Understanding the New Era of Generative Engine Optimization
The landscape of search engine optimization is undergoing its most significant transformation since the invention of the backlink. Large language models (LLMs) like ChatGPT, Gemini, and Claude are no longer just tools for generating text; they have become the primary interfaces through which users discover information, compare products, and make purchasing decisions. This shift has given rise to Generative Engine Optimization (GEO), a discipline focused on making content more “citeable” by AI models.
Large language models excel at synthesizing enormous amounts of information into personalized responses to plain-language prompts. These responses draw on massive training datasets and are often enhanced with real-time internet searches using a process known as Retrieval-Augmented Generation (RAG). For brands and digital publishers, the fastest way to influence what LLMs say is to influence the content they retrieve through those searches. If an AI model cannot find your content or finds it difficult to parse, your brand effectively disappears from the conversational search results.
At Evertune Research, the team used the Evertune AI marketing platform to track hundreds of brands across 250 categories and every major LLM. This massive undertaking provided clear insight into which content AI models cite most often, particularly when users ask for brand or product recommendations. The results of the study, which analyzed 25,000 unique URLs, reveal a definitive preference in the AI ecosystem: AI search loves listicles.
The Data Behind the Citation Revolution
To understand the mechanics of AI citations, Evertune reviewed the 6,000 most-cited URLs per model across ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overview, and Perplexity for March and April. While the total pool of analyzed citations reached 36,000, the dataset distilled down to approximately 25,000 unique URLs, as many top-performing pages were cited across multiple platforms.
The findings were staggering. Of the 25,000 unique URLs reviewed, half were formatted as listicles. When looking at the broader scope of nearly 400 million citations across all models, 63% pointed to listicles. This suggests that while traditional long-form articles and deep-dive essays still have a place, the “Best of” or “Top 10” format is the current king of the AI-driven web.
Listicles possess several inherent qualities that make them ideal for model consumption. First, they are tightly focused on a single topic, such as “best laptops for gamers” or “top CRM software for small businesses.” This topical density makes them highly relevant to specific user prompts. Second, their structured nature—often featuring clear headers, bullet points, and consistent formatting—makes them exceptionally easy for an AI to parse, summarize, and reproduce in a chat interface.
The Comparison Advantage
For brand-related queries, listicles do the heavy lifting for LLMs. Rather than the model having to scan ten different individual product pages to understand the differences between them, a single listicle provides a head-to-head comparison of features, price points, materials, and pros and cons. This structured comparison is exactly what ChatGPT now features prominently in its specialized shopping widget, which prioritizes clear, data-rich product comparisons over nebulous marketing copy.
How Different AI Models Prioritize Content
While the preference for listicles is a universal trend, different AI models exhibit unique behaviors in how they select and present citations. The Evertune analysis showed that listicles accounted for 40% to 65% of the most-cited URLs depending on the specific model.
Gemini and the Google Ecosystem
Google’s Gemini models—including Gemini, Google AI Mode, and Google AI Overviews—showed the highest reliance on listicles, sitting at the top of the range. There is also a significant amount of overlap within the Google ecosystem. More than half of the URLs cited in Google AI Mode also appeared in Google AI Overviews. This suggests that Google’s various AI implementations likely share a core index or a similar set of ranking signals that favor highly structured, authoritative list content.
Copilot and Perplexity
Microsoft’s Copilot sat at the lower end of the listicle spectrum, though listicles still represented a massive 40% of its citations. Interestingly, Copilot is the most “independent” of the models, sharing only 4% to 6% of its top URLs with other models. This indicates that Microsoft’s search algorithms and training data prioritize different authority signals than Google or OpenAI.
Perplexity, often dubbed the “answer engine,” shares more than 20% of its URLs with Google’s models. This overlap suggests that as Perplexity crawls the web, it is identifying the same high-value, highly-structured pages that Google’s traditional and AI search engines favor.
Breaking Down the Listicle Format
Not all lists are created equal. The Evertune study categorized listicles into several types to see which ones the AI models preferred. The vast majority of cited listicles featured ranked lists—content like “Top 5 CRM Tools” or “10 Best Running Shoes for Marathons.” Depending on the specific AI model, ranked lists made up between 71% and 86% of all listicle citations.
