Share of Voice in AI Search: What It Is + How to Track It

Share of Voice (SoV) has been a marketing metric for decades — traditionally measuring your brand's advertising presence relative to competitors. In the age of AI search, Share of Voice takes on new meaning. When someone asks ChatGPT for a recommendation, which brand gets mentioned? How often does Perplexity cite your competitors but not you? AI Share of Voice tracks exactly this, and understanding it is essential for any brand that wants to stay competitive in the era of AI-driven discovery.

This guide explains what Share of Voice means in the context of AI search, how to calculate it, and how to use it to improve your brand's position across ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, and DeepSeek.

What Is Share of Voice?

Share of Voice (SoV) is the percentage of total brand visibility your brand captures in a given market relative to your competitors. The traditional formula is straightforward:

SoV = (Your Brand Mentions / Total Brand Mentions) x 100

Historically, SoV was a metric from television advertising. If there were 1,000 TV ad impressions in your category and your brand accounted for 200 of them, your Share of Voice was 20%. The concept was later adapted for digital marketing — search impression share (the percentage of search impressions you capture for target keywords), social media share of voice (the percentage of social mentions), and similar variations.

The core principle has always been the same: SoV tells you how visible your brand is relative to competitors in a specific channel or market. Research by the Ehrenberg-Bass Institute and others has shown a strong correlation between SoV and market share — brands that maintain a SoV higher than their market share tend to grow, while those with a lower SoV tend to shrink.

Here is a simple example with real numbers. Suppose there are three main competitors in your market. Across 100 relevant brand mentions in advertising or media: your brand has 30, Competitor A has 45, and Competitor B has 25. Your SoV is 30%.

Share of Voice in AI Search — The New Metric

AI search does not work like traditional search or advertising. There are no "impressions" in the conventional sense — AI generates conversational responses. When someone asks ChatGPT "what is the best CRM for small businesses?", the model generates a response that names specific brands. There is no results page, no ad slots, no organic positions.

AI Share of Voice is the percentage of AI-generated responses that mention your brand when prompted with relevant queries.

This is fundamentally different from Google's impression share because AI either names you or it does not. There is no "position 7" in a ChatGPT response. The model typically recommends three to five brands in a given response, and if you are not one of them, your Share of Voice for that query is zero.

This makes AI SoV a zero-sum metric for brand recommendations. If ChatGPT recommends three brands when asked about your category and you are not one of them, you are losing potential customers to the brands that are named. Unlike organic search where you can still capture traffic from lower positions, in AI search you are either in the answer or you are not.

The implications are significant. Brands that dominate AI SoV in their category enjoy a compounding advantage: users trust AI recommendations, return to ask follow-up questions, and form brand preferences based on AI suggestions. Meanwhile, brands with zero AI SoV in key queries are invisible to a growing segment of potential customers.

How to Calculate AI Share of Voice

Calculating your AI Share of Voice follows a structured process:

Step 1: Define your prompt set

Create a list of industry-relevant questions that your ideal customer would ask an AI assistant. These should be conversational queries — the kind of questions people naturally type into ChatGPT or Perplexity. For example, a CRM company might track prompts like "what is the best CRM for small businesses?", "top CRM tools for sales teams", and "which CRM has the best integrations?". Aim for 20 to 50 prompts that cover your core use cases.

Step 2: Query across platforms

Run each prompt across the six major AI platforms: ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, and DeepSeek. Each platform has different training data, recommendation patterns, and citation preferences. A brand that dominates ChatGPT recommendations may be absent from Perplexity or DeepSeek.

Step 3: Count brand mentions per response

For each response, record which brands were mentioned. Note whether each brand was mentioned as a primary recommendation, a secondary mention, or just referenced in passing. Track your own brand and your key competitors.

