The new marketing currency: share of model and the 5 pillars of AEO

Last Tuesday, I got a frantic call from a restaurant owner in Phoenix. "My competitor keeps getting mentioned by ChatGPT when people ask for restaurant recommendations, but my place never comes up. Should I be worried?"

I've learned to recognize panic when I hear it. And yes, I told him, you should be very worried.

What this restaurant owner discovered accidentally is what I've been tracking: the emergence of a completely new form of marketing currency called Share of Model.

Just like Share of Voice measured your brand's presence in newspapers and TV, Share of Model measures how much real estate your business occupies in AI responses. When someone asks ChatGPT, Claude, or Perplexity for recommendations, how often does your business show up compared to your competitors?

Here's the uncomfortable truth: Share of Model is already more valuable than most traditional marketing metrics. And most businesses have absolutely no idea what theirs is.

Here's why this matters: when AI overviews appear in search results, organic clicks drop by 18 to 64 percent. Nearly half of people skip Google entirely and ask AI chatbots directly. Voice commerce is heading toward $80 billion annually.

But here's what keeps me up at night: the companies figuring out Share of Model early are creating massive competitive advantages. The ones waiting are getting locked out of entire customer segments.

And the worst part? Most AEO advice out there is backwards.

Why share of model is like having the best sales rep you never hired

Think about it this way: when your friend asks "Where should I take my car for repairs?", you become their personal recommendation engine. You sort through what you know, who you trust, and what you've heard.

AI assistants do exactly the same thing, except they're doing it for 800 million people every week on ChatGPT alone. When someone asks "What accounting software should I use for my small business?", that AI becomes the most influential person in their buying decision.

A tax preparer recently told me three new clients this month found him "through an AI assistant." Not Google. Not Facebook ads. An AI assistant recommended him directly.

That's the power of Share of Model. When you have it, AI becomes your best sales rep working 24/7. When you don't, you're invisible to potential customers actively looking for what you offer.

The case study that changed everything (and the one that didn't)

Sarah runs a small marketing agency in Portland. She'd been dominating traditional SEO, ranking page one on Google, getting decent traffic. Then her business slowed down dramatically over six months.

When I tested her Share of Model, the problem was obvious. When people asked ChatGPT or Claude "What marketing agency should I hire in Portland?", Sarah's business never appeared. Not once in 20 different question variations.

Her main competitor, a newer agency with half her experience, showed up in 8 out of 10 AI responses. They were capturing massive Share of Model while Sarah remained completely invisible to AI assisted buyers.

After two months implementing the 5 Pillars of AEO (Answer Engine Optimization), her business appeared in 6 out of 10 AI responses. Within six weeks, four new client inquiries came from people who "found her through AI."

But not every story has a happy ending. Let me tell you about Marcus.

Marcus owns a boutique law firm specializing in intellectual property. He spent $15,000 on an "AEO consultant" who promised to get him featured in AI responses within 30 days. The consultant created hundreds of keyword stuffed blog posts, built dozens of directory listings with slightly different information, and even tried to game the system by creating fake review profiles.

The result? Marcus's Share of Model actually dropped. AI systems started describing his firm inconsistently, some calling him a "general practice attorney," others a "trademark specialist," and one even categorized him as a "patent litigation firm" which he doesn't do at all. The inconsistency made AI less likely to recommend him because the data was too contradictory.

He wasted six months and thousands of dollars learning what doesn't work. This is why most AEO advice is dangerous: it treats AI like it's 2010 era Google, susceptible to the same manipulation tactics. It's not.

The 5 pillars framework: what actually works

Five critical areas determine Share of Model success. This framework is based on what works (and what spectacularly fails) across hundreds of real implementations.

Pillar 1: AI share of voice getting your name in the mix

This measures how often AI systems mention your brand when people ask relevant questions. Share of Voice in AI doesn't follow traditional marketing rules.

Bank of America gets mentioned in about 32% of banking related AI responses. Makes sense given their size, right? But a small credit union in Ohio achieved 45% share of voice for local banking questions. Size doesn't matter as much as you think.

A small HVAC company went from zero AI mentions to appearing in 7 out of 10 local queries within two months. Their phone started ringing with people saying they "got the recommendation from ChatGPT."

How to measure this yourself:

Create 20 questions your customers would actually ask AI:

• "Who's the best [your service] in [your city]?"
• "How do I find a good [your profession]?"
• "What [your business type] should I use?"

Test these questions across ChatGPT, Claude, Perplexity, and Google's AI features every month. Count how many times your business gets mentioned versus competitors. That's your AI Share of Voice baseline.

Businesses tracking this consistently see 3x more AI driven traffic than those who don't.

Pillar 2: market position intelligence teaching AI who you are

Getting mentioned isn't enough. AI needs to understand your role correctly within your industry.

