Share of Model: The New KPI That Replaced Share of Voice

What Share of Model Actually Means

Share of Model is how often AI models mention, recommend, or cite your brand when answering questions in your category.

Not your brand name as a query. Not when someone searches "your company name." When someone asks "what is the best project management tool for a remote team?" or "how do I track AI citations from my blog?" and an AI model answers, does your brand show up in that answer? That percentage, across a representative set of queries, is your Share of Model.

The term has been picking up momentum in SEO and brand strategy circles throughout 2025 and 2026. Companies like Adobe, Semrush, and several specialist AI visibility firms now track it as a primary KPI. The underlying idea is not new: brand visibility has always mattered. What is new is where that visibility now needs to exist.

For most of the last decade, brand visibility lived in Google search results. Share of Voice measured it. Now a significant and growing chunk of brand discovery happens inside AI conversations. Share of Model measures that.

Share of Model vs Share of Voice: The Real Difference

Share of Voice and Share of Model sound similar. They are not the same thing and they do not necessarily move together.

Dimension	Share of Voice	Share of Model
What it measures	Brand presence in search results vs competitors	Brand mention frequency in AI responses
Primary channel	Google, Bing search results	ChatGPT, Perplexity, Gemini, Copilot
What drives it	Backlinks, keyword rankings, ad spend	Content authority, schema, topical depth, brand mentions
How to measure it	Rank tracking tools, impression share	Manual query testing, AI monitoring tools
Update frequency	Near real-time (rankings change daily)	Slower for base models, faster for real-time AI search
Competitive benchmark	Easy to measure via Semrush, Ahrefs, etc.	Requires manual benchmarking or specialized tools
Paid media impact	Direct (Google Ads boosts impression share)	Indirect (brand mentions from press can help)

The critical insight: a brand can have very high Share of Voice in traditional search and near-zero Share of Model in AI responses. This happens all the time with brands that relied heavily on paid search and backlink-heavy SEO without building genuine content depth or topical authority.

It also works the other way. A smaller brand that published deep, well-structured, schema-marked content on a specific topic can have outsized Share of Model because AI models trust its content and cite it regularly, even without the domain authority that would put it on page one of Google.

Why This Metric Matters Right Now

Search behavior has changed faster than most brands realized.

SparkToro reported that roughly 60% of Google searches now end without a click. People get what they need from AI-generated answers and move on. Semrush's 2026 AI Traffic Report showed 357% year-over-year growth in traffic arriving from AI referral sources. Adobe's Digital Insights found that AI-referred site visits nearly tripled in a single year across the sites they track.

These numbers mean something straightforward: if your brand is not showing up in AI responses, a growing proportion of people researching your category are not encountering you at all. They are not bouncing from your site. They are not seeing your Google ad. They are having a conversation with an AI, getting an answer that includes competitors, and forming a preference without you in the picture.

"Your brand's absence from AI responses is not neutral. It is the AI actively recommending someone else, every time a relevant question gets asked."

Common framing in AI brand visibility discussions, 2026

The brands with the highest Share of Model in their categories right now are not necessarily the largest brands. They are the brands that started creating structured, authoritative, AI-optimized content 12 to 18 months ago. The window to be an early mover is still open, but it is closing.

How to Measure Share of Model for Free

You do not need a paid tool to start measuring this. The free method takes about 30 to 45 minutes per week once you set it up.

Step 1: Build your query set

Identify 15 to 25 queries that represent how your target audience searches for solutions in your category. These should NOT be your brand name. They should be category-level questions.

Examples for an AI SEO tool company:

• "best free AI SEO tools"
• "how do I check if ChatGPT can find my website"
• "how to get cited by AI models"
• "AI SEO audit tool"
• "does my site have schema markup"

Good sources for query ideas: the People Also Ask section in Google, Reddit threads in your niche, Quora questions, and the autocomplete suggestions in ChatGPT and Perplexity when you start typing your main topic.

Step 2: Pick your AI platforms

At minimum, test three: ChatGPT (with web browsing on), Perplexity, and Google AI Mode. Add Bing Copilot if your audience uses Microsoft products heavily. Four platforms is plenty for most purposes.

Note: ChatGPT without web browsing gives you the base model's training data. ChatGPT with web browsing gives you real-time results. They can differ significantly. Track both for your most important queries.

Step 3: Run the queries and log results

For each query, run it in each platform. Note whether your brand appears in the response. Log the following in a spreadsheet:

• Query text
• Platform
• Was your brand mentioned? (yes/no)
• Were competitors mentioned? (list them)
• Was your content cited as a source? (yes/no, link if yes)
• Date tested

Step 4: Calculate your Share of Model

Your Share of Model for a given period is: (number of responses including your brand) divided by (total responses tested) multiplied by 100.

If you run 20 queries across 3 platforms, that is 60 total responses. If your brand appeared in 9 of those responses, your Share of Model is 15%.

Track this percentage weekly. The trend line matters more than the absolute number, especially early on.

The Weekly Measurement Template

Here is a simple spreadsheet structure you can set up in Google Sheets or Excel:

Query	ChatGPT	Perplexity	Google AI Mode	Copilot	My Brand	Competitor A	Competitor B
best AI SEO tools	Week 1	Week 1	Week 1	Week 1	No	Yes	Yes
how to get cited by ChatGPT	Week 1	Week 1	Week 1	Week 1	Yes	No	Yes
free AI SEO audit	Week 1	Week 1	Week 1	Week 1	No	No	No

Add a summary tab that calculates:

• Your total Share of Model (all queries, all platforms)
• Share of Model by platform (you might dominate Perplexity but be invisible in ChatGPT)
• Competitor Share of Model for comparison
• Share of Model trend over the past 4, 8, and 12 weeks

This manual approach takes 30 minutes once your spreadsheet is set up. It gives you genuinely useful data that most of your competitors are not tracking at all.

