Definition
Share of model is your share of the brand mentions an AI assistant makes when it answers a category question from what it already knows. Unlike share of voice in AI search, which counts mentions inside retrieved answers, share of model probes the model’s default recall. It moves slowly, because training data does.
At a glance
- CategoriesMeasurement
- Related fieldsAnalytics, GEO
- DifficultyIntermediate
At a glance
- Share of model is measured on prompts where the assistant answers without searching, so the answer reflects what it absorbed during training.
- The unit is a brand name in generated text, with no link and no source list attached.
- Gains here follow from being written about widely, over a long period, in places that end up in training data.
Asking a model what it knows without letting it search
The measurement depends on getting an answer that does not trigger retrieval. Broad category prompts do this: name some brands that make X, who are the main players in Y, what should I consider when buying Z.
Capture the full answer, list every brand named, and your share is your mentions over all brand mentions in that answer. Run the prompt set, total it up, and you have a distribution across the category.
Two details move the result more than people expect. Order matters, since the first brand named tends to be the default association. And wording matters, because “best” pulls a different set from “affordable” or “for professionals”.
Search-enabled surfaces muddy this. If the assistant runs a live search, you are measuring retrieval, not recall, and the levers are different.
Slow to move, and hard for a rival to take back
What makes share of model appealing is what makes it frustrating: it barely responds to a content sprint.
Default associations come from being mentioned repeatedly across the wider web, in journalism, forums, documentation and other people’s comparisons, over years. You cannot publish your way into that in a quarter, and neither can a competitor with a bigger budget.
That stability is the value. A position in default recall survives a bad month, a redesign and a crawl problem. Retrieval-based visibility survives none of those.
Treat share of model as your long-term brand measure and share of voice in AI search as your quarterly one. Judging a three-month program on share of model makes good work look like failure.
Build a share-of-model baseline from a prompt list
- Write 15 category prompts with no brand names in them. If your brand appears in the prompt, you are testing the model’s manners, not its recall.
- Turn search off where the interface allows it, and note the setting for every run so later comparisons are fair.
- Record every brand named, in order. First position is worth tracking separately from being on the list.
- Divide your mentions by total brand mentions. That fraction is the number, per assistant, never blended across them.
- Repeat quarterly, not monthly. The metric does not move fast enough to justify weekly reporting, and frequent checks invite overreaction to noise.
Share of model beside share of voice
| Share of model | Share of voice in AI search | |
|---|---|---|
| What is being measured | Default recall, no retrieval | Presence in retrieved, cited answers |
| Typical prompt | Broad category question | Specific buying or comparison question |
| Speed of change | Slow, over quarters and years | Faster, responds to published content |
| Main lever | Being written about across the web | Page-level clarity and coverage |
| Best used for | Long-term brand position | Quarterly program reporting |
Frequently asked questions
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Is share of model the same as share of voice?
No, though the two get used interchangeably and that causes real confusion in reporting. Share of model measures brand recall when the assistant is not searching. Share of voice measures presence in answers built from retrieved sources. One responds to reputation over years, the other to what you published last month.
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How do I increase my share of model?
Get mentioned where the wider web writes about your category: trade press, documentation, reference sites, forums, other people’s comparisons. Digital PR does more here than on-site work. There is no fast route, and any vendor promising one is selling retrieval work under a different label.
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Does share of model still matter if assistants search for everything?
It matters less than it did and it has not stopped mattering. Assistants increasingly retrieve before answering, which shifts weight to visibility score style measures. Default recall still shapes which brands a model treats as worth searching for, and it decides the answer when retrieval returns nothing useful.
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Should this be my headline metric?
Not on its own, and not if leadership expects quarterly movement. Share of model is an excellent annual benchmark and a poor campaign KPI. Pair it with AI brand sentiment for tone and a faster retrieval metric for the work in front of you.