Share of Voice in AI Search Is an Old Growth Metric in a New Arena
Key takeaways
|
Share of voice is one of the oldest metrics in marketing, and one of the most underrated in B2B. For decades it has carried a simple, slightly uncomfortable lesson, which is that brands that get talked about more than their size would predict tend to grow, and brands that go quiet tend to shrink. Not immediately, and not always, but reliably enough that serious marketers have built strategies around it.
What's changed is where the talking happens. It used to be advertising and press. Then search and social. Now a growing share of category conversations happen inside AI answers, where a buyer asks for a shortlist and gets three to five names in a few seconds.
If your share of voice measurement stops at ad spend and Google rankings, you're measuring the arenas you're used to, not the ones your buyers are actually using. And the arena you're missing is the one that increasingly decides who makes the shortlist.
What is share of voice?
Share of voice is the percentage of total visibility in a category that belongs to your brand, compared with competitors. It can be measured through advertising spend, search visibility, social and media mentions, or AI-generated answers. Research by Les Binet and Peter Field found that brands whose share of voice exceeds their market share tend to grow. |
Why share of voice predicts growth
The most cited work on this comes from Les Binet and Peter Field, whose analysis for the IPA found a consistent relationship over many years and many brands. When a brand's share of voice is higher than its share of market, it tends to gain market share over time. When it's lower, the brand tends to lose share. The gap between the two has a name, excess share of voice, and it's one of the more dependable predictors of growth marketers have.
The logic behind it is mental availability. Buyers can only choose brands they think of when the need arises, and brands they hear about more often are easier to think of. Share of voice is a proxy for how much of that memory you're building relative to everyone else competing for the same space in a buyer's head.
Binet and Field later extended this work to B2B with LinkedIn's B2B Institute and found that many of the same principles of brand growth apply when businesses buy from businesses. That finding still surprises a lot of B2B marketers, who've spent years being told their world is purely rational and purely about leads.
Why it matters even more in B2B
B2B buying is lumpy. A company might choose a new security platform, CRM or agency once every few years. LinkedIn's B2B Institute, drawing on research from the Ehrenberg-Bass Institute, popularized what's known as the 95-5 rule, which says that at any given moment, only around 5% of potential B2B buyers are actually in the market.
That changes the job completely. The 95% who aren't buying today are the buyers of the next few years. When they finally start looking, they'll begin with the names they already know. Share of voice is how you get into that memory before the buying window opens, so that you're already on the shortlist when it does. Lead generation can only capture the 5%. Share of voice is how you earn the 95%.
And today, increasingly, that first shortlist isn't built by a buyer's memory alone. It's built by an AI assistant drawing on everything the web says about your category. Which brings us to the arena most share of voice reports leave out.
Four arenas, not one
I find it helpful to think of share of voice as playing out in four arenas, each telling you something different. The paid arena is your share of category ad impressions or spend. It's the easiest to buy and the fastest to disappear the moment you stop paying. The organic search arena is your share of visibility for the keywords that define your category, and it reflects the strength of your content and your authority.
The social and earned arena is your share of mentions across social media, press, podcasts and communities, and it reflects reputation and relevance. And the fourth arena, the one that didn't exist a few years ago, is AI answers, meaning your share of the responses that name a brand when buyers ask about your category. That fourth arena has its own name, share of model, and I treat it as part of share of voice rather than a replacement for it.
What makes the AI arena different is that it reflects the other three, blended together. Models learn from and retrieve across paid, organic and earned content. So weakness anywhere tends to show up here, and strength in the AI arena usually means you're genuinely present across the whole landscape.
Measuring each arena
The measurement is easier than most teams assume. For paid, divide your ad impressions or spend by the category total. Auction insights in search ad platforms give you impression share directly, and competitive intelligence tools can estimate the rest. For organic search, choose the keywords buyers actually use for your category, weight them by search volume and calculate the share of estimated visibility you hold. Semrush and Ahrefs both report this, and Google Search Console shows your side of it.
