Connor Provines
Over the past 10+ years, I've led marketing initiatives for B2B SaaS companies at every stage, from initial market entry (0→1) through scaled growth (1→10). My approach is grounded in a simple principle: strategic thinking paired with hands-on execution. I focus on building sustainable growth engines, not just campaigns. Whether it's positioning a new product, optimizing conversion funnels, or scaling demand generation, I bring both the framework and the tactical expertise to move fast and win.
Templates by Connor Provines
Enrich and score leads automatically with Claude AI, PDL and Perplexity
⚠️ Community Node Disclaimer This template uses the Apify LinkedIn Profile Scraper, which is a community node only available in self-hosted n8n installations. The LinkedIn scraping step is optional and can be removed for n8n Cloud compatibility. Who's it for Sales and marketing teams processing 20+ leads daily who need to eliminate manual research and focus reps on hot prospects. Perfect for B2B companies wanting to qualify inbound leads at scale using AI-powered enrichment and scoring. What it does This workflow automates lead qualification by enriching email addresses with firmographic data from People Data Labs, researching individuals and companies using Perplexity AI, scoring leads against your ICP criteria with Claude, and routing them to appropriate channels. Hot leads (8-10 score) get instant Slack alerts with personalized email drafts. Warm leads (5-7) go to a digest channel. Cold leads (0-4) log to your CRM only. Processing takes 30-60 seconds per lead versus 20 minutes manual research, costing $0.08-0.15 per lead. How it works The webhook receives an email address and optional name. Multiple enrichment sources run in parallel: PDL fetches contact and firmographic data, Perplexity researches the individual's recent activity and company developments, and optionally Apify scrapes their LinkedIn profile. All data merges into a complete profile. Claude AI scores the lead against your ICP rules stored in Google Docs, calculating points for company fit, title fit, buying signals, and timing. Based on the total score, leads route to three tiers with different handling. Hot leads trigger immediate Slack alerts and generate personalized email drafts using Gemini. All qualified leads optionally sync to your CRM. Requirements People Data Labs API (or Apollo/Clearbit alternative) Perplexity API Anthropic Claude API Google Docs for ICP rules Slack workspace Gmail account Optional: Apify for LinkedIn scraping (self-hosted only) Optional: HubSpot or other CRM Set up steps Configure the webhook In the Webhook node, set your webhook path (default is "lead-intake"). Send POST requests with this JSON format: json { "email": "lead@company.com", "name": "Optional Name" } Add API credentials securely People Data Labs: In the PDL Enrich node, click "Credential for Header Auth" → Create new credential → Add header name X-Api-Key with your PDL API key as the value. This uses n8n's credential management instead of hardcoding keys. Perplexity: In both Individual Research and Company Research nodes, add your Perplexity API credentials. Anthropic: In the Anthropic Chat Model node, add your Claude API credentials. Slack: In both Slack nodes, set up OAuth2 and select your target channels. Hot and warm leads can route to different channels. Gmail: In the Send Hot Lead Email node, configure OAuth2 credentials. Google Docs: In the ICP & Use Case node, replace the documentURL with your Google Doc containing ICP scoring rules, then add OAuth2 credentials. Optional - Apify: In LinkedIn Profile Scraper node, add your Apify OAuth2 credentials from https://apify.com/curious_coder/linkedin-profile-scraper Optional - HubSpot: Enable the Upsert to HubSpot CRM node and add your credentials. Customize the customPropertiesValues array to match your fields. Create your ICP rules document Create a Google Doc with this structure: COMPANY FIT (0-3 points): Company size: 50-500 employees = 3 points Industry: SaaS/Technology = 3 points Geography: North America = 3 points TITLE FIT (0-3 points): VP/C-level = 3 points Director = 2 points Manager = 1 point BUYING SIGNALS (0-2 points): Recent funding = 2 points New executive = 1 point TIMING (0-2 points): Urgent need = 2 points Copy the URL and paste it in the ICP & Use Case node's documentURL parameter. Test the workflow Activate the workflow and send a test webhook. Monitor the execution to verify enrichment sources return data, AI scoring completes, routing works correctly, and notifications send to the right channels. How to customize Swap enrichment sources: Replace the PDL Enrich node with Apollo or Clearbit HTTP Request nodes. Update the Merge Enrichment Data node to parse the new response format. Adjust scoring thresholds: In the AI Agent node prompt, change the score ranges (currently 8-10 = hot, 5-7 = warm, 0-4 = cold) and add custom scoring factors like technology stack match or budget authority. Change routing: In the Route by Score node, add new output conditions for additional tiers like VIP or modify existing thresholds. Different notifications: Replace Slack nodes with Gmail or add Twilio nodes for SMS. Update the formatting nodes to create appropriate message templates. Use different AI models: Swap the Anthropic Chat Model with OpenAI for GPT-4 or replace the Gemini formatting nodes with Claude for consistency. Remove LinkedIn scraping: Delete the LinkedIn Profile Scraper node and adjust Merge All Sources to accept 4 inputs instead of 5 for n8n Cloud compatibility. Connect different CRMs: Replace the HubSpot node with Salesforce, Pipedrive, or other CRM nodes. Update the Format for CRM node's field mappings to match your CRM's structure.
