The AISO Checklist: How to Effectively Measure & Improve Visibility in AI Search Results

Over the last few years, working to increase online visibility has evolved dynamically. That’s because the way users search for information online is changing more rapidly than ever.

According to data cited by Semrush, traffic from AI search grew from 17,076 to 107,100 sessions year-over-year between January and May 2025 across analyzed websites, representing a 527% increase.

ChatGPT alone gathers 800 million active users every week, making it the fourth most visited website globally. Furthermore, Semrush predicts that traffic from AI-powered search tools may surpass traffic from traditional search engines as early as 2028.

This does not mean that traditional SEO is dead, though. It simply depicts the evolution of user behavior. Today, it makes little sense to separate SEO from AI search. Users look for answers, regardless of which tool they choose. Your goal is to make sure that your content is quoted, recommended, and discovered wherever that search happens.

CAT Framework: How to optimize for SEO & AI Search, Simultaneously

CAT (Content, Authority, Technical) is a framework based on our AI search optimization experience, to help brands and content teams build visibility across the entire search ecosystem: in both traditional search engines like Google and Bing, and in the new generation of AI-driven search tools such as ChatGPT, Gemini, Perplexity, or Claude.

CAT is future-ready and integrates SEO with AI search to create one clear optimization process for all search channels. It increases the chances of being cited by AI systems and helps protect long-term visibility. It is also a practical foundation for the growing popularity of multimodal search. The framework serves as the baseline for the optimization work we deliver for our clients.

The actionable checklist below, based on the CAT framework, helps you take a holistic approach to your brand’s visibility, regardless of where your potential customers are searching today.

Part I: How to Measure Brand Visibility in AI-Powered Search Results

The first step in improving your visibility is to understand your current standing. In traditional SEO, a wide range of commercial tools support this process. Unfortunately, when it comes to traffic from AI tools, insights from these platforms are not yet sufficient for a comprehensive analysis.

Why Traditional Tools are no Longer Enough

• Standard measurement tools show only a small slice of what happens in AI-powered answers. Data about AI-driven traffic in Bing Webmaster Tools is fragmented. Reports from popular SEO tools, which previously provided a reliable view of visibility in traditional search engines, do not include fully accurate information about how often a brand appears in AI responses.

For instance, in Bing Webmaster Tools, Microsoft officially states that Search Performance data does not cover generative chat experiences. In practice, some signals do appear, but they are heavily anonymized. Due to these limitations, assessing the business impact of AI search as a new traffic channel is challenging.

Still, we can go beyond traditional tools to collect qualitative data that helps us understand how a brand appears in AI-generated answers. To evaluate whether and how your brand is mentioned, follow these audit steps:

Step 1: Test a Range of Prompts

To audit your brand’s visibility in AI responses, begin by testing how models answer different types of queries:

Direct questions, for example:

• What do you know about brand X?
• What are the opinions on product Y?

Comparative queries:

• Brand X vs. Brand Z – which is better for...?
• Compare product Y with its competitors.

Queries about the best options:

• What is the best [product type] for [purpose]?
• Recommend a [service] in [location].

Problem-based queries:

• How do I solve [problem your product addresses]?
• I need help with [task].

Queries across the sales funnel:

• Best X under $500.
• Where can I buy X at the lowest price with free delivery and 24-hour shipping?

Step 2: Analyze Responses Across Multiple AI Platforms

Do not rely on a single tool, because your customers may use different LLMs. Moreover, each model utilizes its own data sources, resulting in distinct outputs. Check your visibility on platforms such as:

• ChatGPT
• Google Gemini
• Perplexity AI
• Claude
• Microsoft Copilot

Testing various queries on different platforms will give you a broader perspective on your brand’s visibility across AI search channels.

Step 3: Monitor Context & Sentiment

Visibility is more than being mentioned. You need to understand how AI presents your brand. Review whether mentions are positive, negative, or neutral, and in what context your products or services are recommended.

Step 4: Check the Cited Sources

Mentions matter more than links in AI answers, but citations are still important. Verify whether your website is referenced as a source. If your domain appears in citations, it is a strong signal that the model considers your content trustworthy and valuable.

Step 5: Analyze Server Logs

As mentioned earlier, standard analytics, including Google Analytics 4 (GA4), do not capture the full extent of AI-generated traffic. Server logs reveal bots such as GPTBot, OAI-SearchBot, or ChatGPT-User. Research shows that GA4 underreports these visits significantly: in one case, logs detected 197 visits from ChatGPT-User in five days, while GA4 registered only 5.

