Share of Voice in the LLM Era: Are You Beating Your Competitors?

The New Competitive Landscape in AI Search

Traditionally, the digital marketer's competitive landscape has been the search engines, and the main goal has been to rank the highest on the search engine results page. This has been achieved and measured by various key performance indicators, such as keyword rankings, impressions, and click-through rates. Thus, if your website ranks higher than your competitors on the search engine results page, then you know you are dominating the search engine ecosystem.

However, the advent of AI search has created a new competitive metric, which is referred to as the Share of Voice in the LLM era. Thus, instead of asking yourself whether your website ranks the highest on the search engine results page, the new question in the AI search era is: Are we being recommended more than the competitors by the AI search engines such as ChatGPT and Perplexity AI.

Understanding and monitoring the share of voice in AI search is becoming an integral part of Generative Engine Optimization (GEO). It can help marketers understand whether they are visible in AI search results and whether they are winning compared to their competitors.

Understanding Share of Voice in the Age of Large Language Models

Generally, Share of Voice (SOV) has meant the percentage of brand visibility within a given market or advertising medium. In SEO, it has often meant the number of times a website appears in search engine results compared to competing websites.

In the age of large language models, this has changed. In this age, AI systems are designed to look at multiple sources of data and provide users with one response based on this data. If users ask questions that require recommendations, comparisons, and expertise, it is possible for multiple brands to be mentioned within this response.

For instance, the user may ask for the best tools for project management or the top companies for a particular service. The AI may then respond by providing some of the available options, considering them credible or popular. Each brand helps build its share of voice for its particular topic.

Therefore, the share of voice for the LLM world is the measurement of how often your brand appears in AI answers compared to other brands. A higher share of voice means having greater visibility and prominence within AI search results.

How AI Systems Choose Which Brands to Mention

The AI system works by processing vast amounts of data available across the internet. AI systems do not choose brands at random. They use data to identify credible, authoritative, and relevant brands.

A 2024 EMNLP study found that retrieval systems strongly influence the content of LLM-generated answers because the model synthesizes information from retrieved documents. This means the sources and entities that appear frequently across authoritative content are more likely to be referenced in AI-generated responses.

There are a number of factors that affect which brands are included in AI-generated answers. One of the most significant is content authority. Brands that produce high-quality, informative content are more likely to be included in AI-generated answers. Topical authority is another significant factor. Brands that produce content in a specific area are more likely to be seen by AI models as experts in that area.

Another significant factor is entity recognition. AI models recognize entities such as organizations, products, and people in their models. Brands that are frequently mentioned in credible sources are more likely to be seen by AI models as a prominent concept in a specific area.

Brands such as OpenAI and Google are among the biggest players in AI technologies. They use massive data sets to train their models, which include credible sources such as websites, knowledge platforms, and credible platforms. The more a brand is mentioned in credible sources, the more likely it is to be included in AI-generated answers.

Why Share of Voice is a Critical GEO Metric

Share of voice is considered a vital metric in a generative search environment. Unlike in a normal search environment, where search results are displayed in a long list, in a generative search environment, artificial intelligence search results are displayed with a limited number of recommendations.

If a brand is not displayed in the results generated by artificial intelligence, it may lead to a significant drop in brand visibility even if the website is performing well in search results. On the other hand, being displayed in artificial intelligence results can increase brand visibility and credibility significantly.

A high share of voice in artificial intelligence search results is a positive indicator that a brand is being frequently recognized and displayed in artificial intelligence results. This can increase user trust in artificial intelligence search results, especially when users are making decisions based on information generated by artificial intelligence.

How to Measure Share of Voice in AI Response

To measure share of voice in the LLM world, marketers must use a different approach from traditional SEO analysis. This is because AI responses change according to prompts. Marketers must test AI tools to understand their responses to relevant queries.

Prompt testing is a common method for measuring the share of voice in AI responses. Marketers use AI tools to input relevant queries in the industry and analyze the results to identify which brands are mentioned in AI responses. Marketers can use relevant queries that a customer may ask in real-time to test AI tools. For instance, marketers can test AI tools using queries that a customer may ask to know more about a product or service offered by a business.

Marketers can use tools like ChatGPT and Perplexity AI to test AI tools. By using multiple prompts, marketers can identify which brands are mentioned in AI responses. If a brand is mentioned in multiple prompts, it is a good sign of high visibility in AI-generated content. On the contrary, if a competitor is mentioned in multiple prompts, marketers may need to improve their GEO strategy.

Building a Prompt Testing Framework

In order to effectively calculate share of voice, marketers should build a framework for testing prompts. The first step is to identify the specific prompts that users are likely to ask about a particular industry. The prompts should be relevant to real customer needs, comparisons, and decision-making scenarios.

The next step is to test all the prompts using multiple AI platforms. The results should be analyzed to identify which brands are being mentioned in the AI platforms.

If a brand is consistently mentioned over a period of time for multiple prompts, it is a good indication of share of voice in the AI world. This way, organizations can easily identify whether their visibility is increasing or decreasing in AI platforms compared to their competitors.

Comparing Your AI Visibility with Competitors

Competitor analysis is another key component of calculating share of voice. By analyzing which brands tend to come up most often in AI responses, marketers can gain insight into which brands dominate in AI recommendations.

This analysis can provide marketers with valuable insights. For instance, if competitors come up often in AI responses, it may be because they have more content authority, better entity recognition or coverage in trustworthy sources.

This helps organizations understand where they stand in relation to competitors and where adjustments may be necessary to boost visibility.

By analyzing competitor presence in AI responses, marketers can better tweak their content and digital PR strategies to boost their share of voice.

Strategies to Increase Share of Voice in AI Results

To increase the share of voice in AI search results, one must ensure the content strategy and overall online presence are strong. Creating quality content with good research done on the subject matter can be one of the best strategies to enhance credibility.

Another strategy would be to ensure the brand has the expertise in its niche or industry. Creating content on the subject matter, which could be considered thought leadership, would be beneficial.

Another factor would be to ensure the brand has been mentioned on other platforms, which are considered credible. This would be beneficial because if the brand has been mentioned on credible websites and forums, the chances of the AI considering the information would be high.

Another strategy is to ensure the content created is organized and easily understood, which is beneficial because the AI can easily pick the key information and insights.

Conclusion: Winning the Visibility Battle in the LLM Era

With the arrival of generative AI search, there is now a new paradigm in which businesses must operate. In this new paradigm, Share of Voice in the LLM era is now more important than ever as it relates to digital business and digital influence.

Through this data, businesses can now understand their place within the new AI discovery paradigm and how they compare to their competitors. By monitoring prompt responses and improving content authority, businesses can now optimize their share of voice.

As AI search continues to advance and change, businesses that optimize their share of voice will be at a significant advantage over those who do not. Those businesses that are able to win this new paradigm will not only be able to rank well in traditional search engine results but will be able to provide trusted sources of information to millions of users around the globe through AI-powered search.