Competitive analysis is painful. You copy raw data into ChatGPT, wait for a response, copy that into another prompt, wait again, then copy that into yet another prompt. By the time you're done, you've spent 2-3 hours on what should be simple. This workflow ends that.

The Problem

Your competitive research process is Manual Chaos.

You find a competitor's pricing page. You copy it into ChatGPT. You ask it to "analyze this." You get back something... okay. But now you need more depth. So you copy that response, add context, paste into a new prompt, and ask for strategic insights. Another 10 minutes waiting.

Then you realize you need an executive summary your CEO can actually present. More copying. More pasting. More waiting.

Three tabs open. Three different AI sessions. Three hours gone. And the output still needs cleanup before it's board-ready.

Here's what makes it worse: every time you copy-paste between prompts, you lose context. The AI forgets what it learned in step one. You end up repeating yourself, adding back details it should already know.

Your tools don't talk to each other. Nothing connects, so you become the connection.

What This Workflow Does

This workflow is a 3-stage AI pipeline that transforms raw competitor data into polished executive summaries automatically. Paste competitor info once, get board-ready reports in 90 seconds.

Here's what happens when you run it:

• Stage 1 (Extract) takes your raw competitor data and structures it into clean JSON with pricing, features, target customers, and positioning
• Stage 2 (Analyze) compares competitors using chain-of-thought reasoning to find patterns, gaps, and opportunities
• Stage 3 (Write) transforms that analysis into a polished executive summary with clear recommendations
• The output lands directly in Notion, formatted and ready to share

Your new competitive analysis routine:

• Paste competitor data (from websites, pricing pages, marketing materials)
• Click "Execute workflow"