Workflow Templates

Automated SEO Health Monitoring & Reporting This workflow automatically monitors the SEO health of websites stored in a Google Sheet. It fetches each website’s HTML, analyzes key SEO metrics (title, meta description, H1 count, canonical, robots, performance score, etc.) and updates results back into Google Sheets. If performance is poor (<50), it sends an alert email. For healthy sites, it generates a detailed PDF report and stores it in Google Drive. Who’s it for Digital marketing teams SEO agencies Website administrators who want automated SEO health checks Businesses with multiple websites or landing pages to monitor How it works Daily Trigger – Runs every day at 9 AM. Fetch Website List – Reads website URLs from Google Sheets. Crawl Websites – Uses HTTP requests to fetch each website’s HTML. SEO Analysis – Extracts SEO-related metadata (title, meta description, H1, etc.). Health Check – Scores SEO performance based on predefined rules. Decision Node – If score < 50 → Send alert email; else → Generate full SEO report. Update Logs – Logs results back into Google Sheets. Generate PDF Reports – Converts HTML reports into PDFs via PDF.co API. Save to Drive – Stores the PDF reports in Google Drive for long-term access. How to set up Open n8n and import the workflow. Configure your Google Sheets credentials and specify the sheet containing your website URLs. Add your Gmail account to allow automated alert emails. Set up your Google Drive credentials for storing PDF reports. Obtain an API key from PDF.co and configure the HTTP Request node. Adjust the Schedule Trigger to the time that works best (default: 9 AM daily). Test the workflow with a sample domain list. Requirements n8n instance (self-hosted or cloud) Google Sheets account (to store website URLs and logs) Gmail account (for sending alerts) Google Drive account (to save SEO reports) PDF.co API Key (for HTML → PDF conversion) How to customize Change performance threshold**: Modify the IF node condition (default <50). Custom SEO rules**: Edit the “SEO Health Check” Function node to add/remove checks (e.g., missing schema tags, page load times). Different output storage**: Replace Google Drive with Dropbox, S3 or OneDrive. Alternate notification channels**: Swap Gmail with Slack, Microsoft Teams or Telegram. Add-ons Send Slack/Teams notifications for low scores. Add PageSpeed Insights API for performance scoring. Generate weekly summary reports per domain. Integrate with Notion/Confluence to log SEO health history. Use Case Examples An SEO agency monitors 100+ client websites daily and sends alerts when a site has poor SEO signals. A company’s marketing manager gets a daily SEO health PDF report stored in Drive. A SaaS product team automatically logs performance changes for each release. Common Troubleshooting | Issue | Possible Cause | Solution | | ------------------------------------ | ------------------------------------------------ | --------------------------------------------------------------------------- | | Workflow fails at HTTP Crawl | Website blocks requests / timeout | Increase timeout in Set Config node or add retry logic. | | Always returns https://example.com | Missing canonical / OG tags in HTML | Enhanced code now infers from JSON-LD or domain detection. Update analyzer. | | PDF not generated | Invalid API key or wrong endpoint in PDF.co node | Verify PDF.co API key and endpoint URL. | | Email not sending | Gmail credentials not set or blocked | Reconnect Gmail in n8n credentials manager. | | Google Sheet not updating | Wrong column mapping in Update Sheet node | Check node mapping: domain column vs performance/date columns. | | Google Drive upload fails | Missing folder permissions | Ensure correct Drive folder ID and credentials. | Need Help? If you’d like assistance setting up, customizing or scaling this workflow for your use case, our n8n automation team at WeblineIndia can help you: Tailor SEO rules for your industry. Connect to additional APIs (Ahrefs, Semrush, PageSpeed). Automate weekly/monthly reporting with summary dashboards.

This n8n template demonstrates how to use AI to capture, qualify, and route inbound leads automatically from email or web forms. It extracts key business information using AI, scores the lead based on your ideal customer profile, creates CRM records, notifies your team on Slack, and logs all activity—including failures—to Google Sheets. Use cases include: automating sales inboxes, qualifying form leads for agencies or SaaS products, routing high-fit prospects to the right territory owner, and keeping your sales and ops teams aligned without manual data entry. Good to know The OpenAI model is used for lead data extraction and will incur a small cost per run depending on volume. This workflow supports either Salesforce or HubSpot as the CRM system—select which one in the configuration node. You’ll need valid credentials for Gmail (or another email service), OpenAI, Slack, Google Sheets, and your chosen CRM before running. How it works Triggers: A Gmail trigger polls for new inbound emails. A Webhook node receives submissions from any online form. Both sources merge into a single pipeline. Validation: Incoming data is checked for required fields (email or text). Invalid entries are routed to the Dead Letter Queue (DLQ) for review. AI Extraction: The OpenAI node extracts structured fields like company name, size, industry, role, region, problem statement, and budget signals from free-form text. Parsing & Scoring: The AI output is parsed, then a code node calculates a 0–100 lead score based on transparent criteria—industry, size, role, problem clarity, and budget mentions. It also assigns a lead tier (Hot, Warm, Cold, Unqualified). CRM Routing: Depending on your configuration, the workflow creates a Salesforce lead (default) or can be easily adapted for HubSpot. Territory or CRM owner routing can be extended here. Slack Notification: A rich Slack message summarizes the lead score and reasoning and includes a “Create intro email” button for quick action. Logging: All successful leads are logged to Google Sheets for reporting. Any failed or invalid leads are logged separately to the DLQ tab for auditing. How to use Configure your credentials for Gmail, OpenAI, Slack, Google Sheets, and your CRM. Open the Workflow Configuration node and fill in your target industries, buyer roles, company size, Slack channel ID, Google Sheets URL, and CRM choice. Create corresponding tabs in your Google Sheet for Leads and DLQ. Test by sending a sample email or form submission, then watch the workflow extract, score, route, and notify automatically. Requirements OpenAI account for text extraction Gmail (or other email provider) for the email trigger Slack for lead notifications Google Sheets for logging leads and DLQ entries Salesforce or HubSpot account for CRM integration Customizing this workflow This template can be expanded in many ways: Add HubSpot routing on the first Switch output. Integrate a Slack button handler to auto-generate intro emails. Add retry and backoff logic for resilience. Modify the scoring rubric in the code node to match your unique ICP. Connect additional sources, such as LinkedIn forms or landing page builders, for omnichannel lead capture.

