I build revenue infrastructure that scales GTM teams

What I Built

Multi-platform enrichment workflow that processes restaurant leads and generates sales intelligence for territory targeting.

System captures:

• POS systems (Toast, Square, Clover)
• Third-party delivery platforms (DoorDash, Uber Eats, Grubhub)
• Driver operations and delivery volume estimates
• Contact information (emails, phone numbers)
• Lead scoring (0-150 points based on fit criteria)

What Happened

• 1,000 restaurants processed across CT and MA markets
• 600+ verified contact emails extracted
• Built to scale - can process additional markets by adjusting geography
• Used to create call blocks and multi-touch outreach campaigns

How It Works

Feed restaurant names and addresses into Google Sheets. Workflow automatically searches Google Maps/Places APIs for business details, analyzes operations using Claude API, extracts contact information via n8n, scores leads, and writes enriched data back to the sheet.

What I Built

Automated campaign system that identifies expansion opportunities in existing customer base and executes outreach sequences.

System monitors:

• Customer usage patterns
• Feature adoption signals
• Lifecycle stage and contract timing
• Engagement activity

What Happened

• 15%+ of monthly closed revenue came from automated campaigns
• Higher conversion rates during winter months compared to peak season
• Consistent expansion activity throughout the year
• Account team could focus on strategic deals while automation handled standard upsells

Key Finding

Winter months (traditionally slower for new business) showed higher conversion rates for expansion campaigns. Customers had more time to evaluate, there was less competitive noise, and it aligned with annual planning cycles.

How It Works

Salesforce queries segment customers based on usage and engagement criteria. Gmass triggers personalized email sequences when expansion signals are detected. System tracks responses and updates CRM automatically.

What I Built

Dual calculator system serving different stakeholders:

Spreadsheet Version:

• Detailed cost breakdowns with assumption visibility
• Scenario modeling capabilities
• Used by owners, accountants, key stakeholders who need to see the math

HTML Version:

• Browser-based calculator for live demonstrations
• Real-time calculations during remote Zoom calls
• Restaurant economics: commission costs, labor per delivery, payback period

What Happened

• Adopted org-wide by sales team for product demos
• Standardized value conversations across reps
• Two distinct versions for different use cases (internal analysis vs. customer-facing demos)

How It Works

Input restaurant's delivery volume, average ticket size, current platform costs, and labor expenses. Calculator shows current total costs, projected costs with new platform, and payback period in months. Spreadsheet version allows detailed scenario testing. HTML version provides instant calculations during conversations.

What I Built

Automated research system that triggers when restaurant demos are booked via Calendly. Takes restaurant name and website as input, runs operational analysis across multiple data sources, and delivers comprehensive discovery brief via email.

System generates:

• ROI calculator with estimated savings based on restaurant profile
• Third-party services identified (delivery platforms, POS systems)
• Google ratings and review analysis
• Local competitor landscape
• Potential pain points based on operational signals
• Positioning strategy recommendations

How It Works

Calendly booking webhook fires when demo is scheduled. System captures restaurant name and website URL, runs Google Maps API lookup for ratings and reviews, analyzes operational profile for pain points using Claude API, identifies competitor landscape, generates ROI estimates, and delivers complete discovery brief via automated email.

Infrastructure

Built on self-hosted n8n server running on DigitalOcean infrastructure (automation.mikegrowsgreens.com). Docker containerization with Caddy reverse proxy for SSL management. Self-hosting provides unlimited operation execution for high-volume discovery analysis without per-operation cost constraints.

Why self-host: Make.com works for simple workflows but becomes cost-prohibitive at scale. Self-hosted n8n provides full control over deployment environment, unlimited operations, and ability to build custom integrations.

What Gets Included

ROI Calculations: Estimated savings based on delivery volume, average ticket size, and current platform costs. Shows payback period and annual savings projections.

Third-Party Services: Identifies which delivery platforms they use (DoorDash, Uber Eats, Grubhub), current POS system, and other tech integrations.

Google Intelligence: Star rating, review count, recent review sentiment, operational hours. Review analysis for operational signals.

Competitor Context: Local competitors within radius, their ratings, market positioning opportunities.

Pain Point Analysis: Based on review text, operational profile, and tech stack. Identifies likely friction points with current setup.

Positioning Strategy: Recommended approach for demo based on their specific operational profile. Tailored talking points.

Why This Matters

Discovery and demo happen in same Zoom call (typical for restaurant sales). Having intelligence upfront allows tailoring demo to specific operational context rather than spending first 10-15 minutes asking basic research questions.