Choose the Right Automation
Identify repetitive, research-heavy competitor monitoring tasks that are good candidates for reliable AI automation.
Automated Deep Research: Track Competitors While You Sleep
Taught by Nate Grahek
Build an n8n-powered competitor monitoring system that uses Perplexity research, Notion archives, change detection, and stakeholder alerts to surface meaningful market shifts automatically.
What you'll learn
Map the Workflow
Design a structured competitor research workflow with clear inputs, outputs, guardrails, and exception-based alerts.
Build in n8n
Configure n8n to run repeated competitor research using company variables, API inputs, and AI-assisted debugging.
Create Usable Reports
Turn messy API responses into clean fields and readable Notion reports with citations, links, and skim-friendly structure.
Detect Competitive Changes
Compare current and previous competitor reports to detect meaningful changes in launches, pricing, positioning, and market activity.
Alert the Right People
Send concise stakeholder notifications that summarize what changed, prioritize importance, and link back to the full source report.
Course curriculum
1 part · 7 chapters
About Nate Grahek
AI Educator @ The Rundown University
Nate is a SaaS founder and Fractional CMO who helps product-driven businesses build marketing systems that actually work — without the fluff. He's spent years helping founders and operators cut through marketing complexity and put the right things on autopilot.
At Rundown University, Nate brings that same hands-on, no-jargon approach to AI education. His workshops and courses focus on practical automation and AI workflows you can deploy the same day — no engineering background required. If you've ever wanted to use AI to get your time back, Nate shows you exactly how.