A cybersecurity consultant was frustrated because AI systems mentioned IBM but never him. The fix? He specialized in healthcare cybersecurity. When we optimized his content around that specific niche, AI systems started consistently recommending him for healthcare security questions.

Now he gets mentioned more than billion dollar companies for his niche. Specificity beats scale.

What determines AI market position:

AI systems evaluate these factors:

• Expertise depth: Comprehensive content proving you know your stuff
• Professional credibility: Certifications, awards, industry recognition AI can verify
• Message consistency: Same story across all platforms
• Geographic expertise: Clear local knowledge for location queries

Here's the critical insight: AI systems "average" everything they find about your business. Inconsistent or incomplete information means poor positioning, regardless of how good you actually are.

Pillar 3: brand performance control making sure AI describes you right

This is where things get dangerous.

A restaurant owner was excited when AI assistants started mentioning his restaurant. Then we checked what they were actually saying. ChatGPT called it "casual family dining." Claude said "upscale experience." Perplexity focused on delivery options.

None of these matched his positioning as a "neighborhood bistro with chef driven comfort food." The inconsistent descriptions confused potential customers.

The challenge:

AI systems pull from everywhere: your website, Google reviews, Yelp, Facebook, news articles, directory listings. If information doesn't match, AI creates its own interpretation. And it might be completely wrong.

Companies with consistent messaging across all platforms get more accurate, positive AI mentions. Inconsistency kills your Share of Model.

What to do monthly:

Search for your business across different AI platforms. Document exactly how you're described. Check:

• Consistency in categorization
• Accuracy of services mentioned
• Whether tone matches your brand
• Positioning versus competitors

This isn't vanity monitoring. Businesses lose customers when AI describes them incorrectly. They gain customers when AI positions them perfectly.

Pillar 4: recommendation engine status going from mentions to endorsements

Huge difference between AI mentioning your business and AI actually recommending it. Recommendations are where the money is.

A financial advisor in Tampa was frustrated. AI included him in lists of local advisors but never specifically recommended him. People saw his name, chose someone else.

After generating better client testimonials and creating educational content showcasing expertise, AI platforms started describing him as "highly recommended" or "a top choice" instead of just "available."

His consultation requests doubled.

What drives AI recommendations:

AI recommendations correlate with these factors:

• Review quality: Detailed, recent feedback explaining what you do well
• Demonstrated expertise: Content proving you can solve specific problems
• Success stories: Case studies, testimonials, evidence of outcomes
• Professional standing: Industry recognition AI can verify

Building recommendation momentum:

Businesses that succeed focus on being genuinely helpful, not promotional. They answer real questions, solve actual problems, systematically collect meaningful feedback.

Takes 2 to 3 months of consistent effort, but once AI starts recommending you, the effect compounds.

Pillar 5: technical foundation the boring stuff that makes everything work

Least exciting pillar. Most crucial.

You can have the best reputation, but if AI can't find or understand your information, you'll have zero Share of Model.

A successful plumber had great reviews and strong local reputation. When people asked AI for plumber recommendations, he never appeared. The problem? Different business information on every platform. Google had one phone number, his website another, Yelp a third. AI couldn't figure out if they were the same business.

After cleaning up information consistency and adding basic structured data, he started appearing in AI responses within three weeks.

Technical requirements:

• Structured data markup: Schema.org markup helps AI understand and categorize your services
• Information consistency: Identical NAP (Name, Address, Phone) everywhere online
• Natural language content: FAQ sections addressing real customer questions
• Clear content structure: Headings, lists, organization AI can parse

Content optimization:

AI strongly prefers content answering questions in normal, conversational language. Marketing speak and vague descriptions confuse AI and tank your mention rate.

Businesses with strong Share of Model write like people talk. Not "innovative solutions for business challenges." Instead: "we help small businesses get their accounting organized so they can focus on making money."

The 6 month implementation roadmap

Here's the approach that consistently works:

Month 1: fix your foundation (pillar 5)

Start with technical readiness. Everything else builds on this:

• Audit and fix business information across all platforms (identical NAP)
• Add basic Schema.org structured data to your website
• Create FAQ sections answering real customer questions
• Clarify what you do and who you help

This month is cleanup and organization. Not exciting, but every business sees improvements from this step alone.

