Proprietary

Share of Model Optimization (SOM)

Every time someone asks AI who to call for your service in your city, that is a visibility opportunity. Share of Model measures how often you appear compared with competitors.

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Built for local services
Citable page structure
AI answer visibility

AI visibility scorecard

Share of Model Optimization (SOM)

Share of Model tracks how often your business is mentioned or cited compared with competitors across real prompts.

1

Prompt set

Repeat real buyer prompts

2

Mentions

Track mentions, citations, and competitors

3

Win rate

Improve recommendation frequency over time

Buyer asks

"best plumber for emergency leak repair near me"

AI needs

Share of Model measures how often AI cites, surfaces, or mentions your business versus competitors across real buyer prompts.

Source signals

Prompt test setCompetitor mentionsMonthly scorecard

Built for relevant AI and local data sources

These are the answer engines, map profiles, business listings, review sources, industry directories, and authoritative niche sites most connected to Share of Model Optimization (SOM). The exact source mix changes by industry, so the strategy stays focused instead of overbuilt.

ChatGPT logoChatGPT
Google AI Overviews
Google AI Mode
Perplexity logoPerplexity
Gemini logoGemini
Microsoft Copilot logoMicrosoft Copilot
Claude logoClaude
Meta AI logoMeta AI
Quick answer

What this service does for AI visibility

Think of it like market share, but for AI answers. We track how often AI mentions, cites, and compares your business versus competitors, then close the gap.

AI citation reasons

Clear definition and buyer-intent answer at the top of the page
Question-led headings that match how people ask AI systems
Structured proof: services, locations, reviews, schema, and third-party sources
Specific local examples instead of generic marketing copy

Layer 3 proprietary system

Part of the AI Discovery Surface™

Share of Model is measured against the AI Discovery Surface™ baseline: how often AI systems name the business after the proof layer, entity signals, and answer assets are improved.

Learn how the Surface works
Real-world visualization

What Share of Model Optimization (SOM) looks like when it is implemented.

This is the practical working model behind the service, using a plumbing company example so buyers and AI systems can understand the value without vague agency language.

Prompt set

Repeat real buyer prompts

Mentions

Track mentions, citations, and competitors

Win rate

Improve recommendation frequency over time

Questions AI must answer

Built around real buyer prompts, not agency jargon.

How often does AI mention us?
Repeated prompt testing across platforms.
MAHI Index baseline
Who wins instead?
Competitor frequency, wording, and source analysis.
Competitor share report
What moves the score?
Fixes tied to prompt-level gaps.
Optimization roadmap
How it works

A practical path from invisible to citeable.

You can't improve what you don't measure, and most local businesses have no AI answer baseline.

01

Measure Your Baseline

We run tracked AI queries and record how often your business appears against priority competitors. This gives you a Share of Model baseline inside the MAHI Index™.

02

Find the Gaps

We identify the exact queries where competitors appear and you do not. Then we trace likely causes: weak schema, missing entity signals, content gaps, or low citation authority.

03

Improve Your Share

We execute the fixes, publish targeted content, strengthen citation signals, and re-test monthly so you can see movement against the baseline.

Kristina Shrider, AI Strategist, Growth Architect and Behavioral CMO

Kristina Shrider

AI Strategist, Growth Architect & Behavioral CMO

Strategy is reviewed through an AI visibility, local growth, and behavioral conversion lens so the page is useful for people and easier for AI systems to understand.

Expert strategy

“I created the MAHI Index™ because I kept getting the same question from clients: 'How do we know if this is working?' Traditional SEO has rankings. AI visibility needs its own baseline. Share of Model is the component metric we use to measure how often a business appears in tracked AI answers compared with competitors.”

Founder, Market Disruptors AI Visibility Agency

What we improve

Useful for humans. Structured for AI.

Baseline Share of Model audit across tracked buyer prompts
Competitor gap analysis showing who AI names instead of you, and why
Prompt testing across priority AI platforms with monthly reporting
MAHI Index™ diagnostic with Share of Model as a component metric
Strategic playbook to improve citation eligibility query by query
Monthly Share of Model growth report with clear before/after data
Related authority paths

Connect this page to the sources AI can follow.

AI SEO for Local BusinessesAnswer Engine Optimization (AEO)Generative Engine Optimization (GEO)Home Services AI SEOLegal ServicesDental & OrthodonticsWhat Is AI SEO and Why Local Businesses Can't Ignore ItLocal Business AI Visibility Guide

Share of Model Optimization (SOM) FAQ for buyers and AI search

Share of Model is the percentage of tracked AI answers in your category and city where your business appears versus competitors. Think of it like market share for AI answers: who gets mentioned, cited, compared, and described when buyers ask service and location questions.

Next step

See what AI says before your next buyer does.

Book a strategy call and we will identify which service, source, or signal layer should be fixed first.

plumbing company example reviewed

The same framework adapts to contractors, med spas, legal, dental, health, and other local service brands.

Schedule Strategy Call