How to measure and maximize visibility in AI search by Conductor

AI is changing the digital landscape as we know it. An industry that used to run on Google’s 10 blue links is now rapidly transitioning to digital experiences based on personalized prompts and direct answers from AI.

Success is expanding beyond tracking rankings, keywords, and organic traffic. To drive future growth, brands need to prioritize visibility and authority across all search experiences and optimize to improve mentions and citations within AI responses. 

Which begs the question: How do brands measure and maximize their visibility in AI? Let’s dive in.

What is AI visibility?

AI visibility refers to how often and effectively your brand, products, or content appear in AI search and large language models (LLMs). This includes search experiences like Google AI Overviews, ChatGPT, Perplexity, and other answer engines that synthesize information and provide direct answers to a user’s question, often citing their sources. 

These AI models process billions of data points, drawing from brand websites, academic papers, and other online content to generate comprehensive, conversational responses tailored to a user’s specific query. 

When your content or brand is mentioned or cited by AI, that impacts your AI visibility. This represents a significant shift from traditional search engine results pages (SERPs), where the goal was primarily to rank high on a list of links. Now, the emphasis is on being the definitive, authoritative source that an AI retrieves and references.

What makes AI visibility different from traditional search visibility?

While traditional search engines focus on matching keywords to webpages and ranking them based on relevance and authority, AI models prioritize direct answers and contextual relevance.

The goal of AI search is to answer a user’s question directly. With their question answered, that user is much less likely to follow a link to your website, so metrics like organic traffic don’t carry the same weight that they used to. 

Despite that, a strong presence in AI responses can dramatically increase brand awareness and topical authority, even in a “zero-click” search environment.

Key factors that impact your AI visibility

Here are some of the key factors that influence AI visibility:

• Content quality and authority: AI models that source from real-time search data/indexes favor high-quality, comprehensive, and factually accurate content. The better the content, the more likely it is that it will be mentioned or cited.
• Authorship and expertise: AI models, like search engines, look for signals of Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T). Brands with a strong reputation for expertise in their field are more likely to be cited by AI.
• User intent and content relevance: AI models are designed to understand complex queries on a topical level and provide highly relevant responses. That means your content should anticipate user questions, offer clear, concise solutions, and improve overall topical authority. An element of your site’s topical and domain authority encompasses how well your site covers a topic holistically, by understanding user needs, and providing content that answers their questions.  
• Brand mentions and citation: Just as backlinks signal authority in traditional SEO, brand mentions and citations from other sources are critical for AI visibility. When reputable sources mention your brand or link to your content, it’s essentially a vote of confidence in your brand that AI models recognize.
• User experience: While not a direct factor for AI visibility, a strong user experience (UX) can indirectly impact it. Just like with SEO, a positive UX can contribute to your overall site authority, which AI models may consider when evaluating sources.
• Content structure: AI models can more easily parse and understand well-structured content. This includes using clear headings and subheadings, bulleted or numbered lists, tables, and definitional content. Well-structured content also provides a better UX, helping to boost your authority amongst your audience.
• LLM accessibility: For LLMs to use your content effectively, it must be easily accessible and understandable by machines. This means ensuring your website’s technical foundation is solid and taking steps like leveraging Schema markup.

How to measure your AI visibility?

AI search is making traditional SEO metrics less predictive of success. That makes it all the more important for brands to understand how they’re appearing in AI search so they can take steps to optimize their presence. 

Understanding and tracking your AI presence

Tracking AI presence involves monitoring how your brand and content are referenced in AI-generated answers. New metrics that brands need to focus on are mentions and citations within AI responses. These metrics help you understand if AI models consider your content a primary, trusted source for specific queries, or if you have opportunities to optimize.

Unlike with traditional SEO, where smaller websites or organizations could get away with manual tracking, AEO accounts for an infinite number of prompts for every possible intent scenario, combined with login states that show personalized outputs; this results in endless generated responses. Getting the full picture of your AI search visibility requires an automated and intelligent end-to-end AEO tool, like Conductor, that is capable of analyzing this data at scale. 

AEO and AI visibility measurement tool examples

Answer engine optimization (AEO) and AI visibility tools allow you to measure and understand your presence in AI search at speed and scale, making them essential for large and small brands. The most effective AI visibility or AEO tools or platforms should have the following capabilities: 

• Comprehensive AI engine coverage (ChatGPT, Perplexity, AI Overviews, etc.)
• Real-time monitoring and crawling
• Actionable optimization insights
• Integration capabilities
• Enterprise features
• Attribution modeling and traffic impact
• Historical trend analysis
• Competitor and market benchmarking
• Content readiness scoring
• Custom query and entity tracking

Several tools and platforms are now available to measure and maximize AI visibility for small and enterprise-level companies. Be sure to thoroughly explore each tool’s capabilities to see which one best meets your specific needs.

Useful resource:

• See how different AEO/AI Visibility solutions stack up when compared head-to-head in this comprehensive AEO/AI Visibility Platform Evaluation Guide.

Conductor is the only end-to-end solution that supports AEO/GEO/SEO from opportunity and content generation to measurement and monitoring. Conductor is powered by a proprietary data platform, unifying intent signals from AI and traditional search engines, analytics, impressions, and technical health signals alongside API-based AI visibility technology to help users increase brand visibility, traffic, and conversions across large language models (LLMs) and other digital experiences. 

Conductor shows you where your brand appears in AI-generated answers on platforms like ChatGPT and Perplexity, while also giving insight into how you’re performing against competitors for AI visibility. It helps pinpoint the best opportunities to create and optimize content to maximize visibility and authority across every search surface. Then, real-time monitoring and alerting provides a 24/7 insurance policy to ensure LLMs are finding and indexing your content for peak performance. 

Try Conductor for free today to see these features in action and get an idea of your brand’s current AI search performance. 

Steps to improve your AI visibility

When assessing your AI visibility, look for more than just a mention. Pay attention to whether your content is directly cited, if its core message is accurately summarized, and if the sentiment of the mention is favorable. 

High-quality, accurate citations indicate that AI models perceive your brand as a reliable and authoritative source. This interpretation helps optimize your content strategy.

Improving your AI visibility is an ongoing process of optimizing your content and technical foundation to align with how AI models process information. Just like with SEO, this is not a process that is one and done; there will always be opportunities to further optimize your content for AI visibility.

Content strategies to improve AI visibility

The quality of your content has a significant impact on how users and answer engines view your site. The following content strategies are key to maximizing your AI visibility:

• Highlight your unique expertise in specific and authoritative content
• Prioritize satisfying user intent 
• Structure your content for machine-reading
• Leverage a human-in-the-loop approach when creating content
• Expand digital PR

Technical strategies to improve AI visibility

If your website isn’t technically sound, answer engines are less likely to surface it. The following technical website strategies are critical to improving overall UX and AI visibility:

• Leverage Schema
• Monitor your website for technical issues
• Improve your site’s UX
• Prioritize LLM accessibility

Useful resource:

Download the complete AI Visibility Guide for detailed insights on how to action all of the content and technical strategies mapped out above.

AI visibility in review

As AI models become more integrated into daily search behaviors, proactive AEO strategies will be essential for maintaining and growing your brand’s presence.

The focus is shifting from merely optimizing for traditional search engine algorithms to understanding and influencing how large language models interpret information from your site. 

Brands that make informed, strategic decisions now to invest in AEO will continue to drive growth and are better positioned to become AI search leaders within their industries.