Automated Deep Research: Track Competitors While You Sleep
Workshop recording
Nate Grahek AI Educator @ The Rundown University
7 chapters · 54m · Intermediate
About this course
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
- Choose the Right Automation Identify repetitive, research-heavy competitor monitoring tasks that are good candidates for reliable AI automation.
- 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
Your instructor
Nate Grahek AI Educator @ The Rundown UniversityNate 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.