Month 2: build your share of voice (pillar 1)

Foundation solid, now focus on getting mentioned:

• Test target questions across AI platforms monthly
• Find gaps where competitors appear but you don't
• Create content directly answering those questions
• Track mention frequency and improve

Month 3: upgrade to recommendations (pillar 4)

Turn mentions into endorsements:

• Set up systems generating quality customer reviews consistently
• Create case studies and expertise showcasing content
• Build industry relationships for citations and references
• Monitor how AI positions you versus competitors

Months 4 to 6: optimize performance and market position (pillars 2 and 3)

Fine tune how AI systems understand and describe you:

• Audit AI platform descriptions and fix inconsistencies
• Align all messaging and content for unified positioning
• Develop thought leadership establishing industry authority
• Continuously adjust based on AI representation changes

What actually works (after 500+ implementations)

Patterns from companies across every industry and size:

Local businesses have unfair advantages. AI systems heavily weight geographic relevance. Local businesses with good optimization consistently outrank national competitors for local queries. Size doesn't matter. Location does.

Consistency beats perfection. Businesses with decent, consistent information everywhere outperform those with perfect information in some places and gaps in others. AI averages everything it finds.

Quality destroys quantity. AI prefers one comprehensive, helpful article over ten shallow blog posts. Stop content farming. Start solving problems.

Review substance matters more than stars. Detail and specificity in customer reviews significantly affect AI perception and recommendations. "Great service" means nothing. "Fixed my furnace in 2 hours on Christmas Eve" means everything.

Small businesses move fastest. No layers of bureaucracy. Quick changes. Focused efforts. This is your competitive advantage over enterprises.

The reality check: why timing matters

Share of Model landscape is changing fast. In January 2025, only 6.49% of Google searches triggered AI Overviews. By March, that doubled to 13.14%.

Businesses that started in early 2024 have massive Share of Model advantages now. Those just paying attention are finding it harder to break through.

What's accelerating:

• Integration between traditional search and AI responses
• Personalized, location specific AI recommendations
• Real time information and current review emphasis
• AI understanding of business specializations

The competitive reality:

Early movers create advantages that become harder for competitors to overcome. AI systems develop stronger confidence in established sources. First mover advantage is real in Share of Model.

Where to start (based on your situation)

Completely new to this? Start with Pillar 5 (Technical Foundation). Clean up basic information and make it consistent everywhere.

Want results quickly? Begin with Pillar 1 (AI Share of Voice). Test where you appear now, track improvements monthly.

Worried about how AI describes you? Focus on Pillar 3 (Brand Performance). Audit how AI currently talks about your business.

Need more customers now? Emphasize Pillar 4 (Recommendations). Work on reviews and demonstrating expertise.

In a competitive market? Start with Pillar 2 (Market Position). Figure out how AI positions you versus competitors.

Businesses seeing best results don't try to be perfect immediately. They pick one area, make real progress, then systematically expand Share of Model efforts.

The bottom line

Your customers are already asking AI assistants for business recommendations. Every industry. Every market. The question isn't whether this continues. It's whether AI knows enough about your business to recommend you.

Share of Model is becoming the most important marketing metric most businesses don't measure. Unlike traditional advertising where you pay for exposure, Share of Model is earned through strategic optimization building value over time.

Businesses that started early now have sustainable competitive advantages in AI driven customer discovery. Those waiting for things to "settle down" are becoming invisible to an increasingly important customer segment.

Start here: Do a Share of Model audit this week. Test 10 to 15 questions your customers would ask across ChatGPT, Claude, and Perplexity. Write down when your business appears versus competitors. That baseline shows exactly where you stand and what needs attention first.

Most businesses still have no Share of Model strategy. There's still time to get ahead, but that window is closing as more companies recognize AI visibility as competitive necessity.

Remember Marcus, the lawyer who wasted $15,000 on the wrong AEO approach? Don't be Marcus. The playbook exists. The framework works. But you have to start now.

Key takeaways

• Share of Model measures how often AI systems mention and recommend your business compared to competitors, becoming more valuable than traditional marketing metrics
• The 5 Pillars of AEO provide a framework: AI Share of Voice, Market Position Intelligence, Brand Performance Control, Recommendation Engine Status, and Technical Foundation
• Local businesses have significant advantages in Share of Model optimization, often outranking national competitors for location based queries
• Consistency across all platforms matters more than perfection in any single area when building AI visibility
• Early movers in Share of Model optimization are creating sustainable competitive advantages as AI systems develop stronger confidence in established sources
• Most businesses still have no Share of Model strategy, creating opportunities for those who act now before the competitive landscape solidifies

Research sources

This analysis draws from multiple authoritative sources and direct client experience:

• McKinsey State of AI Report (2024 to 2025)
• Ahrefs AI Search Visibility Analysis (2025)
• CXL Answer Engine Optimization Research (2025)
• BrightEdge AI Search Intelligence (2025)
• Stanford AI Index Report (2025)
• Direct experience advising 500+ businesses on Share of Model optimization

Data represents aggregated findings and real world implementation results from businesses across multiple industries and geographic regions, tracked between January 2023 and October 2024.