and a templated message (see message template in the flow). Google Sheets Store State of Rows in Verified & Sent and Store State of Rows in Unverified & Not Sent Google Sheet Column Structure Create these columns exactly (the Google Sheets nodes in the flow expect these names): A Google Sheet formatted like this ➤ sample | Name | Number | Email | Address | Product Title | Product ID | Size | Quantity | Total Price | Product Image | Invoice Link | Product Status | Validity | Status | |-----------------|---------------|-------------------|--------------|------------------------------------------------|------------|------|----------|----------------|--------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|----------------|------------|----------| | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur dohs | Air Force 1 Reigning Champ Dark Grey 1:1 - 40 | 251 | 40 | 1 | BDT 5800.00 | | Invoice | on-hold | verified | sent | | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur dohs | Air Force 1 Reigning Champ Dark Grey 1:1 - 40 | 251 | 40 | 1 | BDT 5800.00 | | Invoice | on-hold | unverified | not sent | Customization Ideas Adapt the Code mapping node for Shopify payloads or other marketplaces. Iterate and include multiple products in the message instead of using products[0]. Add filters in the Code node (e.g., only process orders with total > 5000). Add fallback channels (SMS or email) for unverified numbers. Persist logs into a database for analytics and retention beyond Google Sheets. Add admin notifications (Slack, email) at the end of each run. Useful Links Dashboard:** https://app.rapiwa.com Official Website:** https://rapiwa.com Documentation:** https://docs.rapiwa.com Support & Help WhatsApp**: Chat on WhatsApp Discord**: SpaGreen Community Facebook Group**: SpaGreen Support Website**: https://spagreen.net Developer Portfolio**: Codecanyon SpaGreen

This workflow monitors product prices from BooksToScrape and sends alerts to a Discord channel via webhook when competitor's prices are lower than our prices. 🧩 Nodes Used Schedule (for daily or required schedule) If nodes (to check if checked or unchecked data exists) HTTP Request (for fetching product page ) Extract HTML (for extracting poduct price) Code(to clean and extract just the price number) Discord Webhook (send discord allerts) Sheets (extract and update) 🚀 How to Use Replace the Discord webhook URL with your own. Customize the scraping URL if you're monitoring a different site.(Sheet i used) Run the workflow manually or on a schedule. ⚠️ Important Do not use this for commercial scraping without permission. Ensure the site allows scraping (this example is for learning only).

How it works 🧠 AI-Powered News Update Bot for Zalo using Gemini and RSS Feeds This workflow allows you to build a smart Zalo chatbot that automatically summarizes and delivers the latest news using Google Gemini and RSS feeds. It’s perfect for keeping users informed with AI-curated updates directly inside Vietnam’s most popular messaging app. 🚀 What It Does Receives user messages via Zalo Bot webhook Fetches the latest articles from an RSS feed (e.g., AI news) Summarizes the content using Google Gemini Formats the response and sends it back to the user on Zalo 📱 What Is Zalo? Zalo is Vietnam’s leading instant messaging app, with over 78 million monthly active users—more than 85% of the country’s internet-connected population. It handles 2 billion messages per day and is deeply embedded in Vietnamese daily life, making it a powerful channel for communication and automation. 🔧 Setup Instructions 1. Create a Zalo Bot Open the Zalo app and search for "Zalo Bot Creator" Tap "Create Zalo Bot Account" Your bot name must start with "Bot" (e.g., Bot AI News) After creation, Zalo will send you a message containing your Bot Token 2. Configure the Webhook Replace [your-webhook URL] in Zalo Bot Creator with your n8n webhook URL Use the Webhook node in this workflow to receive incoming messages 3. Set Up Gemini Add your Gemini API key to the HTTP Request node labeled Summarize AI News Customize the prompt if you want a different tone or summary style 4. Customize RSS Feed Replace the default RSS URL with your preferred news source You can use any feed that provides timely updates (e.g., tech, finance, health) 🧪 Example Interaction User: "What's new today?" Bot: "🧠 AI Update: Google launches Gemini 2 with multimodal capabilities, revolutionizing how models understand text, image, and code..." ⚠️ Notes Zalo Bots currently do not support images, voice, or file attachments Make sure your Gemini API key has access to the model you're calling RSS feeds should be publicly accessible and well-formatted 🧩 Nodes Used Webhook HTTP Request (Gemini) RSS Feed Read Set & Format Zalo Message Sender (via API) 💡 Tips You can swap Gemini with GPT-4 or Claude by adjusting the API call Add filters to the RSS node to only include articles with specific keywords Use the Function node to personalize responses based on user history Built by Nguyen Thieu Toan (Nguyễn Thiệu Toàn) (https://nguyenthieutoan.com). Read more about this workflow by Vietnamese: https://nguyenthieutoan.com/share-workflow-n8n-zalo-bot-cap-nhat-tin-tuc/