Step 4: Calculate your SoV

Apply the formula: (Your Mentions / Total Brand Mentions) x 100

Here is a worked example: you run 50 prompts across all platforms. Your brand appears in 12 responses. Competitor A appears in 28 responses. Competitor B appears in 35 responses. Your AI SoV = 12 / (12 + 28 + 35) x 100 = 16%.

This tells you that across relevant queries, your brand captures 16% of AI mindshare in your category. Competitor B dominates with 47%, and Competitor A holds 37%.

It is important to note that doing this manually is possible but extremely time-consuming. You would need to run hundreds of queries across six platforms, record each response, and tabulate the results. A single round of manual checking might take a full working day, and you would need to repeat it regularly to track changes over time.

How to Track AI Share of Voice (Automatically)

The manual approach to tracking AI Share of Voice is instructive for understanding the concept but impractical as an ongoing monitoring strategy. This is where purpose-built tools come in.

RivalScope automates the entire AI Share of Voice tracking process across all six major AI platforms. Here is how it works:

1. Set up your prompts — you define the conversational queries that matter to your brand once
2. Automated monitoring — RivalScope runs your prompts across ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, and DeepSeek on a regular schedule
3. Brand mention tracking — every response is analyzed for brand mentions, counting both your brand and your competitors
4. SoV calculation — your visibility percentage is calculated automatically, giving you a clear picture of where you stand
5. Trend analysis — track how your SoV changes over time, identifying improvements and regressions

What this looks like in practice: you log into your dashboard and see your overall visibility percentage, a per-platform breakdown (you might have 25% SoV on ChatGPT but only 8% on Perplexity), a competitor comparison showing exactly who is capturing the rest of the voice, and trend lines showing how these numbers have moved over time.

This automated tracking removes the guesswork and provides the consistent data you need to make informed decisions about your AI visibility strategy.

5 Ways to Increase Your AI Share of Voice

Once you know your current SoV, here are five proven strategies to increase it:

1. Identify your zero-visibility prompts

Start with the queries where competitors appear but you do not. These are your biggest opportunities because they represent queries where customers are actively seeking recommendations in your category but AI never mentions your brand. Focus your initial efforts here rather than trying to improve everywhere at once.

2. Get cited in the sources AI models trust

When AI recommends a competitor, check which sources are being cited in the response. Many AI platforms (especially Perplexity and Google AI Overviews) show their sources. If competitors are being mentioned because of a G2 listing, an industry blog review, or a Reddit discussion, you know exactly where to focus. Get your brand mentioned in those same sources.

3. Publish structured comparison content

Create content that directly positions your brand alongside the category. "Best [category] tools", comparison pages, and buyer's guides that name your brand are exactly the type of content AI models draw from when generating recommendations. Make sure this content is published on your own site and, ideally, on third-party publications as well.

4. Build presence on platforms AI models draw from

Reddit, G2, Capterra, industry publications, and niche forums are disproportionately influential in AI recommendations. If you are absent from these platforms, you are likely absent from AI responses. Build a genuine presence — answer questions, earn reviews, contribute expert commentary.

5. Track consistently

AI responses change over time as models are updated and new content enters the training data. What works today may shift in a month. Regular monitoring ensures you catch changes early and can adjust your strategy before competitors overtake you. Weekly or bi-weekly checks are ideal for most brands.

For a comprehensive strategy covering all aspects of AI visibility, see our guide on Answer Engine Optimisation.

Conclusion

AI Share of Voice is the metric that tells you whether your brand is winning or losing in the age of AI-powered discovery. Unlike traditional metrics that measure impressions or clicks, AI SoV measures something more fundamental: whether AI recommends your brand when it matters.

The brands that track and optimize their AI SoV now are building an advantage that will compound over time as AI search adoption continues to grow. The brands that ignore it risk becoming invisible to a growing segment of potential customers.

Track your AI Share of Voice across 6 platforms — start free with RivalScope.

For related reading, see our guides on what is AEO, how to monitor what ChatGPT says about your brand, and whether ChatGPT gives everyone the same answer. Visit the Learning Hub for the full library.