Model Context Marketing

Use large language models as both a market intelligence layer and a distribution channel.

Model Context Marketing is the practice of working with LLMs to unlock business potential—enabling marketers to understand markets more deeply and position brands more effectively in AI-mediated discovery.

This isn't just about being found by AI. It's about using AI to make better decisions about messaging, positioning, content, and opportunities—then structuring your content so AI systems can understand, trust, and cite you.

The Problem

Search Engine Decay. Search engines are losing their dominance as the primary information channel. Built on infrastructure with too much friction—too many clicks, too much time. Users are increasingly turning to AI for instant answers instead.

Website Fatigue. Users are exhausted by traditional websites. They don't need 900 pages and complex navigation. They just want to know: What do you have? How much? Can I use it?

Brands aren't showing up in AI-generated responses. When users ask ChatGPT, Claude, or Perplexity for recommendations, many companies are invisible.

Showing up incorrectly. LLMs hallucinate—generating plausible but inaccurate information about your products, pricing, or capabilities.

Traditional tactics don't work. Hype, spin, and promotional language are filtered out. LLMs prioritize factual, research-based, verifiable information from domain experts.

Read: AI as a Marketing Channel →

Two Sides of Model Context Marketing

MCM isn't just a new channel—it's a fundamental shift in how marketers work. There are two interconnected sides:

Outbound: Being Found by LLMs

Structure your content so AI systems can understand, trust, and cite you.

  • • Structured data (JSON-LD schemas)
  • • Semantic HTML and proper hierarchy
  • • Authority signals and E-E-A-T
  • • Factual, research-based content
  • • Clear product/service information

Inbound: Using LLMs to Understand Markets

Use AI as a market intelligence operator to make better decisions faster.

  • • Identify market signals and untapped demand
  • • Analyze competitive positioning at scale
  • • Understand customer language and pain points
  • • Test messaging before production
  • • Build custom AI research operators

Read: The Evolution of MCM →

The CMO Framework

Model Context Marketing follows a three-step process:

Connect

Publish model-ready, structured content that AI systems can crawl and understand.

Measure

Track AI crawler activity and test how accurately LLMs represent your brand.

Optimize

Refine content based on gaps and inaccuracies in AI responses.

Read the complete framework →

The MCM Pillars

Effective Model Context Marketing content stands on these foundational pillars:

Truth

Speak the truth. Provide concise, unambiguous facts—entities, prices, specifications, verifiable claims with sources.

Structure

Structure content the right way. Use machine-readable metadata, JSON-LD schemas, semantic HTML, and clear relationships.

Freshness

Create fresh content consistently. Include explicit update markers, timestamps, and change history.

Authority

Build authority. Demonstrate verified ownership and consistent cross-site signals showing expertise.

Depth

Go deep. Share comprehensive knowledge from both personal expertise and organizational experience.

Velocity

Move quickly. Publish frequently and get knowledge out there while it's relevant.

Authenticity

Be authentic. Don't just regurgitate AI-generated content—share real expertise and genuine insights.

Key Concepts

Getting Started

  1. 1. Read the framework — Understand CMO and the MCM Pillars
  2. 2. Implement foundation — Set up robots.txt, sitemap, and structured data
  3. 3. Structure your content — Use semantic HTML and JSON-LD schemas
  4. 4. Create quality content — Follow the content strategy
  5. 5. Build authority — Establish topical authority