By Connor ProvinesGenerate multi-format documentation with Claude Sonnet & Google Docs
[Meta] Multi-Format Documentation Generator for N8N Creators (+More) One-Line Description Transform n8n workflow JSON into five ready-to-publish documentation formats including technical guides, social posts, and marketplace submissions. Detailed Description What it does: This workflow takes an exported n8n workflow JSON file and automatically generates a complete documentation package with five distinct formats: technical implementation guide, LinkedIn post, Discord community snippet, detailed use case narrative, and n8n Creator Commons submission documentation. All outputs are compiled into a single Google Doc for easy access and distribution. Who it's for: n8n creators preparing workflows for the template library or community sharing Automation consultants documenting client solutions across multiple channels Developer advocates creating content about automation workflows for different audiences Teams standardizing workflow documentation for internal knowledge bases Key Features: Parallel AI generation - Creates all five documentation formats simultaneously using Claude, saving 2+ hours of manual writing Automatic format optimization - Each output follows platform-specific best practices (LinkedIn character limits, Discord casual tone, n8n marketplace guidelines) Single Google Doc compilation - All documentation consolidated with clear section separators and automatic workflow name detection JSON upload interface - Simple form-based trigger accepts workflow exports without technical setup Smart content adaptation - Same workflow data transformed into technical depth for developers, engaging narratives for social media, and searchable descriptions for marketplaces Ready-to-publish outputs - No editing required—each format follows platform submission guidelines and style requirements How it works: User uploads exported n8n workflow JSON through a web form interface Five AI agents process the workflow data in parallel, each generating format-specific documentation (technical guide, LinkedIn post, Discord snippet, use case story, marketplace listing) All outputs merge into a formatted document with section headers and separators Google Docs creates a new document with auto-generated title from workflow name and timestamp Final document populates with all five documentation formats, ready for copying to respective platforms Setup Requirements Prerequisites: Anthropic API (Claude AI) - Powers all documentation generation; requires paid API access or credits Google Docs API - Creates and updates documentation; free with Google Workspace account n8n instance - Cloud or self-hosted with AI agent node support (v1.0+) Estimated Setup Time: 20-25 minutes (15 minutes for API credentials, 5-10 minutes for testing with sample workflow) Installation Notes API costs: Each workflow documentation run uses ~15,000-20,000 tokens across five parallel AI calls (approximately $0.30-0.50 per generation at current Claude pricing) Google Docs folder: Update the folderId parameter in the "Create a document" node to your target folder—default points to a specific folder that won't exist in your Drive Testing tip: Use a simple 3-5 node workflow for your first test to verify all AI agents complete successfully before processing complex workflows Wait node purpose: The 5-second wait between document creation and content update prevents Google Docs API race conditions—don't remove this step Form URL: After activation, save the form trigger URL for easy access—bookmark it or share with team members who need to generate documentation Customization Options Swappable integrations: Replace Google Docs with Notion, Confluence, or file system storage by swapping final nodes Switch from Claude to GPT-4, Gemini, or other LLMs by changing the language model node (may require prompt adjustments) Add Slack/email notification nodes after completion to alert when documentation is ready Adjustable parameters: Modify AI prompts in each agent node to match your documentation style preferences or add company-specific guidelines Add/remove documentation formats by duplicating or deleting agent nodes and updating merge configuration Change document formatting in the JavaScript code node (section separators, headers, metadata) Extension possibilities: Add automatic posting to LinkedIn/Discord by connecting their APIs after doc generation Create version history tracking by appending to existing docs instead of creating new ones Build approval workflow by adding human-in-the-loop steps before final document creation Generate visual diagrams by adding Mermaid chart generation from workflow structure Create multi-language versions by adding translation nodes after English generation Category Development Tags documentation n8n content-generation ai claude google-docs workflow automation-publishing Use Case Examples Marketplace contributors: Generate complete n8n template submission packages in minutes instead of hours of manual documentation writing across multiple format requirements Agency documentation: Automation consultancies can deliver client workflows with professional documentation suite—technical guides for client IT teams, social posts for client marketing, and narrative case studies for portfolio Internal knowledge base: Development teams standardize workflow documentation across projects, ensuring every automation has consistent technical details, use case examples, and setup instructions for team onboarding