Meeting Minutes & Action Item Tracker Fully automated meeting documentation workflow that uses AI to transform raw transcripts into professional PDFs and actionable tasks. Features AI-powered summary generation (GPT-4) Automatic action item extraction with assignees, deadlines, and priorities Professional PDF generation with custom styling Multi-channel distribution (Email, Slack, Google Drive) Task creation in Google Tasks Personalized notifications to each assignee Deadline tracking and urgency detection Setup Instructions REQUIRED CREDENTIALS: OpenAI API - Get from Gmail OAuth2 - Connect your Google account Google Drive OAuth2 - Same Google account Google Tasks OAuth2 - Same Google account Slack OAuth2 - Connect your workspace htmlcsstopdf API - Get from CONFIGURATION STEPS: WEBHOOK: Note your webhook URL after activation EMAIL NODES: "Email All Participants": Uses participants array from input "Send Individual Task Emails": Change @yourcompany.com to your domain GOOGLE DRIVE: Select folder where PDFs should be stored Recommended: Create "Meeting Minutes" folder SLACK: Select channel for team notifications Recommended: Create #meeting-notes channel GOOGLE TASKS: Select task list where tasks should be created Default list works fine TESTING: Use the webhook URL with sample meeting data Check execution log for any errors Verify PDF in Google Drive Check emails were sent Confirm tasks created in Google Tasks Example Input Format POST : Headers: Content-Type: application/json Body: { "title": "Weekly Team Standup", "date": "2025-09-29", "participants": [ "john@company.com", "sarah@company.com", "joe@company.com" ], "duration": "30 minutes", "transcript": "John started the meeting by discussing the progress on the API development. Sarah mentioned that she's working on the dashboard and needs to prepare mockups by Thursday. The team agreed that Sarah will review the API documentation before the client demo on Friday. Akshita confirmed she finished the database schema redesign and needs to schedule a meeting with DevOps team by next Monday to discuss production deployment." } This will generate: Professional PDF with summary and action items Emails to all participants Individual task emails to John, Sarah, and Joe Tasks in Google Tasks Slack notification Output After execution, you'll get: Professional PDF stored in Google Drive Email sent to all participants with meeting overview Individual emails to each assignee with their tasks Slack notification with summary and download link Tasks created in Google Tasks with deadlines CUSTOMIZATION: Modify PDF styling in "Generate PDF Document" node Adjust email templates in Gmail nodes Change AI prompts in OpenAI nodes for different output Modify priority/deadline logic in "Parse and Enrich Data" Troubleshooting Workflow stops at validation: Ensure transcript has >50 words Check that webhook payload is correctly formatted No PDF generated: Verify htmlcsstopdf API credentials Check API usage limits Tasks not created: Verify deadline format is YYYY-MM-DD Check Google Tasks API connection Emails not sending: Confirm Gmail OAuth2 is connected Check that email addresses are valid Support For issues or questions, visit the n8n community forum. License MIT License - Feel free to modify and share!

Unleash the power of AI to automate your job search, tailor your applications, and boost your chances of landing your dream job! This comprehensive workflow handles everything from finding relevant job postings to generating personalized resumes and cover letters. Use cases are many: Automate your entire job application process:** Spend less time searching and more time preparing for interviews. Tailor your resume and cover letter for every application:** Maximize your ATS compatibility and stand out to recruiters. Efficiently track your applications:** Keep all your job search activities organized in one place. Discover new job opportunities:** Leverage the Adzuna API to find relevant listings. Good to know: Free Adzuna API:* This workflow utilizes the *free Adzuna API, making job search capabilities accessible without initial cost. OpenRouter Chat Model Costs:** AI model usage (for resume rewriting and cover letter generation) will incur costs based on the OpenRouter pricing model. Please check OpenRouter's official website for updated pricing information. Model Availability:** The AI models used may have geo-restrictions. If you encounter a "model not found" error, it might not be available in your country or region. How it works: Webhook Trigger: The workflow is initiated via a webhook, allowing you to trigger it manually or integrate it with other systems (e.g., a form submission with your desired job title and resume). Resume Extraction: Your uploaded resume (e.g., PDF) is automatically extracted into a readable text format. Job Search (Adzuna API): Using the provided job title, the workflow queries the Adzuna API to fetch relevant job postings. Job Filtering: Duplicate job listings are filtered out to ensure you receive unique opportunities. Job Info Extraction: Key details like job description, company name, and job URL are extracted from each posting. Skills Extraction (AI): An AI model (OpenRouter) analyzes the job description to identify the top skills and qualifications required. Resume Match Scoring (AI): Your resume is compared against the extracted job skills by an AI model, generating a compatibility score (1-5). Conditional Resume & Cover Letter Generation: If the resume match score is satisfactory (≥ 3): Tailored Resume Generation (AI): An AI model rewrites your resume, specifically highlighting the skills and experience most relevant to the target job, in an ATS-friendly and human-readable JSON/HTML format. Personalized Cover Letter Generation (AI): A custom cover letter is drafted by AI, uniquely tailored to the job description and your newly optimized resume, generated as well-formatted HTML. Google Sheets Integration: The generated cover letter, tailored resume, job URL, and application status are automatically updated in your designated Google Sheet for easy tracking. Gmail Notification: A personalized email containing the generated cover letter, tailored resume, and a direct link to the job posting on Adzuna is sent to your specified email address. Webhook Response: A final text response is sent back via the webhook, summarizing the sent application materials. How to use: Manual Trigger:** The workflow is set up with a manual trigger (Webhook) for initial testing and demonstration. You can easily replace this with an n8n form, a scheduled trigger, or integrate it into your existing tools. Input:** Provide your desired job search keyword and your resume (e.g., as a PDF) to the webhook. Review & Apply:** Review the AI-generated cover letter and tailored resume sent to your email, then proceed to apply for the job using the provided Adzuna link. Requirements: n8n Instance:** A running n8n instance (self-hosted or cloud). Adzuna API Key:** A free Adzuna API key (easily obtainable from their developer portal). OpenRouter Account:** For AI model access (costs apply based on usage). Google Sheets Account:** To store and track your job applications. Gmail Account:** To send automated application emails. Customizing this workflow: This workflow is highly customizable. You can: Integrate with other job boards (e.g., LinkedIn, Indeed) using their APIs. Add more sophisticated AI models or custom prompts for even finer control over resume and cover letter generation. Connect to other services for CRM, calendar management, or applicant tracking. Implement different filtering criteria for job postings. Expand the data stored in your Google Sheet (e.g., interview dates, feedback). Start automating your job search today and streamline your path to career success!

