Workflow Templates

Automate user consent collection with a seamless workflow that captures form submissions, stores them securely, and sends professional AI-generated confirmation emails 📧🤖. This template streamlines compliance by logging every consent action directly into Google Sheets while also notifying your internal team instantly through Slack. With built-in Azure OpenAI email generation, every user receives a personalized, secure, trust-building confirmation without manual intervention. Perfect for DPDP/GDPR-aligned consent management systems. What This Template Does Receives user consent submissions via a Webhook trigger 🚀 Extracts name, email, version, and timestamp for structured processing 🔍 Saves or updates the record in Google Sheets for audit and compliance tracking 📄 Generates a responsive HTML thank-you email using Azure OpenAI 🤖 Formats the output into a clean subject + email body via a Code node 🧩 Sends the user a confirmation email via SMTP 📧 Converts HTML into a Slack-friendly message for internal alerts 🔔 Posts the formatted notification to your Slack channel for instant visibility 💬 Key Benefits ✅ Fully automated consent logging—no manual tracking required ✅ AI-generated HTML emails ensure professional, consistent communication ✅ Real-time Slack alerts keep your team informed instantly ✅ Compliant with DPDP/GDPR consent tracking best practices ✅ Easy to integrate into any website or mobile app via webhook ✅ Ensures audit-ready records with accurate timestamps and version history Features Webhook trigger for instant consent capture Google Sheets integration for centralized data storage Azure OpenAI-powered HTML email generation SMTP email delivery with dynamic fields Slack API integration for real-time notifications Custom JS transformations for email + Slack formatting Timestamp automatic insertion for compliance Requirements Google Sheets OAuth2 credentials Azure OpenAI API key SMTP email credentials (e.g., Gmail, Outlook, SendGrid) Slack API credentials A consent form or preference center that can send POST requests Target Audience SaaS founders needing user consent management EdTech, HealthTech, FinTech, and compliance-heavy platforms Data Protection & Privacy teams (DPDP/GDPR compliance) Automation consultants building consent or preferences centers If you want, I can also generate: ✅ Landing page text for this template ✅ A companion version for "Consent Withdrawal" ✅ A website prompt for Lovable to auto-generate UI/buttons

This workflow automates inventory management and predictive reordering for Shopify stores. It integrates Shopify, Google Sheets, and Slack to monitor inventory levels, calculate dynamic reorder points based on sales velocity, and automate supplier communication. The workflow helps prevent stockouts, reduces overstock, and streamlines the purchase order process with minimal manual intervention. Key Features Automated Inventory Monitoring:** Fetches real-time inventory, product, and order data from Shopify and Google Sheets. Predictive Reordering:** Calculates sales velocity and dynamic reorder points for each SKU. Supplier Communication:** Automatically generates and sends purchase orders (POs) to suppliers via email or API. Multi-Warehouse Logic:** Checks for possible stock redistribution before triggering new orders. Business Rule Enforcement:** Applies custom rules (MOQ, budget, business days, approval thresholds). Real-Time Alerts:** Notifies stakeholders via Slack about critical stock risks and slow-moving products. Comprehensive Logging:** Updates purchase order logs and analytics dashboards for full traceability. How to Configure Shopify Integration Create a Shopify Private App and obtain your API credentials (API key, password, and store URL). In n8n, set up Shopify credentials using these details. Google Sheets Integration Prepare three Google Sheets: Inventory Master: Contains SKU, product details, and ideal stock levels. Suppliers: Contains supplier contact information and SKU mapping. Purchase Order Log: Tracks all generated POs. Share these sheets with the Google account connected to n8n and set up Google Sheets credentials. Slack Integration Create a Slack Incoming Webhook for the channel where you want to receive alerts and summaries. Add the webhook URL to the relevant Slack nodes in the workflow. Supplier Communication For email: Configure the Email node with your SMTP credentials and supplier email addresses. For API: Set up HTTP Request nodes with supplier API endpoints and authentication as required. Workflow Parameters Adjust configuration nodes to set business rules such as: Reorder point multipliers Safety stock days Budget limits Minimum order quantities (MOQ) Approval thresholds Scheduling The workflow is set to run hourly by default. Adjust the trigger node as needed. Testing Run the workflow manually with test data to ensure all integrations and logic work as expected before enabling automation. How It Works Trigger: Runs automatically on an hourly schedule. Configuration: Sets business parameters (Shopify URL, reorder multipliers, safety stock days, budget, etc.). Data Collection: Retrieves inventory, product details, and recent orders from Shopify. Reads inventory master, supplier list, and PO log from Google Sheets. Data Merging: Combines all sources into a unified SKU-level dataset. Sales Velocity Calculation: Computes 7/30-day sales velocity for each SKU. Dynamic Reorder Point: Calculates reorder points based on sales velocity, lead time, and safety stock. Reorder Check: Identifies SKUs below their reorder point. Stockout Risk Assessment: Flags SKUs at high risk of stockout and sends Slack alerts. Warehouse Redistribution: Attempts to balance stock between warehouses before reordering. Supplier Data Enrichment: Adds supplier info and checks availability. Business Rule Checks: Validates business day, MOQ, promotional periods, budget, and approval needs. Order Calculation: Determines optimal order quantities and prioritizes by profitability. PO Structuring: Prepares PO line items and context for supplier communication. PO Dispatch: Sends PO via email or API to the supplier. PO Confirmation & Logging: Waits for confirmation and updates the PO log in Google Sheets. Slow-Mover Detection: Identifies slow-selling SKUs and sends actionable Slack suggestions. Inventory Update: Syncs inventory changes back to Shopify. Analytics & Reporting: Updates dashboards, scenario planning sheets, and accounting systems. Daily Summary: Aggregates and sends a daily activity summary to Slack. Example Use Case A Shopify retailer uses this workflow to automate inventory management. Every hour, the workflow checks current stock and sales trends, predicts which products are at risk of running out, and automatically creates purchase orders for suppliers. If a product is selling slowly, the system notifies the team with suggestions for discounts or bundling. All actions are logged and summarized daily, ensuring the team stays informed and inventory is always optimized. Prerequisites Shopify account with API access Google Sheets with inventory, supplier, and PO log sheets Slack workspace and webhook for notifications Supplier email/API endpoints for PO dispatch Limitations & Notes Customization may be required for specific business rules or supplier integrations. Ensure API credentials and sheet structures match the workflow’s configuration. Multi-warehouse logic assumes accurate warehouse-level inventory data. If you need further customization or have specific requirements for your business logic, adjust the configuration and node parameters accordingly.