By Connor ProvinesScore product-qualified leads with Amplitude, Claude & PDL for sales routing
AI-Powered Product-Qualified Lead (PQL) Scoring & Sales Routing One-Line Description Automatically score product usage signals from Amplitude cohorts and route hot leads to sales with enriched context. Detailed Description What it does: This workflow transforms behavioral data into sales-ready leads by instantly detecting when users hit your PQL threshold, enriching their profile with company intelligence, and using AI to score their conversion potential. Hot leads are routed directly to sales with personalized conversation starters, while warm and cold leads enter appropriate nurture sequences. Who it's for: Product-led growth (PLG) teams bridging the gap between product adoption and sales conversion Sales development teams needing real-time alerts on high-intent users with actionable context Revenue operations professionals optimizing lead handoff processes between product and sales Key Features: Real-time PQL detection - Triggers instantly when users enter Amplitude behavior cohorts, eliminating manual lead review Multi-source enrichment - Combines product usage data with company intelligence from People Data Labs and AI-powered research AI-driven scoring - Evaluates usage intensity, ICP fit, intent signals, and timing to produce 0-10 lead scores with breakdown reasoning Smart routing logic - Automatically categorizes leads as hot (8-10), warm (5-7), or cold (0-4) for appropriate follow-up workflows Sales enablement context - Provides conversation starters, key insights, red flags, and handoff recommendations tailored to each lead Customizable criteria - References external Google Doc for PQL rules, allowing non-technical teams to update scoring logic How it works: Trigger: Amplitude fires webhook when user enters predefined PQL cohort based on product usage patterns Enrichment: Pulls company data from People Data Labs and conducts AI research on company stage, tech sophistication, and budget indicators AI Scoring: Agent evaluates combined usage + enrichment data against ICP criteria stored in Google Docs, producing structured scoring output Routing: High-scoring leads (hot) generate formatted Slack alerts for immediate sales outreach; warm/cold leads could trigger email sequences (not shown in this template) Setup Requirements Prerequisites: Amplitude account with cohort webhook capability (Growth plan or higher) People Data Labs API key for company/person enrichment (paid credits required) Perplexity API for AI-powered company research Anthropic Claude API for PQL scoring logic Google Gemini API for Slack message formatting Slack workspace with OAuth app configured for posting messages Google Docs containing your PQL criteria and ICP definition (publicly readable or authenticated access) Estimated Setup Time: 45-60 minutes including API credential configuration, Amplitude cohort definition, and PQL criteria document creation Installation Notes Amplitude cohort setup: Define your PQL cohort using behavioral criteria (e.g., "Users who viewed 5+ pages AND invited team members in last 7 days"). Configure webhook to fire on cohort entry. PQL criteria document: Create a Google Doc outlining your scoring components (usage intensity factors, ICP requirements, intent signals). Update the Google Docs Tool node with your document URL. Free email filtering: The workflow includes logic to flag free email domains (Gmail, Yahoo, etc.) which you may want to route differently Testing tip: Use Amplitude's "Test Webhook" feature to send sample payloads before going live Customization Options Replace People Data Labs with Clearbit, Apollo, or other enrichment providers by swapping the HTTP Request node Add CRM integration to automatically create opportunities or update lead scores in Salesforce/HubSpot Extend routing paths by adding branches for warm/cold leads (e.g., trigger email sequences via Customer.io, Braze) Adjust scoring weights by modifying the AI agent prompt or criteria document without touching workflow logic Multi-channel alerts by duplicating output nodes to send to email, SMS, or CRM tasks in addition to Slack Category Sales Tags amplitude pql product-qualified-leads sales-automation lead-scoring enrichment people-data-labs slack-notifications ai-scoring revenue-operations Use Case Examples SaaS PLG companies: Automatically escalate free trial users who hit usage milestones (API calls, integrations connected, team invites sent) to sales for upgrade conversations Developer tools: Identify enterprise-ready accounts based on team size growth, deployment patterns, and GitHub integration usage, routing to enterprise sales team B2B marketplaces: Surface buyers showing high-intent behavior (multiple searches, saved items, pricing page views) to account executives with company context for proactive outreach
