What is Agent-First Competitive Intelligence?
The Problem with Traditional Competitive Intelligence
Every product team knows they should track competitors. Most don't — or they do it once and never update the data. The reason is simple: traditional competitive intelligence is tedious, manual work.
You open a competitor's website, copy pricing into a spreadsheet, paste a product feature description into another tab, and maybe save a screenshot somewhere. Two weeks later, the data is already outdated. Nobody wants to repeat the process.
Some teams try to automate this with ChatGPT or similar tools. But copy-pasting AI-generated summaries creates a new problem: no sources, no structure, no audit trail. You end up with paragraphs of text that nobody can verify or update.
What "Agent-First" Actually Means
Agent-first means the product is designed from the ground up for AI agents to be the primary data collectors — not humans.
Instead of a human navigating a UI to enter data, an AI agent uses structured tools (MCP protocol) to:
- Add competitors and their data points
- Link every data point to a source URL
- Categorize information into dimensions (pricing, product, positioning, etc.)
- Generate SWOT analyses and strategic insights
The human's role shifts from data entry to review and decision-making. You verify sources, override incorrect data, add your own insights, and use the structured comparisons to make strategic decisions.
The 10 Research Dimensions
Market Eagle structures competitive research into 10 dimensions:
- Company Profile — Founding, size, funding, headquarters
- Pricing — Plans, pricing models, discounts
- Product — Features, integrations, platform capabilities
- Target Audience — Segments, personas, markets
- Strengths & Weaknesses — SWOT analysis per competitor
- Positioning — Brand, messaging, unique selling proposition
- Go-to-Market — Channels, partnerships, sales strategy
- Technology — Stack, architecture, infrastructure
- Customer Feedback — Reviews, NPS, sentiment analysis
- Trends & Development — Roadmap, growth, market trends
Each dimension has a specialized research skill that guides the AI agent through a thorough analysis process. The agent knows what to look for and where to find it.
Why Structured Data Matters
The key insight behind agent-first CI is that structured data is more valuable than unstructured text. When every data point has a category, a source, and a timestamp, you can:
- Compare competitors side-by-side on any dimension
- Track how competitor data changes over time
- Verify the accuracy of any specific claim
- Roll back incorrect changes
- See exactly who (human or agent) contributed each piece of information
This is fundamentally different from a Google Doc full of competitor notes or a ChatGPT conversation that disappears when you close the tab.
Getting Started
If you want to try agent-first competitive intelligence, sign up for Market Eagle — it's free to start. Install the Claude plugin, create your first analysis, and let the agent do the research. You'll have structured competitive data in minutes instead of hours.