What Actually Drives Share of Model Growth

Some things move Share of Model. Others do not, despite what you might expect.

What works

Topical authority: This is the biggest driver. When your site has comprehensive, interconnected coverage of a topic, AI models treat you as a go-to source. A site with 20 well-linked articles on AI SEO will get cited more often for AI SEO queries than a site with one excellent article on the same topic. Depth and interconnection matter.

Brand mentions on authoritative external sites: AI models learn from text they were trained on and, for real-time systems, from what they find when crawling. When your brand is mentioned in industry publications, reputable blogs, or community platforms like Reddit, those mentions train the model to associate your brand with the topic. This is why PR and thought leadership content has taken on a new importance in the AI era.

FAQPage and structured schema: Pages with FAQPage schema directly match how users query AI models. When your site has a clear question-answer structure backed by schema, AI models can extract and cite those answers with confidence. Without schema, even good content is harder for AI to parse and attribute correctly.

Content that answers exact questions: Look at the queries your target audience types into AI engines. Write content that directly answers those exact questions in the first paragraph of the relevant section. AI models retrieve content that best answers a specific query. Content structured around real queries outperforms content structured around keyword themes.

Consistent entity signals: Your organization name, URL, and contact information should be consistent across your website, your Google Business Profile, your LinkedIn page, and any directories you appear in. AI models cross-reference these signals to determine if your entity is trustworthy. Inconsistencies reduce confidence and citation likelihood.

What does not drive Share of Model

Backlink count alone: High backlink count gets you into the candidate pool (AI models tend to draw from sites that traditional search also ranks well). But once you are in the pool, backlinks do not determine citation. Content quality and structure do.

Social media follower counts: Having 50,000 Twitter followers has no meaningful impact on AI citation rates. Social signals are not a significant input to current AI model citation logic.

Paid search campaigns: Running Google Ads increases your visibility in paid search but has no direct impact on AI model citations. AI models do not know about your ad spend.

Publishing frequency for its own sake: Posting 5 shallow articles per week does not move Share of Model. Publishing one deep, well-structured, schema-marked article per week does. Quality and depth of coverage outperform publishing velocity every time.

Using AI to Analyze Your Competitors' Share of Model

Your measurement spreadsheet already tracks competitors as part of the process. But you can go deeper.

When a competitor shows up in an AI response, pay attention to exactly what gets cited. Is it a specific article? A specific claim? A definition? A statistic? This tells you what type of content is working in your category.

Ask ChatGPT directly: "When you answer questions about [your category], which websites do you typically cite and why?" The answer is not perfectly reliable (AI models do not always have accurate self-knowledge), but it gives useful directional information about what the model associates with expertise in your space.

Also ask: "What are the most authoritative resources on [your topic]?" The sites that appear repeatedly in these meta-queries are the ones with the highest Share of Model in your category. Study their content structure. What schema do they use? How are their articles structured? How long are their answers? What kind of statistics do they cite? Reverse-engineer what is working and do more of it.

Paid Tools vs the Free Method

Several paid tools now offer Share of Model or AI visibility tracking. They are worth knowing about, but the free method above is sufficient for most sites starting out.

Paid options in this space as of mid-2026 include tools from companies like Peec.ai, Profound, and several AI SEO platforms that have added citation tracking features. These tools automate the query testing, run it across more queries and platforms than manual testing allows, and generate competitive reports automatically.

The free method is better for getting started because it forces you to actually read the AI responses rather than just look at a dashboard number. Reading responses builds intuition about why your brand does or does not appear, which makes your content decisions better.

Switch to a paid tool when: (1) you have more than 50 queries to track, (2) you need to run tests daily rather than weekly, or (3) your team does not have 30 minutes per week for manual testing.

A 90-Day Share of Model Growth Plan

Here is a realistic timeline for growing your Share of Model from wherever you are starting.

Days 1 to 14: Baseline measurement. Set up your query list and spreadsheet. Run the first measurement across all four platforms. Record your baseline Share of Model percentage. Do not try to improve anything yet. You need to know where you are starting.

Days 15 to 30: Technical fixes. Check that AI crawlers are allowed in your robots.txt. Add FAQPage schema to your top 5 pages by traffic or importance. Add Article schema with complete author data to every article you have published. Check your sitemap is submitted and accurate. These fixes take a weekend and can produce measurable improvement within 2 to 4 weeks for real-time AI search engines.

Days 31 to 60: Content structure improvements. Go through your top 10 articles and rewrite section intros to be answer-first. Add a comparison table to any article covering multiple options. Add blockquote callouts with your most quotable claims. Update dateModified in schema after each change. Run your Share of Model measurement again at the end of this period and compare to baseline.

Days 61 to 90: Content gaps. Based on your measurement data, identify which queries have zero Share of Model for your brand. These are content gaps. Write one new article per week targeting a different gap query. Each article should be 1,500 words minimum, answer-first structure, with FAQPage schema and HowTo schema where applicable.

At the end of 90 days, most sites that follow this plan see measurable Share of Model improvement. The sites that see the biggest gains are the ones that do the content gap work in the last 30 days, not just the technical fixes.

Run your free AI SEO audit to see your current technical readiness score. It checks schema, meta tags, content structure, and AI crawler access in 5 seconds. Use the results to prioritize your first 30 days.

Frequently Asked Questions About Share of Model