By Connor ProvinesAuto-Generate Competitive Battlecards with AI, Slack & Notion (Klue Alternative)
--- Enterprise Competitive Intelligence System (Klue+Crayon Alternative) One-Line Description Build your own Klue/Crayon alternative: Auto-generate comprehensive competitive battlecards with AI research agents for ~$50/month instead of $1,500+ --- Detailed Description What it does: This workflow replicates enterprise competitive intelligence platforms (Klue, Crayon, Kompyte) at 5% of the cost. When sales teams mention a competitor in Slack, AI agents automatically research the company, scrape websites, analyze customer reviews, generate SWOT analysis, and compile everything into structured 9-section battlecards stored in Notion. The system then powers real-time Q&A, letting teams ask "What's their biggest weakness?" and get instant, citation-backed answers—just like Klue's "Ask Klue" feature. Why build vs. buy? | Platform | Annual Cost | Licensing | |----------|-------------|-----------| | Klue | $16,000+ | Per-user fees | | Crayon | $30,000+ | Enterprise-only | | Playwise HQ | $3,000+ | Pro plan | | This workflow | $500-800 | Unlimited users | Who it's for: Startups & scale-ups ($1-10M ARR) that can't justify $15K+ for Klue Sales enablement teams building competitive intelligence without enterprise budgets Product marketing managers maintaining battlecard databases that stay updated Founder-led sales teams needing instant competitive insights without dedicated CI headcount Companies already using n8n looking to add competitive intelligence to their stack --- Key Features (vs. Enterprise Alternatives) | Feature | This Workflow | Klue | Crayon | |---------|---------------|------|--------| | AI Battlecard Generation | ✅ 9 sections | ✅ 4-6 sections | ✅ 5-7 sections | | Slack Q&A Agent | ✅ Real-time | ✅ "Compete Agent" | ❌ Manual | | Customer Review Analysis | ✅ G2, Capterra | ✅ Multi-source | ✅ Multi-source | | SWOT Analysis | ✅ Auto-generated | ✅ Manual/AI hybrid | ✅ Manual | | Data Ownership | ✅ 100% yours | ❌ Vendor-hosted | ❌ Vendor-hosted | | Per-User Fees | ✅ None | ❌ ~$1K/user/year | ❌ Custom | | Setup Time | 45-60 min | Weeks | Weeks | | Annual Cost | ~$500-800 | $16,000+ | $30,000+ | Core Capabilities: ✅ Automatic research pipeline - Scrapes competitor websites, reviews (G2, Capterra), LinkedIn, and product pages ✅ AI-powered analysis - Generates SWOT analysis, positioning insights, feature comparisons, and competitive attack surfaces using Claude Sonnet ✅ Intelligent Q&A agent - Sales reps ask questions in Slack and get contextual answers with proper citations (replicates Klue's "Ask Klue") ✅ Structured battlecard format - Creates 9-section competitive profiles including messaging analysis, discovery questions, and supporting quotes ✅ Multi-source intelligence - Combines website content, customer reviews, market research, and sentiment analysis ✅ Database synchronization - Maintains competitor registry in n8n Data Tables with auto-updated Notion pages --- How it works: Phase 1: Competitor Detection & Routing Sales rep mentions competitor in Slack (e.g., @bot create battlecard for Salesforce or @bot what's HubSpot's biggest weakness?) AI detection agent parses message, extracts competitor name, and queries n8n Data Table using fuzzy matching Workflow routes to battlecard creation (new competitor) or Q&A agent (existing competitor) Phase 2: Research & Data Collection For new competitors, five parallel research streams activate: Company identification via Perplexity (official name, website, LinkedIn) Website scraping via Jina AI (4+ key pages: homepage, features, pricing, about) Customer review analysis via Perplexity (G2, Capterra, Reddit for complaints and pain points) Feature research via Perplexity (core features, integrations, pricing model) Market positioning via Perplexity (competitive positioning, target market, differentiators) Phase 3: AI Battlecard Generation Five parallel Claude Sonnet 4.5 agents generate distinct sections: Company Overview + Basic Information Positioning & Messaging Analysis Feature Comparison + Product Analysis SWOT Analysis (strengths, weaknesses, opportunities, threats) Competitive Attack Surfaces + Discovery Questions Supporting