Overview This workflow automates your entire sales outreach process across LinkedIn, Email, and WhatsApp using AI to create hyper-personalized messages for each prospect. Instead of spending hours crafting individual messages, the workflow analyzes your lead data and generates customized connection requests, emails, and WhatsApp messages that feel genuinely personal and researched. The workflow includes a built-in approval mechanism, so you can review all AI-generated messages before they're sent, ensuring quality control while still saving massive amounts of time. How It Works The workflow follows a seven-step process: Step 1: Data Collection The workflow starts by reading your lead data from a Google Sheet. Your sheet should contain information about each prospect including their name, title, company, industry, technologies they use, and any other relevant details that can be used for personalization. Step 2: Batch Processing To prevent overwhelming APIs and ensure smooth operation, the workflow processes leads in batches. Each lead's complete data is prepared and formatted for the AI agent to analyze. Step 3: AI Personalization This is where the magic happens. The AI agent receives all the prospect data and generates three distinct messages: A LinkedIn connection request (under 300 characters) that references their specific role, company, or industry A professional HTML email that demonstrates you've researched their business and explains how you can help A casual WhatsApp message that's friendly and approachable The AI is instructed to make these messages sound completely human, never generic or templated. Step 4: Data Cleanup and Storage The AI's output is parsed and cleaned up, then written back to your Google Sheet in separate columns. This creates a permanent record of all generated messages for your review. Step 5: Manual Approval Before anything gets sent, you receive an email asking for your approval. You can review all the generated messages in your Google Sheet, make any edits if needed, and then approve or reject the batch. This ensures you maintain full control over what goes out. Step 6: LinkedIn Automation Once approved, the workflow triggers your Phantombuster agent to send LinkedIn connection requests using the AI-generated messages. Phantombuster handles the actual LinkedIn interaction safely within their platform's limits. Step 7: Email and Notification Delivery Finally, the workflow sends out the personalized emails via Gmail and optionally notifies you via Telegram for each message sent. This happens sequentially to respect rate limits and maintain deliverability. Setup Requirements Before you can use this workflow, you'll need to set up several accounts and gather credentials: Essential Services: An n8n instance (cloud or self-hosted) A Google account with Google Sheets access A Gmail account for sending emails An OpenAI account with API access (for the AI agent) Phantombuster account (for LinkedIn automation) Optional Services: Telegram account and bot (for notifications) Credentials You'll Need: Google Sheets OAuth2 credentials Gmail OAuth2 credentials OpenAI API key Phantombuster API key and agent ID Telegram bot token and chat ID (if using notifications) How to Use This Workflow Initial Setup: Import this workflow into your n8n instance Add all required credentials in n8n's credential manager Create your Google Sheet with the following columns at minimum: First Name, Last Name, Title, Company Name, Personal Email, Industry, Website. Add three additional columns for output: Connection, AI Email, AI Whatsapp Message Copy your Google Sheet ID from the URL and update it in all Google Sheets nodes Open the AI Agent node and update the prompt with your personal information: your name, title, email, and LinkedIn URL Update the email addresses in the Gmail nodes to your actual email addresses Configure your Phantombuster agent for LinkedIn and add the API key and agent ID Running the Workflow: Add your lead data to the Google Sheet (you can start with just 2-3 leads for testing) Click "Execute Workflow" in n8n to start the process Wait for the AI to generate messages (this takes a few seconds per lead) Check your email for the approval request Review the AI-generated messages in your Google Sheet Reply to the approval email with your decision If approved, the workflow will automatically send LinkedIn requests, emails, and WhatsApp messages Best Practices: Start small. Process 5-10 leads at a time initially to test the quality of AI-generated messages and ensure everything works correctly. Once you're confident in the output, you can scale up to larger batches. Monitor your results. Keep track of response rates in your Google Sheet and adjust the AI prompt if certain types of messages aren't performing well. Respect rate limits. Gmail allows 100-500 emails per day depending on your account type, and LinkedIn has strict limits on connection requests (typically 100 per week through automation tools). Stay well within these limits to avoid account restrictions. Customizing This Workflow The workflow is designed to be highly customizable to fit your specific use case: Personalizing the AI Prompt: The most important customization is in the AI Agent node's prompt. You can modify it to: Emphasize different aspects of your value proposition Change the tone from formal to casual or vice versa Include specific pain points relevant to your target industry Add your company's unique selling points Adjust message length and structure Modifying the Output: You can change what the AI generates by editing the prompt. For example, you might want: Different message types (Twitter DMs instead of WhatsApp) Multiple email variations for A/B testing Follow-up message sequences Industry-specific templates Adding Features: The workflow can be extended with additional nodes: Add time delays between sends to appear more natural Include condition checks to segment leads by industry or company size Connect to your CRM to automatically log activities Add sentiment analysis to filter out negative-sounding messages Implement response tracking by monitoring your inbox Changing Tools: If you prefer different services, you can swap out nodes: Replace Phantombuster with other LinkedIn automation tools Use SendGrid or Mailgun instead of Gmail for higher volume Add Slack notifications instead of Telegram Connect to WhatsApp Business API for official messaging Data Source Alternatives: Instead of Google Sheets, you could: Connect directly to your CRM (HubSpot, Salesforce, Pipedrive) Use Airtable as your database Pull data from CSV files uploaded to cloud storage Integrate with lead generation tools like Apollo or Hunter Tips for Success The quality of your AI-generated messages depends heavily on the data you provide. The more information you have about each prospect (their role, company size, technologies used, recent news, pain points), the more personalized and effective the messages will be. Regularly review and refine your AI prompt based on the responses you're getting. If prospects aren't responding, your messages might be too sales-focused or not personal enough. Adjust the prompt to make messages feel more consultative and helpful. Don't send to your entire list at once. Even with approval gates, it's wise to test with small batches, measure results, iterate on your approach, and then scale up gradually. Always comply with email and LinkedIn best practices. Never spam, always provide value in your outreach, respect people's time and privacy, and make it easy for them to opt out if they're not interested. This workflow is a powerful tool that can save you hours of work while actually improving the quality of your outreach through AI-powered personalization. Use it responsibly and watch your response rates improve.

