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The Factors That Influence AI Search Visibility

Catch the replay below to learn how Seer is optimizing for LLMs and tracking visibility in AI answers, or scroll down for video clips broken out by key topics.

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Chapter 1: AI Search: Understanding Shifts and Opportunities in 2025

 

AI Search is reshaping how users find information. As marketers, we must adapt to new search behaviors, diversify our approach, and prepare for a more fragmented search ecosystem. This discussion covers:

  • The rise of AI search alongside traditional search – How platforms like ChatGPT, Perplexity, and Gemini are changing search behaviors and creating new opportunities.

  • The future of search and platform diversity – Why SEO is moving toward conversational search, hyper-personalization, and niche AI assistants beyond Google.

The challenges ahead for marketers – How declining organic traffic, increased AI-driven content creation, and attribution complexity will reshape digital strategies.

 

 

Chapter 2: Understanding AI Search Systems and Optimization Strategies

 

To optimize for AI search, you first need to understand how these systems work. We discuss how different AI models rely on a mix of training data, each with its own implications for SEO and content strategy:

  • The three types of AI search systems – A breakdown of models that rely solely on training data, those that always search the web, and hybrid systems like ChatGPT.
  • How AI training data is structured – The role of common crawl data, knowledge bases, publisher partnerships, and post-training refinements in shaping AI-generated answers.
  • Why Bing matters for AI visibility – Since ChatGPT sources web search data from Bing, brands looking for faster insights should focus on optimizing for Bing’s search results.

 

 

Chapter 3: The Impact of Google's AI Overviews

 

Google’s AI Overviews (AIOs) impact on click-through rates is undeniable. This discussion covers how brands can adapt, understanding how to potentially earn visibility in AIOs, and more, including :

  • How to rank in Google’s AI Overviews – Why question-based, uniquely useful content is critical and how brands can optimize for long-tail, natural language queries.
  • The impact of AIOs on organic and paid CTRs – Our study findings of AIOs on organic and paid CTRS.
  • Which industries are most affected – Insights from our data on healthcare, business services, and biotech, and why earning citations in AIOs is becoming a necessity.

 

 

Chapter 4: What do we know about ChatGPT

 

Tracking traffic from ChatGPT and AI-driven search isn’t as straightforward as traditional analytics methods. We discuss how to measure and optimize AI visibility effectively, including:

  • Why UTM codes aren’t reliable for ChatGPT tracking – Understanding how AI citations work and how to use regex and custom channel groups for better visibility.
  • How to identify and track key AI-driven queries – Using semantic question patterns, People Also Ask, and audience forums to predict AI search behavior.
  • What triggers AI web searches – The FLIP framework (Fresh, Local, In-Depth, Personalized) and how businesses can leverage it for proactive optimization.

 

 

Chapter 5: What Factors Correlate with Visibility in LLMs?

 

In this discussion, we explore the new rules of search and how LLMs are reshaping visibility, including:

  • The role of Bing rankings and AI citations – Why appearing in Bing’s top 20 matters and how AI models pull from broader datasets beyond just search results.
  • SEO factors that drive AI visibility – How content recency, citations, statistics, and media formats impact your chances of being surfaced in AI-generated answers.
  • Why high-value traffic from AI search matters – With AI-driven platforms like ChatGPT and Perplexity driving users with higher conversion intent, brands need to rethink their approach to measuring success.

 

 

Chapter 6: Where Do We Go From Here

 

This discussion breaks down key insights on how brands can adapt to changes in SEO and AI-driven search, including:

  • How AI search engines pull data – The role of Bing rankings, citations, and training data in AI-generated responses.
  • What factors impact AI visibility – From on-page content and media formats to publisher partnerships and off-page signals.
  • Why ChatGPT traffic matters – Analyzing referral traffic, conversion rates, and how different industries are seeing early adoption.
Short on time? Listen to the summary (via NotebookLM)