quotes agent extracts tactical customer quotes from reviews. Content merger combines all sections into unified markdown document. Phase 4: Storage & Access Complete battlecard saves to Notion database and competitor registry. Slack confirmation sent with link to new battlecard. Phase 5: Real-Time Q&A For existing competitors, Q&A agent: Retrieves battlecard from Notion Uses Claude to answer questions with battlecard data Optionally supplements with Perplexity for breaking news Posts formatted answer in Slack with section citations --- What makes this different: vs. DIY Google Docs: ✅ Automated research (no manual copying/pasting) ✅ Consistent structure across all battlecards ✅ Real-time Q&A without searching folders vs. Enterprise Tools: 💰 95%+ cheaper than Klue/Crayon ($500 vs. $16K-30K) 🔧 Full customization of research sources and battlecard structure 📁 Complete data ownership (your Notion/n8n, not vendor platform) 👥 No per-user fees (unlimited team access) --- Setup Requirements Prerequisites: Slack workspace with bot permissions (app mentions, message posting) Notion workspace with database for battlecard storage n8n instance (Cloud or self-hosted) with Data Table module Anthropic API key (Claude Sonnet 4.5 for generation, 3.5 for detection) Perplexity API key (Sonar Pro for research) Jina AI API key (web scraping) Estimated Setup Time: ⏱️ 45-60 minutes including API configuration, Slack bot setup, and Notion database template creation --- Installation Notes Slack Configuration: Create Slack app with scopes: app_mentions:read, chat:write, channels:history Subscribe to app_mention event pointing to n8n webhook Notion Setup: Use provided template (30 rich text properties for battlecard sections) Create integration and share database with it Copy database ID from URL n8n Configuration: Create Data Table "Competitors" with columns: CompetitorName (text), NotionURL (text) Import workflow JSON and update credentials Store your company's Notion profile page ID in "Get Our Page" tool node Testing: Test battlecard creation with small company Verify fuzzy matching with typos (salesforce.com → Salesforce) Test Q&A agent on existing battlecard ⚠️ Common Issues: Perplexity rate limits: Space calls 30+ seconds apart Slack formatting: Use single asterisks bold not double Notion properties: Requires 30-property minimum (do not reduce) --- Customization Options Research Sources Swap Perplexity for OpenAI/Tavily, add YouTube/GitHub scrapers, integrate Crunchbase API Storage Backend Replace Notion with Airtable, Google Docs, Confluence, or PostgreSQL Battlecard Structure Add/remove sections (pricing analysis, customer case studies, security comparison), reorder based on priorities Q&A Enhancements Add threaded replies, create slash commands, schedule weekly competitor news digests Advanced Features Quarterly auto-refresh, CRM integration (show battlecards in Salesforce deals), Gong integration (auto-generate from sales calls) --- Who This Workflow Replaces Direct Alternatives: ✅ Klue - Competitive enablement platform ($16K+/year) ✅ Crayon - Competitive intelligence platform ($30K+/year) ✅ Kompyte - Competitive tracking tool ($300-5K/year) ✅ Playwise HQ - AI battlecard generator ($3K-5K/year) ✅ Contify - Market intelligence platform (Enterprise pricing) --- Category Sales & Marketing Tags competitive-intelligence sales-enablement slack-bot notion-database ai-research battlecards klue-alternative crayon-alternative competitive-analysis sales-automation market-intelligence --- Use Case Examples 🎯 B2B SaaS Sales Team Generate battlecards when new competitors emerge in deals. Sales leader mentions @bot create battlecard for Airtable—60 seconds later, entire team has comprehensive competitive profile with attack angles and discovery questions. 📊 Product Marketing at Startup Maintain living competitor database that eliminates manual quarterly research (saving 20+ hours/quarter). PM uses Q&A mid-presentation: @bot what's Linear's current pricing? gets instant answer. 🚀 RevOps & Enablement Team Provide instant Slack Q&A for reps mid-call (@bot what questions expose Salesforce's pricing gaps?). New hires onboard faster with centralized, AI-maintained knowledge base versus outdated PDFs. 💼 Founder-Led Sales Solo founder can't afford $16K for Klue but needs professional competitive intelligence. Build battlecard library organically over months for ~$50/month in API fees. 🏢 Enterprise Replacing Klue/Crayon Company with 100+ reps spent $35K/year on Crayon but only used battlecards. Migrated to this workflow, saved $33K annually, maintained same adoption with identical Slack integration. --- 💡 Pro Tip Start with 5-10 most common competitors to build core library, then add others as they appear in deals. This workflow pays for itself after creating just 3-4 battlecards versus hiring freelance researchers or buying enterprise tools.