Who's it for This workflow is perfect for individuals, small businesses, or households who need to: Automatically process and categorize expense receipts Extract structured data from invoices and receipts using AI Store receipts in multiple locations (Google Drive and S3) Send automated email notifications with expense details Send documents to accounting systems via email hooks How it works This comprehensive expense processing workflow combines AI-powered document analysis with automated file management and notifications. Here's the complete flow: Form Submission: Users submit expenses through a web form with receipt upload and category selection (Personal, Business, or Shared/Home) AI Document Processing: The workflow extracts text from PDF receipts using OCR, then uses Google Gemini AI to parse and structure the data into a standardized JSON format including vendor details, amounts, dates, and categorization Smart Routing: Based on the expense category, receipts are automatically routed to different processing paths with category-specific folder organization Multi-Destination Storage: Receipts are uploaded to: Google Drive (organized by year/month folders) S3 cloud storage buckets Different destinations based on expense type Email Notifications: Sends formatted HTML email notifications with complete expense details and links to stored receipts Accounting System Integration: Automatically forwards business expenses to accounting systems via email hooks (customizable per user requirements) Requirements Credentials needed: Google Gemini API**: For AI-powered document analysis Google Drive OAuth2**: For personal and business drive access Gmail OAuth2**: For sending email notifications S3 Storage**: For cloud backup (AWS S3, Wasabi, etc.) Services used: Google Drive (multiple accounts supported) Google Gemini AI Gmail S3-compatible storage Form trigger webhook How to set up Step 1: Configure Credentials Set up Google Gemini API credentials in n8n Configure Google Drive OAuth2 for both personal and business accounts Add Gmail OAuth2 credentials Set up S3 storage credentials Step 2: Update Configuration Replace all placeholder values: YOUR_GEMINI_CREDENTIAL_ID with your Gemini credential ID YOUR_PERSONAL_GDRIVE_CREDENTIAL_ID with personal Drive credential YOUR_BUSINESS_GDRIVE_CREDENTIAL_ID with business Drive credential YOUR_GMAIL_CREDENTIAL_ID with Gmail credential YOUR_S3_CREDENTIAL_ID with S3 credential Update Google Drive folder structure: Replace YOUR_BUSINESS_DRIVE_ID and YOUR_SHARED_DRIVE_ID with actual drive IDs Update the JavaScript code in the three Code nodes with your actual folder mapping Configure email addresses: Replace user@example.com with your notification email Replace receipts@paperless-service.com with your accounting system's email hook (this is a mail hook for uploading documents to small business accounting systems - can be modified per user requirements) Update S3 bucket names: Replace business-expenses, personal-expenses, and shared-expenses with your bucket names Step 3: Set Up Folder Structure Create organized folder structures in your Google Drives: Drive Root/ ├── 2024/ │ ├── January/ │ ├── February/ │ └── ... (all months) ├── 2025/ │ ├── January/ │ └── ... (all months) └── 2026/ └── ... (all months) Step 4: Test the Workflow Activate the workflow Submit a test expense through the form Verify files are uploaded to correct locations Check email notifications are received How to customize the workflow Expense Categories Modify the form dropdown options and conditional logic to add/remove expense categories: Edit the "On form submission" node form fields Update the IF condition nodes for routing Add new processing paths as needed AI Processing Schema Customize the structured output parser schema to extract different fields: Modify the JSON schema in the "Structured Output Parser" node Update the AI system prompt for different extraction requirements Add new fields for specific business needs Storage Destinations Add or modify storage locations: Duplicate upload nodes for additional cloud services Modify folder organization logic in Code nodes Add new conditional routing for different storage rules Email Templates Customize the HTML email template: Edit the email message content in the Gmail node Add/remove expense fields in the table Modify styling and branding Folder Organization Update the JavaScript code in Code nodes to match your folder structure: Modify the CSV data with your actual folder IDs Change the date-based organization logic Add custom folder naming conventions Integration Extensions Extend the workflow with additional integrations: Add Slack notifications Connect to accounting software (QuickBooks, Xero) Integrate with expense management platforms Add approval workflows for business expenses

Jotform Lead Qualification & Distribution System Transform lead chaos into systematic qualification and instant routing - achieving 5-minute response times, 300% conversion increase, and eliminating sales team conflicts through AI-powered BANT scoring and intelligent territory assignment. What This Workflow Does Revolutionizes lead management with AI-driven qualification and automated distribution to the right sales rep: 📝 Intelligent Lead Capture - Jotform collects complete lead profile including budget, timeline, and pain points 🤖 AI BANT Scoring - GPT-4 evaluates leads across Budget, Authority, Need, Timeline (0-100 score) 🎯 Smart Routing - Automatically assigns leads based on score, territory, industry expertise, and workload 💼 Instant CRM Creation - Creates detailed contact records in HubSpot/Salesforce with full context 📧 Dual Notifications - Sales rep gets detailed brief, lead receives professional confirmation 📊 Complete Tracking - Google Sheets logging enables performance analysis and conversion metrics 🔥 Priority Tiering - Hot leads (75+) go to senior reps, warm to mid-level, cold to SDRs 💡 Pre-Written Talking Points - AI provides conversation starters based on lead pain points 🚀 Zero Manual Work - End-to-end automation from form submission to first contact Key Features AI Lead Qualification Engine: GPT-4 analyzes every lead using BANT framework with 25-point scoring per category (Budget, Authority, Need, Timeline) Intelligent Territory Routing: Matches leads to sales reps based on geography, industry expertise, deal size capacity, and current workload Real-Time CRM Integration: Creates fully populated contact records in HubSpot, Salesforce, or Pipedrive with AI insights Instant Rep Notifications: Beautiful HTML emails with complete lead profile, BANT breakdown, talking points, and recommended next steps Lead Confirmation Emails: Professional auto-responses set expectations and introduce assigned account executive Conversion Probability Scoring: AI estimates likelihood of close based on BANT signals and pain severity Deal Value Estimation: Automatically calculates potential deal size based on company size and budget range Red Flag Detection: AI identifies concerns (budget constraints, wrong decision-maker, competitor lock-in) Competitor Vulnerability Assessment: Evaluates how easily lead can switch from current solution Opportunity Size Classification: Tags leads as Small/Medium/Large/Enterprise for proper resource allocation 24-Hour SLA Monitoring: Hourly checks identify uncontacted leads and escalate to sales management Complete Audit Trail: Every lead logged to Google Sheets with timestamps, scores, and assignments for analytics Perfect For B2B SaaS Companies: Fast-growing software companies with high lead volume (100+ leads/month) Technology Services: IT consulting, MSPs, and technology solution providers Enterprise Sales Teams: Organizations with complex products requiring senior rep expertise Professional Services: Law firms, accounting