The domain audit report includes a brand share of voice table.
A list of brands with a multiplier next to each.
This piece explains what to do with it.
What the x AVG figure means
The multiplier shows how often a brand appears in the content AI agents are most likely to read on your domain, relative to the average across all brands detected.
1.0x is baseline. That brand appears exactly as often as the average.
2.0x means the brand appears twice as often as average across AI-retrieved pages.
0.1x means the brand is almost absent from the content AI is reading on your site.
This is derived from a scrape of your highest traffic pages. We use public signals to identify which URLs are most likely to receive AI traffic, then analyse which brands appear across those pages.
This is real data from your actual content.
Not modelled, not synthetic.
How to interpret a high multiplier
A brand at 2.0x or above is heavily present in the specific content AI agents are retrieving when users ask purchase questions in your vertical.
This is commercially significant for two reasons.
That brand is benefiting from AI recommendation visibility through your editorial. When
ChatGPTorPerplexityanswers a question using your content, that brand is in the answer. You produced the content. The brand gets the visibility. That's a value exchange that currently goes uncompensated.If that brand is an existing advertiser, their investment is working harder than they know. If they're not an advertiser, this is the opening for a new commercial conversation.
How to interpret a low multiplier
A brand at 0.1x to 0.3x is barely present in the content AI is reading on your site.
This is the more commercially sensitive finding.
We consistently see cases where a brand is a significant advertiser with a publisher, buying display, sponsorships, and branded content, while having near zero presence in the specific articles AI agents are retrieving when users ask relevant purchase questions.
This isn't an editorial failure.
It's a structural gap between where a brand's media investment is concentrated and where AI is actually forming recommendations.
That gap is now visible.
And it's the foundation for a categorically different advertiser conversation.
How to use this in an advertiser conversation
The brand SOV data gives you three angles.
For brands already advertising with you.
Show them how present they are in your AI-retrieved content versus their competitors. Make the invisible visible. If they're winning, it's a retention argument. If they're losing, it's an upsell opportunity.
For brands not currently advertising.
Show them who is winning AI visibility through your editorial right now. A brand seeing a competitor at 1.8x while they sit at 0.2x has a clear reason to engage.
For your own commercial strategy
The brands with the highest multipliers on your domain are the ones with the strongest organic AI presence through your content. Those are your most compelling AI advertising conversations.
Start there.
What the brand SOV data doesn't tell you
This is important.
The brand SOV figure is based on content presence, not actual AI citation frequency.
A brand appearing frequently in your content is more likely to be present in AI answers, but it's not a direct measure of how often any AI platform is recommending that brand.
For that, you need integration.
The analytics platform shows actual LLM traffic by page and by brand, in real time.
The audit shows the opportunity.
The platform shows the actuality.
If the audit data is compelling, that's the conversation to have next.
If you haven’t generated an audit yet, you can do it here: blankspace.so/site-audit