Share of Model: track your brand visibility in AI
Share of Model measures how often a brand appears in answers generated by AI engines (ChatGPT, Google AI Mode, Google AI Overview, Perplexity, Gemini) across a defined set of questions. Repliq breaks it down into four indicators: visibility, share of voice, sentiment and position.
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When a customer asks ChatGPT, Perplexity or Gemini which brand to choose in your field, is your brand part of the answer? More and more buyers form a first opinion inside these answers, sometimes before visiting a single website. Knowing whether you appear, and how prominently, becomes as useful as tracking your Google ranking. The market has given this measure a name: Share of Model.
In one sentence: Share of Model measures how often a brand appears in answers generated by AI engines such as ChatGPT, Google AI Mode, Google AI Overview, Perplexity or Gemini, across a defined set of questions.
Where the term comes from
Share of Model extends a familiar lineage in marketing. Les Binet and Peter Field's work on advertising effectiveness established the importance of excess share of voice (ESOV), the gap between a brand's share of voice and its share of market. Share of search came next, developed by Les Binet and James Hankins around 2020, measuring the volume of queries associated with a brand.
Share of Model applies the same logic to generative engines. The term was introduced by Jack Smyth at Jellyfish in 2024, then popularised by Tom Roach in Marketing Week as the natural successor to share of search in the era of large language models. In its original sense, the notion also covers the associations a model attaches to a brand, not only the frequency of mentions. In practice, we break it down into measurable indicators.
This work of optimising for AI answers has a name, GEO (Generative Engine Optimization). It is the extension of search engine optimisation (SEO), which until now targeted page rankings. SEO and GEO complement each other: a brand that is strong in SEO, picked up by reference sources, is more likely to appear in AI answers.
Why track your visibility in AI
You already track your Google ranking and, most likely, your share of voice in the media. AI answers are a new surface where your brand is present or absent, and where a buyer's decision can form well before any visit to your site. This shift from the search engine to the answer engine changes the nature of what needs measuring.
Regular measurement tells you whether you appear, on which questions and against whom. You get a clear read of your presence and a starting point to improve it. Brands that start early read the trend before the others.
The four indicators
To move from concept to measurement, Repliq tracks four indicators per brand. Two answer the question of presence, two the question of the quality of that presence.
Visibility
Visibility (appearance rate) answers a simple question: how often do I appear? It is calculated by dividing the number of AI answers where the brand appears by the total number of answers measured.
A useful methodological point: each question is asked on several engines and in each market language. The same question therefore produces several answers. Visibility is calculated on that set of answers, not on the number of questions.
Share of voice
Share of voice answers: how much room do I occupy against my competitors? It is calculated by dividing your brand's mentions by the total mentions of your brand and your tracked competitors.
An example makes the difference concrete. Take a Swiss coffee brand that wants to know how it shows up in AI. It defines 50 category questions, such as which coffee to choose for a bean-to-cup machine or best Swiss roasters. Asked on four engines, those questions produce around 200 answers to analyse.
- The brand appears in 72 of those answers. Its visibility is 36%.
- Within those answers, counting every named brand, its own accounts for 15% of mentions against its tracked competitors. Its share of voice is 15%.
The reading is instructive. This brand is visible in just over a third of answers, a good start. When it appears, it still shares the space with several competitors. The two figures point to two levers: being cited more often (visibility), or occupying more room when you are (share of voice).
Sentiment
Sentiment measures the tone attached to the brand when an AI mentions it: positive, neutral or negative. Being cited is not enough. "X is an option, but customer service falls short" is a mention, yet it works against the brand. Sentiment tells you whether the mention is an asset or a liability. Our article on sentiment in the premium segment details this reading.
Position
Position measures the order in which the brand appears in the generated answer. A brand cited first (#1) does not carry the same weight as one mentioned at the end of a list. Average position, tracked over time, shows whether the brand is gaining or losing ground in the hierarchy the AI sets up.