firms, consulting practices with territory-based teams Manufacturing: Industrial equipment sales with industry-specific expertise requirements Healthcare Tech: Medical software and equipment sales with compliance considerations Financial Services: Wealth management, insurance, and fintech with regulatory requirements Marketing Agencies: Digital marketing and advertising agencies qualifying client prospects What You'll Need Required Integrations Jotform - Lead capture form (free tier works) Create your form for free on Jotform using this link OpenAI API - GPT-4 for AI BANT scoring (~$0.20-0.40 per lead) Gmail - Automated notifications to sales reps and leads Google Sheets - Lead tracking database and analytics CRM System - HubSpot, Salesforce, or Pipedrive (via API) Optional Integrations Slack - Real-time lead notifications to sales channel Calendar Integration - Auto-schedule follow-up calls Quick Start Import Template - Copy JSON and import into n8n Add OpenAI Credentials - Set up OpenAI API key (GPT-4 required for best BANT analysis) Create Jotform Lead Capture Form: Company Name (q3_companyName) Contact Name (q4_contactName) Email (q5_email) Phone (q6_phone) Company Size (q7_companySize) - dropdown: 1-10, 11-50, 51-200, 201-500, 500+ Budget Range (q8_budgetRange) - dropdown: <$10K, $10K-$25K, $25K-$50K, $50K-$100K, $100K+ Timeline (q9_timeline) - dropdown: Immediate, 1-3 months, 3-6 months, 6+ months Industry (q10_industry) - dropdown or text Current Solution (q11_currentSolution) - text area Pain Points (q12_painPoints) - text area Configure Gmail - Add Gmail OAuth2 credentials (same for all Gmail nodes) Setup Sales Team Routing: Edit "Intelligent Routing Logic" node Update salesTeam object with your actual sales reps Configure territories, industries, and deal size thresholds Configure CRM Integration: Choose your CRM (HubSpot shown, easily adapted for Salesforce/Pipedrive) Add CRM API credentials Map custom fields as needed Setup Google Sheets: Create spreadsheet with "Lead_Tracking" sheet Replace YOUR_GOOGLE_SHEET_ID in workflow (3 places) Columns auto-populate on first submission Customize Email Templates: Update company name, phone, website URLs Adjust branding colors if desired Set Up Escalation: Update sales manager email in escalation node Adjust 24-hour SLA threshold if needed Test Workflow - Submit test lead through Jotform Go Live - Embed form on website, share link, add to email signatures Customization Options Lead Scoring Thresholds: Adjust what constitutes Hot (75+), Warm (50-74), Cold (25-49) Territory Configuration: Add/modify territories, states, countries for rep assignment Industry Expertise: Define which reps specialize in which industries Multi-Level Routing: Add VP or director assignment for enterprise deals Custom BANT Weights: Adjust importance of Budget vs Authority vs Need vs Timeline Qualification Disqualification: Auto-reject leads below minimum score Round-Robin vs Workload: Choose between even distribution or capacity-based assignment Integration Flexibility: Swap HubSpot for Salesforce, Pipedrive, Zoho, or custom CRM Follow-Up Sequences: Add automated email nurture campaigns for different tiers Calendar Booking: Include Calendly/Chili Piper links for instant meeting scheduling Lead Source Tracking: Add UTM parameters and campaign tracking Industry-Specific Qualifying: Custom questions and scoring for different verticals Multi-Touch Attribution: Track which marketing channels produce best leads Competitor Intelligence: Add fields to track which competitor they're considering Expected Results 5-minute response time - From form submission to rep contact (vs 48+ hours manual) 300% conversion increase - Faster response + better qualification = 3x more deals Zero lead conflicts - Automated assignment eliminates sales team arguments 95% SLA compliance - 24-hour escalation ensures no leads fall through cracks 40% time savings - Reps spend time selling, not qualifying or cherry-picking leads 85% accurate routing - AI + territory logic assigns to optimal rep first time 60% reduction in unqualified meetings - BANT scoring filters out poor-fit prospects 100% lead visibility - Complete tracking from inquiry to close in Google Sheets 50% manager time savings - Automated monitoring vs manual lead assignment 2x rep productivity - Only work high-quality, properly matched leads Use Cases SaaS Company (Series B, 50 Sales Reps) Scenario: Lead submits form requesting project management software for 200-person engineering team. Budget: $50K-$100K annually. Timeline: 1-3 months. Current solution: Jira. Pain: Poor cross-team visibility. AI BANT Analysis: Budget: 23/25 (has budget, validated by company size) Authority: 22/25 (VP Engineering, decision-maker) Need: 24/25 (critical pain, expanding team needs better tools) Timeline: 20/25 (moderate urgency, current fiscal quarter) Total Score: 89/100 - HOT LEAD** Automated Response: 9:14 AM: Form submitted 9:14 AM: CRM contact created with full profile 9:15 AM: Sarah Johnson (Senior AE, specializes in Tech/Engineering tools) receives detailed notification 9:15 AM: Lead receives confirmation email introducing Sarah 9:17 AM: Sarah calls lead (3-minute response time) 9:45 AM: Discovery meeting scheduled for tomorrow 10:30 AM: Sarah updates CRM status to "Qualified Opportunity" Result: Lead converts to $85K annual contract. 3-minute response time impressed prospect (competitor took 2 days). Total sales cycle: 18 days vs 45-day average. Professional Services Firm (8 Consultants) Scenario: Small business owner (25 employees) inquires about IT consulting. Budget: <$10K. Timeline: 6+ months. Current solution: "We handle it ourselves." Pain: "Sometimes things break." AI BANT Analysis: Budget: 8/25 (insufficient budget for typical engagement) Authority: 18/25 (owner, but budget-constrained) Need: 12/25 (low pain severity, reactive not proactive) Timeline: 5/25 (no urgency, exploratory inquiry) Total Score: 43/100 - COLD LEAD** Red Flags**: Below minimum deal size, no immediate pain, DIY mentality Automated Response: Assigned to Emily Brown (SDR) for nurture track Lead receives confirmation with educational resources Emily sends follow-up email with free IT assessment offer Lead added to quarterly newsletter nurture campaign No immediate sales rep time wasted on low-probability lead Result: 6 months later, business experiences server crash. Remembers firm from newsletter. Submits new request with "Immediate" timeline and $25K budget. This time routes to senior consultant, converts to $40K managed services contract. Enterprise Software (Global Sales Team) Scenario: Fortune 500 procurement manager submits RFP for enterprise data platform. Budget: $500K+. Timeline: Immediate (Q1 deadline). 5,000 employees. Industry: Healthcare. Current: Legacy Oracle system. AI BANT Analysis: Budget: 25/25 (enterprise budget, board-approved) Authority: 20/25 (procurement, but mentions C-suite sponsorship) Need: 25/25 (critical: compliance requirements, legacy system EOL) Timeline: 25/25 (urgent: Q1 deadline 8 weeks away) Total Score: 95/100 - ENTERPRISE HOT LEAD** Key Insight**: Competitor vulnerability HIGH (legacy system, compliance pressure) Automated Response: Assigned to Michael Chen (Senior AE, Healthcare + Enterprise specialist) Sales VP automatically CC'd on notification (deal size >$250K) CRM tags: "Enterprise", "Healthcare", "RFP", "Q1 Deadline" Michael's calendar checked, existing demo moved to prioritize this lead Michael calls within 8 minutes (prospect answered, impressed) Enterprise demo scheduled for next day with solutions engineer Legal and compliance teams looped in proactively Result: Won $650K 3-year contract. 