Automatically discover, analyze, and report the most viral TikTok and Instagram videos in your niche every day. This workflow leverages AI and Apify to help you stay ahead of social media trends. What This Workflow Does Scrapes trending videos** from TikTok and Instagram using Apify. Filters and analyzes** content based on engagement, growth rate, and recency. Uses AI (OpenAI GPT-4 Vision & GPT-4)** to provide visual and trend analysis for each video. Identifies “super viral” content** and sends instant Slack alerts. Saves results to Google Sheets** and sends a daily email report with the top trends. Use Cases Social Media Managers:** Instantly spot viral trends to inform your content strategy. Content Creators:** Get daily inspiration from the fastest-growing videos in your niche. Marketing Teams:** Monitor competitor performance and adapt to new trends quickly. Agencies:** Automate trend research and reporting for multiple clients. How to Configure Workflow Configuration: Add your API keys, set engagement thresholds, and adjust main workflow settings. Search Config: Enter your keywords, hashtags, language, and time window for content discovery. Scrape TikTok & Scrape Instagram: Set up your Apify API credentials and endpoints. Save to Google Sheets: Connect your Google account and select the destination spreadsheet. Send Daily Digest Email: Add the recipient’s email address and customize the message if needed. Send Super Viral Alert (optional): Configure your Slack webhook for instant notifications. > Tip: Test each integration and double-check your credentials before activating the workflow. Requirements Apify account and API token Google account for Sheets integration OpenAI API key (for AI analysis) Slack webhook URL (optional, for viral alerts) Stay ahead of the curve and never miss a viral trend again!

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.

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.

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.

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!