From server logs, you can:

• Track when AI bots visit your website and how often
• Estimate how visible your content is across generative tools like ChatGPT
• Identify which URLs are used as sources for models’ answers

Step 6: Collect & Analyze New Success Indicators

From an AI search optimization (AISO) perspective, focus on:

• Frequency: the number of times the brand is mentioned. Please note that we track mentions, not links.
• Citations: how often your site is referenced as a source through links.
• Position and sentiment: whether your brand is recommended first or listed among many options, and in what tone it is described.

These metrics help you understand not only how often your brand appears in LLM-generated answers, but also discover the tone that shapes users’ perception of your authority.

Part II: AI Search Optimization (AISO) Checklist

To actively build your brand’s visibility in generative chat experiences, you need to implement an AI Search Optimization (AISO) strategy. It expands traditional SEO practices to match the way modern AI systems read, interpret, and use online content.

Step 1: Create & Optimize Content Based on the E-E-A-T Framework

Proving your Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T, as referred to by Google) helps you optimize for both traditional search results and AI chatbots, because AI tends to favor content from credible experts.

• Publish detailed, in-depth articles, guides, case studies, and testimonials
• Clearly present content authors and their qualifications
• Update your content regularly to keep it aligned with current knowledge

The recommended E-E-A-T focus shows that AI search and traditional SEO follow the same principles of credibility and expertise. By strengthening these signals, you support visibility in both environments, because high-quality, trustworthy content works across all search channels.

Step 2: Structure Content Easy

Aim to answer potential user questions directly, using natural language. A clear structure makes it easier for AI systems to extract specific information.

• Use headings (H1, H2, H3) to organize content
• Include bullet lists, numbered lists, and tables
• Create extensive FAQ sections that address common questions and concerns

A clear structure helps LLMs process your content. The easier it is for the model to extract information from your site, the higher the chance that your material will be used effectively when generating answers for the user.

Step 3: Implement Structured Data

Help algorithms understand your website’s context by adding schema markup. Key types include:

• Organization for company information
• Product for product details, pricing and reviews
• FAQPage for questions and answers
• Article and NewsArticle for informational content

Using schema markup gives algorithms clear context about your business and content, which increases the chances that your pages will be interpreted correctly and shown in richer, more relevant search results.

Step 4: Build Authority Beyond your own Website

AI evaluates a brand’s credibility based on signals from the wider internet.

• Earn mentions and links from reputable sources such as industry portals, news sites, and Wikipedia
• Monitor and engage in discussions about your brand on forums (for example, Reddit) and Q&A platforms (such as Quora), as they are often used as data sources for AI models
• Encourage positive reviews and ratings on external platforms

Strong authority signals outside your website help AI understand how the market perceives your brand. When reputable sources mention you and users speak positively about you, models are more likely to treat your brand as trustworthy and include it in their recommendations.

Step 5: Manage Access for AI Crawlers

Determine whether and how language models can utilize your content. Files such as LLMs.txt may eventually become a standard for controlling access, similar to robots.txt in traditional search. For now, if visibility is your priority, allow AI crawlers to access your content by enabling them in your robots.txt file.

Step 6: Check in GA4 Whether LLM-Generated Links Lead Users to 404 Pages

If you spot broken URLs receiving traffic from AI-generated links, consider implementing 301 redirects from incorrect URLs to valid ones. This step is crucial because broken URLs disrupt crawling and indexing signals, which can limit how AI systems establish relationships between your pages. Correct 301 redirects help maintain authority, preserve link equity from AI-generated referrals, and ensure that models reference the right version of your content.

Adapt your Strategy to an Increasing Role of AI Search

Considering the pace of SEO change driven by the rapid growth of LLMs, it’s clear that we need to prepare for fast adjustments in our visibility strategies. Google still plays a major role in how people search; however, new platforms are reshaping the way users explore information, compare products, and make purchasing decisions.

As a result, optimizing online visibility has become more complex. The most effective approach is to pair practical knowledge of LLMs with the capabilities of today’s analytics tools, take a holistic view of optimization, and, as always, stay focused on business goals.

About the Author

Joanna Jelenik Technical SEO Manager at Insightland

Technical SEO Manager and Team Leader at Insightland, with extensive experience in e-commerce. She specializes in technical analysis that drives business decisions and measurable results, as well as AI Search – from strategy to performance evaluation. A passionate advocate of SXO and behavioral data analysis, she co-created the AI Search service – an evolution of SEO built on vector semantics. She loves asking “why” and finding answers in data, believing that the best solutions stem from curiosity, context, and a deep connection between SEO and business objectives.

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