8-minute response time + pre-qualified insights helped beat 4 competitors. Sales cycle: 6 weeks (vs 6-month average for enterprise deals). Manufacturing Sales (Regional Reps) Scenario: Plant manager in Texas requests quote for industrial equipment. Company size: 200 employees. Budget: $25K-$50K. Timeline: 3-6 months. Industry: Automotive. Current: 10-year-old machinery, frequent breakdowns. AI BANT Analysis: Budget: 20/25 (has capital budget, needs approval) Authority: 19/25 (plant manager, recommends to CFO) Need: 22/25 (high: downtime costs, efficiency losses) Timeline: 18/25 (planned capital purchase, budget cycle timing) Total Score: 79/100 - HOT LEAD** Talking Points**: Focus on ROI from reduced downtime, payback period Automated Response: Territory-based routing assigns to Jessica Martinez (Southwest US, Manufacturing) Email highlights equipment efficiency ROI calculator Lead receives PDF product catalog automatically Jessica calls within 12 minutes, schedules site visit for next week Technical specialist added to meeting invite automatically Result: $42K equipment sale + $8K annual maintenance contract. Jessica's quick response and ROI-focused approach (from AI talking points) won deal over competitor who took 3 days to respond. Marketing Agency (Qualifying Client Fit) Scenario: E-commerce startup (2 employees) requests full-service digital marketing. Budget: <$10K monthly. Timeline: Immediate. Current: Doing it themselves. Pain: "Need more customers." AI BANT Analysis: Budget: 12/25 (below agency minimum of $15K monthly) Authority: 22/25 (founder, decision-maker) Need: 18/25 (need is real, but unrealistic expectations) Timeline: 20/25 (urgent, but may not understand scope) Total Score: 72/100 - WARM LEAD** Red Flags**: Budget too low, unrealistic expectations, startup risk Automated Response: Assigned to David Williams (Mid-Level AE) AI recommends: "Qualify budget realism, educate on agency pricing" David calls, explains pricing, suggests DIY consulting option ($5K) Lead appreciates transparency, opts for consulting package now Agreed to revisit full-service when reaches $100K MRR Result: $5K consulting engagement (profitable given rep level). Client reaches $100K MRR 8 months later, upgrades to $20K monthly retainer. Honesty during qualification built trust and long-term relationship. Pro Tips Response Time is King: Every minute delayed reduces conversion by 10%. Use mobile notifications for reps. BANT Customization: Adjust scoring weights based on your sales cycle. Enterprise may weight Authority higher, transactional sales may weight Timeline higher. Territory Conflicts: Use round-robin within territories to prevent cherry-picking. Track conversion rates by rep. Lead Source Attribution: Add hidden fields to Jotform to track UTM parameters and campaign sources. Continuous Improvement: Monthly review of Google Sheets data to refine AI scoring thresholds. Rep Accountability: Use 24-hour escalation data to identify training needs or workload issues. Disqualification Criteria: Add automatic rejection for competitors, students, or leads outside serviceable areas. Integration Expansion: Connect to calendar systems (Calendly, Chili Piper) for instant meeting booking. Lead Nurture Tracks: Route cold leads to marketing automation (HubSpot sequences, Mailchimp campaigns). A/B Testing: Try different form fields and AI prompts to optimize qualification accuracy. Mobile Optimization: Ensure Jotform is mobile-friendly for leads submitting from phones. Follow-Up Sequences: Add automated day 2, day 7, day 30 follow-ups for non-responsive leads. Competitive Intelligence: Track which competitors are mentioned most, adjust positioning accordingly. Budget Realism Check: AI can identify when stated budget doesn't match company size/needs. Multi-Product Routing: For companies with multiple product lines, route based on interest. Learning Resources This workflow demonstrates advanced automation: AI Agents for Complex Qualification: Multi-dimensional BANT scoring with natural language understanding Dynamic Routing Algorithms: JavaScript-based logic for territory, expertise, and workload balancing CRM API Integration: Creating fully populated contact records with custom fields Conditional Email Formatting: HTML templates with dynamic content based on lead tier Scheduled Monitoring: Cron-based checking for SLA compliance and escalation Data Aggregation: Complete lead pipeline tracking for business intelligence Code Node Efficiency: Custom JavaScript for complex routing logic beyond visual nodes Multi-Output Branching: Parallel execution for CRM, notifications, and tracking Error Handling: Graceful failure modes for API timeouts or missing data Performance Optimization: Minimizing API calls while maximizing data capture Business Impact Metrics Lead Response Time: Track average time from submission to first contact (target: <5 minutes) Conversion Rate by Tier: Compare close rates for Hot vs Warm vs Cold leads to validate scoring Rep Performance: Measure conversion rates by sales rep to identify training needs or star performers Lead Source ROI: Calculate which marketing channels produce highest-scoring leads SLA Compliance: Track % of leads contacted within 24 hours (target: >95%) Revenue Per Lead: Compare deal sizes for AI-qualified leads vs manual qualification Time to Close: Measure if faster response and better qualification shortens sales cycles Assignment Accuracy: Track how often leads need re-assignment (target: <10%) Manager Escalations: Monitor frequency of 24-hour SLA breaches by rep Cost Per Lead Processed: Calculate ROI of automation vs manual lead distribution Ready to Transform Your Lead Management? Import this template and turn lead chaos into systematic qualification and instant routing with AI-powered BANT scoring! 🎯✨ Questions or customization? The workflow includes detailed sticky notes explaining each component's logic and decision criteria. Template Compatibility ✅ n8n version 1.0+ ✅ Works with n8n Cloud and Self-Hosted ✅ Fully customizable routing logic ✅ Integrates with any CRM via API

Overview This workflow auto-generates a personalized research report on any prospect who books a call with you—using their LinkedIn profile and advanced web research. When a call is booked in your calendar, the system looks up the lead’s LinkedIn URL from a Google Sheets database. That profile is then scraped using Relevance AI to extract posts, experiences, and education. It also runs a deep-dive query on the person using Perplexity to uncover relevant news, insights, and context. This structured data is passed to an AI model that produces a clean profile summary, suggested pain points, and solution ideas. Finally, the system builds and sends you a fully formatted HTML report via email—ready to review before your meeting. Who’s it for Founders taking high-stakes sales calls SDRs/BDRs booking back-to-back meetings Agencies and consultants who want to personalize discovery calls Teams doing high-touch enterprise sales or B2B outreach How it works Triggered when a new call is booked via Cal.com Finds matching LinkedIn URL from a local database (Google Sheets) Scrapes public LinkedIn data via Relevance AI Runs a Perplexity query on the prospect for deeper context Formats the scraped data using Code nodes Sends structured info to AI to generate: A company + person profile Suggested pain points and solutions Formats everything into a clean HTML report Emails you the final summary to prep for the call Example use case > Someone books a call. You receive a report 2 minutes later in your inbox with: > - Their role, company, and latest posts > - What their business does > - Recent news and context from Perplexity > - Predicted pain points and how you might help > > You show up to the call prepped and ready How to set up Connect your Cal.com trigger (or replace with any booking tool) Set up your Google Sheet(s) with contact info + LinkedIn profiles Add Relevance AI API key and configure LinkedIn scraping (they have free credits) Link Perplexity API for web research Customize the AI prompts and report formatting Connect Gmail or preferred email provider to send reports Requirements Cal.com or other booking platform Google Sheets for lead storage Relevance AI account and API access Perplexity API key OpenAI or similar LLM for summarization Email integration (e.g. Gmail) How to customize Replace Cal.com with Calendly, SavvyCal, etc. Change AI prompt tone and structure of the report Add CRM push (e.g. log into HubSpot, Notion, or Airtable) Add Slack or Telegram notifications for call alerts Format reports as PDF instead of HTML for download