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

Who’s it for Recruiting agencies, executive search firms, and in-house talent teams that want to automate candidate sourcing and prequalification. Instead of spending hours searching, scoring, and writing outreach, this workflow turns any job description into a ready-to-use shortlist with personalized messages. Youtube Walkthrough What it does (How it works) This workflow takes a job description (title, description, and location) and runs a complete recruiting automation pipeline: Normalize job titles** and generate variations to widen search coverage. Search candidates** in Apollo (or your CRM / database of choice). Remove duplicates** to keep clean lists. Score candidates** with AI (0–5) and provide concise reasoning across experience, industry, and seniority. Enrich LinkedIn profiles** (name, title, image, location, experience). Create structured candidate assessments** (summary, alignment, red flags, positives). Generate outreach messages** (email + LinkedIn DM) tailored to the candidate. Write to Airtable** for job/candidate tracking and downstream automation. Everything is plug-and-play, with no manual searching or copy-pasting required. Requirements n8n (Cloud or self-hosted) Airtable account + API access Apollo API or your preferred candidate source LLM provider: OpenAI or Anthropic LinkedIn enrichment API (RapidAPI, Apify, etc.) > ⚠️ Do not hardcode API keys in HTTP nodes. Always use Credentials in n8n. Airtable table specifications Create one base (e.g., Candidate Search – From Job Description) with two tables: Jobs Table Job Title (text) Job Description (long text) Job Location (text) Candidates (linked to Candidates table) Candidates Table Core fields: Name, LinkedIn URL, Job Title, Location, Image URL, Job Searches (linked) Assessment fields: Summary Fit Score, Executive Summary, Title Alignment, Skill Alignment, Industry Alignment, Seniority Alignment, Company Type Alignment, Educational Alignment, Potential Red Flags, Positive Signals, Final Recommendation, Next Steps Suggestion Outreach fields: Email Subject, Email Body, LinkedIn Message How to set up Connect credentials Add Airtable, Apollo/CRM, and OpenAI/Anthropic credentials under n8n Credentials. Create Airtable base/tables Follow the above spec for Jobs and Candidates. Match field names exactly to avoid mapping errors. Configure the trigger The workflow starts from a Form/Webhook node. It captures: Job Title (required) Job Description (required) Location (required) Target Companies (optional, comma-separated domains) Job title mutation The workflow uses an AI node to normalize the job title and generate up to 5 variations for broader candidate searches. Candidate search Apollo (or your CRM API) is queried with the generated titles and location filters. Results are deduped. AI scoring & structuring Candidates are scored 0–5 with clear reasoning (experience, industry, seniority, general fit). Profiles are formatted into structured JSON for Airtable. LinkedIn enrichment Enrichment API fetches missing data (geo, image, job history). Candidate assessment An AI model produces a full recruiter-ready evaluation (fit summary, strengths, red flags). Outreach generation The workflow drafts a concise cold email (<75 words) and LinkedIn DM (<60 words), consultative in tone. Write to Airtable All jobs and candidates (with assessments and outreach messages) are logged for review and integration. How to customize Swap Apollo with your CRM** (Greenhouse, Bullhorn, etc.). Adjust scoring prompts** to match your niche (sales, engineering, healthcare). Add custom filters** for target companies or industries. Change outreach tone** to align with your brand voice. Limit by score** (e.g., only push candidates with score ≥4). Security & best practices Store all keys in n8n Credentials (never in nodes). Use Set nodes to centralize editable variables (title, location, filters). Always add sticky notes in your workflow explaining steps. Rename nodes clearly for readability. Troubleshooting No candidates found?** Loosen title variations or broaden location. Low fit scores?** Refine keywords and required skills in scoring prompts. Airtable errors?** Double-check Base ID, Table ID, and field names. API rate limits?** Enable batching/pagination and increase intervals. SEO title: Build candidate shortlists from a job description to Airtable with Apollo, AI scoring, and personalized outreach Keywords: recruiting automation, Apollo people search, candidate enrichment, AI scoring, Airtable recruiting CRM, LinkedIn outreach, n8n workflow template

How It Works Automates fraud risk detection for financial transactions by analyzing real-time webhook events through AI-powered scoring. Target audience: fintech companies, payment processors, and banking teams preventing fraud losses. Problem solved: manual fraud checks are reactive and slow; automated detection catches suspicious transactions instantly. Workflow receives transactions via webhook, configures processing parameters, runs OpenAI GPT-4 fraud analysis, calculates risk scores, branches on risk level, holds high-risk transactions, alerts fraud teams, logs incidents, and documents evidence for compliance investigations. Setup Steps Configure webhook endpoint for transaction ingestion. Set OpenAI API key and fraud detection prompts. Connect Google Sheets for incident logging. Enable email alerts to fraud team distribution list. Map risk thresholds (high/low). Prerequisites OpenAI API key, webhook-capable transaction source, Gmail for alerts, Google Sheets access, incident tracking database. Use Cases Payment processors detecting card fraud, fintech platforms catching account takeovers Customization Adjust risk thresholds and scoring logic. Add phone/SMS alerts for urgency. Benefits Detects fraud within seconds, reduces financial losses by up to 90%