By Connor ProvinesRecover missed demos with Calendly, Zoom & AI-generated follow-ups
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 YOURCALENDLYEVENTTYPEURI 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.
By Connor ProvinesAnalyze email performance & optimize campaigns with GPT-4, SendGrid, and Airtable
Analyze email performance and optimize campaigns with AI using SendGrid and Airtable This n8n template creates an automated feedback loop that pulls email metrics from SendGrid weekly, tracks performance in Airtable, analyzes trends across the last 4 weeks, and generates specific recommendations for your next campaign. The system learns what works and provides data-driven insights directly to your email creation process. Who's it for Email marketers and growth teams who want to continuously improve campaign performance without manual analysis. Perfect for businesses running regular email campaigns who need actionable insights based on real data rather than guesswork. Good to know After 4-6 weeks, expect 15-30% improvement in primary metrics Requires at least 2 weeks of historical data to generate meaningful analysis System improves over time as it learns from your audience Implementation time: ~1 hour total How it works Schedule trigger runs weekly (typically Monday mornings) Pulls previous week's email statistics from SendGrid (delivered, opens, clicks, rates) Updates the previous week's record in Airtable with actual performance data GPT-4 analyzes trends across the last 4 weeks, identifying patterns and opportunities Creates a new Airtable record for the upcoming week with specific recommendations: what to test, how to change it, expected outcome, and confidence level Your email creation workflow pulls these recommendations when generating new campaigns After sending, the actual email content is saved back to Airtable to close the loop How to set up Create Airtable base: Make a table called "Email Campaign Performance" with fields for weekending, delivered, uniqueopens, uniqueclicks, openrate, ctr, decision, testvariable, testhypothesis, confidencelevel, testdirective, implementationinstruction, subjectlineused, emailbody, icp, usecase, baselineperformance, successmetric, targetimprovement Configure SendGrid: Add API key to the "SendGrid Data Pull" node and test connection Set up Airtable credentials: Add Personal Access Token and select your base/table in all Airtable nodes Add OpenAI credentials: Configure GPT-4 API key in the "Previous Week Analysis" node Test with sample data: Manually add 2-3 weeks of data to Airtable or run if you have historical data Schedule weekly runs: Set workflow to trigger every Monday at 9 AM (or after your weekly campaign sends) Integrate with email creation: Add an Airtable search node to your email workflow to retrieve current recommendations, and an update node to save what was sent Requirements SendGrid account with API access (or similar ESP with statistics API) Airtable account with Personal Access Token OpenAI API access (GPT-4) Customizing this workflow Use different email platform: Replace SendGrid node with Mailchimp, Brevo, or any ESP that provides statistics API—adjust field mappings accordingly Add more metrics: Extend Airtable fields to track bounce rate, unsubscribe rate, spam complaints, or revenue attribution Change analysis frequency: Adjust schedule trigger for bi-weekly or monthly analysis instead of weekly Swap AI models: Replace GPT-4 with Claude or Gemini in the analysis node Multi-campaign tracking: Duplicate the workflow for different campaign types (newsletters, promotions, onboarding) with separate Airtable tables
By Connor Provines