One-Line Description Automatically detects missed Zoom demos booked via Calendly and triggers AI-powered follow-up sequences. Detailed Description What it does: When a prospect books a demo through Calendly but fails to join the Zoom meeting, this workflow automatically detects the no-show, generates personalized recovery messages using AI, updates your database, and notifies your sales team—all within minutes of the meeting ending. It bridges Calendly, Zoom, and your follow-up channels to ensure no lead falls through the cracks. Who it's for: Sales teams** running high-volume demo calendars who lose 20-40% of booked meetings to no-shows Customer success managers** conducting onboarding calls where attendance tracking matters SDRs and BDRs** who need immediate alerts when prospects miss scheduled meetings Revenue operations teams** seeking to improve demo-to-opportunity conversion rates through faster follow-up Key Features: Real-time no-show detection** - Automatically checks Zoom participant lists against expected attendees within seconds of meeting end AI-generated recovery messaging** - Creates contextual, empathetic follow-up emails and LinkedIn messages tailored to each no-show scenario Instant team notifications** - Sends formatted Slack alerts with attendee details and suggested next actions so reps can manually follow up if needed Attendance tracking database** - Maintains a searchable record of all bookings and attendance status for reporting and analysis Multi-channel follow-up orchestration** - Coordinates email, Slack notifications, and optional CRM updates from a single automation Selective event filtering** - Processes only specific Calendly event types so you control which meetings trigger the workflow How it works: Booking capture: Calendly webhook fires when a demo is scheduled, extracting Zoom meeting details and attendee information Meeting monitoring: When the Zoom meeting ends, a second webhook triggers attendance verification by pulling the participant list from Zoom's API No-show identification: Workflow cross-references the expected attendee email with actual Zoom participants to confirm whether they attended Automated response: For confirmed no-shows, AI generates personalized recovery messages while the system updates your database and notifies your team via Slack Optional integrations: Simultaneously updates CRM deal stages or triggers additional follow-up sequences based on your configuration Setup Requirements Prerequisites: Calendly account** (any paid plan) with webhook access and Personal Access Token Zoom account** (Pro or higher) with Server-to-Server OAuth app credentials for API access OpenAI API key** for AI-generated follow-up message creation Slack workspace** with OAuth permissions to post messages (optional but recommended) n8n Data Table** created with columns: meeting_id, email, status (built-in n8n feature, no external database needed) Email sending service** configured in n8n (SMTP, Gmail, SendGrid, etc.) if enabling automated email sending CRM API access** (HubSpot, Salesforce, Pipedrive, etc.) if enabling deal updates (optional) Note: Zoom API has rate limits (varies by plan); this workflow makes 1-2 API calls per meeting end event. Estimated Setup Time: 45-60 minutes including Zoom app creation, Calendly webhook configuration, and Data Table setup Installation Notes Critical setup steps: Zoom webhook validation**: You must complete Zoom's webhook endpoint validation process before receiving real events. The workflow includes a dedicated validation path—run it once after creating your Zoom app. Calendly webhook creation**: Use the "Manual Setup Trigger" path in the workflow to programmatically create your Calendly webhook subscription. This only needs to run once. Event type filtering**: Replace the placeholder YOUR_CALENDLY_EVENT_TYPE_URI with your specific demo event type URI from Calendly to avoid processing all meeting types. Test with a real meeting**: Book a test demo, join briefly with a different email than the booking email, then leave. The workflow should detect the "no-show" for the booking email. Common pitfalls to avoid: Forgetting to enable the disabled "Send Recovery Email" node after testing (it's disabled by default to prevent accidental sends during setup) Not configuring Zoom Server-to-Server OAuth correctly (requires Account ID, Client ID, and Client Secret—not JWT credentials) Using a personal Calendly account instead of an organization account (webhooks require organization-level access) Overlooking the Data Table creation step—the workflow will fail without this internal database Testing recommendations: Start with Slack notifications only (leave email sending disabled) to verify the workflow logic Use your own email as a test booking to safely generate AI messages without sending to real prospects Check the Data Table after each test to confirm booking records are being created and updated correctly Customization Options Easy modifications: Swap email for SMS**: Replace the email node with Twilio SMS to send text message follow-ups instead Add delays**: Insert "Wait" nodes to schedule follow-ups hours or days later rather than immediately Change AI tone**: Modify the OpenAI prompt to match your brand voice (casual, formal, humorous, etc.) Multi-step sequences**: Duplicate the AI and email nodes to create a 3-touch follow-up cadence over several days Different CRM platforms**: The HubSpot node can be swapped for Salesforce, Pipedrive, or any CRM n8n supports Extension possibilities: Add Google Sheets logging for executive dashboard reporting on no-show rates Integrate with Calendly's rescheduling API to automatically send rebooking links Connect to Loom or Vidyard APIs to attach pre-recorded demo videos in follow-up emails Create a "second chance" discount workflow that offers incentives for rescheduling Build a predictive model by exporting no-show data to analyze patterns (time of day, lead source, etc.) Category Sales Tags calendly zoom no-show-recovery demo-automation lead-follow-up sales-automation meeting-tracking ai-messaging slack-notification openai Use Case Examples SaaS sales team**: A B2B software company runs 40+ demos per week. When prospects no-show, this workflow immediately notifies the assigned rep in Slack with a pre-written LinkedIn message, sends an empathetic recovery email offering a Loom recording alternative, and flags the deal in HubSpot for manual outreach within 2 hours. Agency onboarding**: A marketing agency conducts discovery calls with new clients. If a client misses their scheduled kickoff meeting, the workflow logs the no-show, updates the client status in their CRM, and sends a friendly rescheduling email with three alternative time slots—all before the account manager even notices. Customer success**: A customer onboarding team tracks training session attendance. When users don't join their scheduled implementation calls, the workflow automatically sends a resource-rich email with documentation links, notifies the CSM team channel, and schedules a follow-up task in their project management tool.