Together, these four indicators make up a brand's dashboard. Here is what that reading looks like, on illustrative, anonymised data.
Brand visibility in AI answers
| # | Brand | Visibility | SOV | Sentiment | Position |
|---|---|---|---|---|---|
| 1 | Competitor A | 52% | 28% | 75 | #1.6 |
| 2 | Competitor B | 44% | 22% | 61 | #2.1 |
| 3 | Your brandYou | 36% | 15% | 72 | #2.4 |
| 4 | Competitor C | 30% | 18% | 68 | #2.8 |
| 5 | Competitor D | 22% | 12% | 54 | #3.3 |
These four indicators extend and sharpen the three classic answer-engine KPIs: share of voice and position make measurable what "being recommended" meant intuitively.
Reading your figures: by engine and by language
Two habits help interpret these indicators.
Look engine by engine. ChatGPT, Google AI Mode, Google AI Overview, Perplexity and Gemini cite different sources and brands. A brand can be well present on one and discreet on another. The per-engine detail shows where to act.
Same brand, different results by engine
| Engine | Visibility | Share of voice |
|---|---|---|
ChatGPT | 48% | 19% |
Google AI Mode | 41% | 17% |
Google AI Overview | 33% | 13% |
Perplexity | 30% | 14% |
Gemini | 22% | 9% |
Look language by language. In Switzerland, the same question in French, German or Italian returns different brands. Tracking your figures in each market language gives a faithful picture, and avoids drawing conclusions from a single one.
Mention and citation
One last distinction, simple and useful. A mention is your brand named in the text of the answer. A citation is your site designated as a source, with a link.
If an AI writes that brands like yours are known for their quality, you are mentioned. If it adds a link to your site as a source, you are also cited. Both count: a mention builds the association in the buyer's mind, a citation can generate traffic and serves as proof. Tracking them separately gives a sharper picture of who speaks for your brand in the answers.
How to start
A few principles set a sound starting point.
- Build a stable set of questions that represents your category, drawn from real buyer questions.
- Measure over time, because AI answers vary from one run to the next: the trend over time is what counts.
- Separate each engine and each language.
- Distinguish visibility, share of voice, sentiment and position, then mention and citation.
- Hold a reliability bar: favour verified data from the real interface, not estimates.
This is the approach we apply to Swiss Atlas, our longitudinal tracking of Swiss brand visibility in AI, whose first sector results will appear on Repliq Research.
Measure my visibility in AIAn AI visibility audit sets this starting point; monthly monitoring reads the trend.
FAQ
Does Share of Model replace SEO? No. SEO and Share of Model reinforce each other. SEO remains the foundation, Share of Model extends it to AI answers.
How is Share of Model measured? From a stable set of questions, through four indicators: visibility, share of voice, sentiment and position.
Which engines should you track? At a minimum ChatGPT, Google AI Mode and Google AI Overview, completed by Perplexity and Gemini, measured separately.
How does it differ from classic share of voice? Share of voice measures advertising or search presence. Share of Model measures presence in AI answers. Same logic, different ground.
Read next:
Frequently Asked Questions
Does Share of Model replace SEO?
No. SEO and Share of Model reinforce each other. SEO remains the foundation for organic traffic; Share of Model extends it to AI answers. A brand picked up by reference sources is more likely to appear in answer engines.
How is Share of Model measured?
From a stable set of questions, asked on each engine and in each market language. Repliq tracks four indicators: visibility (share of answers where the brand appears), share of voice (the brand's weight against tracked competitors), sentiment (the tone attached to it) and position (order of appearance).
Which engines should you track?
At a minimum ChatGPT, Google AI Mode and Google AI Overview, which cover most AI exposure. Perplexity and Gemini complete the picture. Each engine cites different sources and brands, so they must be measured separately.
How does it differ from classic share of voice?
Share of voice measures a brand's advertising or search presence against its category. Share of Model measures its presence in AI answers. Same logic of relative share, different measurement ground.
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