For social and earned, count mentions of your brand and your competitors across social platforms, news, podcasts and communities over a period, and calculate your share of the total. Watch sentiment alongside volume, because a spike from a bad news cycle isn't growth. And for AI answers, run a fixed set of category prompts across several assistants, several times each, and calculate your share of all the brand mentions in the responses. Because answers vary between runs, that number only means something across many prompts and runs, the issue explained in AI non-determinism.
Reading the pattern
Once you have all four, compare each with your market share and look at the pattern rather than any single number. A brand that's strong in paid but weak everywhere else is renting its visibility, and it will evaporate the moment the budget does. A brand that's strong in earned but weak in organic has people talking about it but content that doesn't capture the conversation. A brand that's below its market share in every arena is losing mental availability, often without realizing it.
The pattern I see most often right now is a brand with strong organic search share and weak AI share. These are companies that spent a decade winning Google rankings and are discovering that AI answers draw on different signals. Ahrefs' study of 75,000 brands found branded web mentions correlated with AI Overview visibility at 0.664, compared with 0.218 for backlinks. Rankings built on links don't automatically translate into being named by AI, and the gap shows up clearly once you measure the fourth arena. Brand mentions in AI answers covers how to close it.
Common mistakes
The most common mistake is measuring only paid, because it's the easiest to count and the least durable. Close behind is choosing flattering keywords, tracking the terms you already win rather than the terms buyers actually use. Share of voice is also relative by definition, so changing your competitor set from quarter to quarter quietly destroys the trend.
Counting volume without sentiment is another trap, since being talked about badly isn't growth. And the biggest omission of all, right now, is skipping the AI arena entirely, which is where the shortlist increasingly gets built and where most teams have no data whatsoever. AI sentiment analysis helps with the sentiment side.
Share of voice in the Engine Optimization Matrix™
Share of voice is the scoreboard across all four rows of the Engine Optimization Matrix™. Organic search share measures the SEO row. Snippet and AI Overview presence measures the AEO row. Generative engine mentions and model recall measure the GEO and LLMO rows. Looking at them side by side shows you which row is holding your brand back.
For related reading, see AI visibility, what is brand awareness, demand generation vs lead generation and content marketing KPIs.
Stop guessing which engine to fix first. Mastering AI Visibility puts AI SEO, AEO, GEO and LLMO in one Demand Doctrine™ edition, built on the Engine Optimization Matrix™. Out November 18.
Frequently asked questions
What is share of voice?
Share of voice is your brand's share of total visibility in a category, compared with competitors, measured in ads, search, mentions or AI answers.
What is excess share of voice?
Excess share of voice is the gap between a brand's share of voice and its share of market. Binet and Field found brands with positive excess share of voice tend to grow.
Does share of voice matter in B2B?
Yes. Binet and Field's work with LinkedIn's B2B Institute found many brand growth principles apply in B2B, where most buyers aren't in market at any given time.
What is the 95-5 rule?
It's the estimate, popularized by LinkedIn's B2B Institute, that only about 5% of potential B2B buyers are in market at any given time.
How do you measure share of voice in AI search?
Run a fixed set of category prompts across several AI assistants several times each, and calculate your share of the brand mentions in the responses.
What is the difference between share of voice and share of model?
Share of model is share of voice measured specifically in AI-generated answers. I treat it as one of four arenas of share of voice.
What is a good share of voice?
It depends on your market share. A share of voice above your market share suggests you're building future growth. Below it suggests you're losing ground.
Which tools measure share of voice?
Semrush and Ahrefs for search, social listening tools for mentions, ad platform auction insights for paid, and AI visibility tools such as Semrush's AI Visibility Toolkit for AI answers.
About the author. Harold Bell is the founder of MQL Magnet and has spent about 16 years in enterprise technology marketing, working with brands like Cisco, Rubrik and Nutanix in different capacities. He's a member of the Forbes Communications Council, the creator of the Engine Optimization Matrix™ and the author of Partner Over Product. |