Good to know: The workflow runs every hour with a randomized delay of 5–20 minutes to help distribute load. It records the exact date and time a lead is emailed so you can track outreach. Follow-ups are automatically scheduled two days after the initial email. How it works: After apify completes, the JSON data is retrieved and inserted into the proper JSON node (only the JSON is removed — nothing else). The agent then runs on its own, parsing the data and pushing it to Google Sheets. When a lead is emailed, the system tags it with the date and time for tracking. Two days later the workflow automatically triggers a follow-up, again on an hourly schedule with the same time delay. How to use: Start by connecting your apify account to retrieve data. Place the returned JSON into the designated JSON node. Configure your Google Sheet where the data will be stored. Adjust the time delay window or follow-up period if needed. Insert your email credentials and the message. Requirements: Apify account with active leads/data. Google Sheet for storing and managing parsed lead information. n8n credentials configured for your accounts. email credentials Customising this workflow: You can easily extend this template to include other CRMs, different time delays, or additional notification steps. For example, push new leads to Slack, send SMS notifications, or trigger downstream analytics dashboards automatically.

This n8n template demonstrates how to use AI to fully automate the generation and scheduling of X (formerly Twitter) content based on a specific, predefined persona. Use cases are many: It's perfect for social media marketers looking to streamline content creation, individual experts building a consistent brand voice, or businesses aiming to drive traffic to specific services with a steady stream of relevant content. Good to know The AI model used in this workflow (via OpenRouter) requires an API key and will incur costs based on usage (typically a few cents per generation). The Blotato node used for posting is a third-party community node and requires a separate Blotato account. How it works This workflow is divided into two main processes: Content Generation and Content Posting. Content Generation Process: A Schedule Trigger kicks off the workflow every 4 hours. An AI Agent (LangChain) generates a post based on a detailed prompt defining a persona, purpose, and rules. A Code node refines the AI's output, ensuring the text ends naturally. The generated post is then saved to a Google Sheet with a "Not Posted" status, creating a content queue. Content Posting Process: The workflow retrieves one "Not Posted" item from the Google Sheet. An IF node checks the post's category to determine if an image is required. If an image is needed, it searches for and retrieves a matching image file from a specified Google Drive folder. The Blotato node posts the text (and image, if applicable) to the designated X (Twitter) account. A confirmation email is sent via Gmail to notify stakeholders of the successful post. Finally, the Google Sheet status is updated to "Completed" to prevent duplicate posts. How to use You can test the workflow anytime using the manual trigger. For production, adjust the posting frequency in the "Trigger: Every 4 Hours" node. The quality of the generated content is determined by the prompt. Edit the system message within the "AI: Generate X Post Content" node to customize the persona, purpose, tone of voice, etc. To generate posts with images, you must upload image files to the specified Google Drive folder. The filename must exactly match the post's category name (e.g., Evidence-based_Graph.png). Requirements An OpenRouter account (or another AI service account) for the LLM. A Blotato account for social media posting. A Google account for content management, image storage, and notifications (Sheets, Drive, Gmail). Customising this workflow Expand the workflow to post to other social media platforms supported by Blotato, such as Facebook or LinkedIn. Instead of posting immediately, add a human-in-the-loop approval step by sending the AI-generated draft to Slack or email for review before publishing. Replace the Schedule Trigger with a Webhook Trigger to generate and post relevant content based on external events, such as "when a new blog post is published."

💼 Lead Outreach Agent This AI workflow helps you quickly react to new leads with an initial personalized outreach. A great start of your lead nurturing sequence to avoid loosing precious leads that could turn into paying customers. Most importantly it uses gotoHuman so you can review the AI-analysis and the AI-generated editable email draft before it is sent out in your name. How it works We receive a new form submission incl. the email address and company name of the prospect and extract the website URL from the address. We proceed only for company email addresses. We scrape the website using Firecrawl and summarize it with OpenAI Our AI agent runs an analysis based on the lead information and documents describing our own company and the defined Ideal Customer Profiles. It also fetches previously approved examples from gotoHuman so you're effectively creating a self-learning agent. It responds with the analysis and the drafted outreach email. Human Approval in gotoHuman. Allows editing the drafted email. We can now send our email including any edits made during the review and be sure that we are using high-quality content instead of AI slop. How to set up Most importantly, install the gotoHuman node before importing this template! (Just add the node to a blank canvas before importing) Set up your credentials for the different services In gotoHuman, select and create the pre-built review template "Lead Outreach Agent" or import the ID: T873fI1Xli5nt3eh33Rj Select this template in the gotoHuman node Requirements You need accounts for gotoHuman (Human Supervision) OpenAI (AI Agent) Typeform (Lead Form Submissions) Firecrawl (Website Scraping) Gmail Google Docs (Company Wiki) How to customize Replace the Typeform trigger with any other way you might receive or find new leads Provide the AI Sales Agent with more context to properly analyze the lead and create better personalized emails. Consider adding tools that allow the agent to fetch more infos about the prospect's company or personal profile, or to find out more about your specific product/service offerings and how your sales pitches look like.