Ranked vs. Unranked Content
Unranked lists, such as “7 Ways to Save on Groceries” or “12 Ideas for a Backyard Garden,” were a distant second. These provide value but lack the definitive “winner” or hierarchy that AI models often look for when answering a direct recommendation prompt. Institutional rankings, such as the data-heavy “Best Colleges” rankings from U.S. News & World Report, accounted for a surprisingly small portion of citations, ranging from only 1.4% to 4.7%.
The Rise of Earned Media and Affiliate Domains
The study also looked at the domains providing these listicles. Corporate sites, earned media (news and industry publications), and affiliate domains were the dominant sources. Forbes.com emerged as a powerhouse in this category. While Forbes is traditionally considered an earned media domain, its expansion into affiliate segments like Forbes Advisor and Forbes Vetted has made it a top-three source for listicles across every single AI model analyzed.
This highlights a critical lesson for marketers: appearing in a “Best of” list on a high-authority domain like Forbes or TechRadar is often more valuable for AI visibility than having the #1 spot for a keyword on your own corporate blog.
The Risks: Google Penalties and FTC Regulations
While the data suggests that listicles are a “cheat code” for AI citations, there are significant risks involved in over-indexing on this strategy. Both search engines and regulatory bodies are becoming increasingly wary of how listicles are used for promotion.
Google’s Crackdown on Promotional Listicles
Google has already signaled its intent to crack down on promotional listicles that offer little real-world value. The March 2026 core update specifically targeted “site reputation abuse” and low-quality, self-promotional content. If a brand creates a “Top 10” list on their own site where they are conveniently ranked #1 and the other nine competitors are misrepresented or poorly reviewed, Google’s algorithms are increasingly likely to flag this as spam. When Google penalizes a page, its chances of appearing in a Google AI Overview or Gemini response plummet.
FTC Oversight and Legal Compliance
Beyond SEO, there are legal ramifications to consider. The Federal Trade Commission (FTC) has introduced a final rule that prohibits businesses from misrepresenting that a website they control provides independent reviews. If you own a review site that purports to be an independent third party but exists solely to funnel traffic to your own products, you could run afoul of trade regulation rules regarding fake reviews and testimonials. Transparency in affiliate relationships and ownership is no longer just a “best practice”—it is a legal necessity.
Anatomy of a Highly Cited Page
What does a page actually look like when it gets cited by an LLM? The Evertune research provides a technical blueprint for the roughly 25,000 URLs that dominated the citation data. These pages weren’t just lists; they followed a specific structural and linguistic pattern.
Word Count and Paragraph Structure
The most-cited pages typically ranged from 1,000 to 2,000 words. However, there were model-specific variations. Copilot showed a preference for conciseness, frequently citing pages with an average of 964 words and 24 paragraphs. In contrast, Gemini skewed more verbose, favoring expansive content that averaged 1,977 words and 53 paragraphs.
Sentence Complexity and Links
Across the board, the most successful pages maintained a high level of readability. The average sentence length was 18 words. This “sweet spot” allows for enough detail to provide value without becoming so complex that the AI’s natural language processing struggles to summarize it. Additionally, these pages were heavily interlinked, both internally and externally, helping the AI crawl bots understand the context and authority of the information provided.
The Importance of Hierarchy
Structured headings (H2s and H3s) are essential. AI models use these tags as a roadmap to navigate the content. A page with a clear H2 for “Key Features” and H3s for individual product names is much more likely to be cited than a block of text where those names are only bolded or included in a paragraph.
Developing a Winning GEO Strategy
Based on the insights from Evertune’s 25,000 URL analysis, brands and SEO professionals should adjust their content strategies to maximize their “AI brand score.” GEO is not about replacing traditional SEO, but rather evolving it to meet the needs of bot-driven search.
Focus on Hyper-Specific Content
LLMs cite content that is highly structured and hyper-specific. Rather than writing a broad article on “Marketing,” focus on “The 10 Best Email Marketing Tools for E-commerce Startups in 2026.” The more specific the topic, the more relevant the content becomes to the niche prompts users are typing into ChatGPT or Perplexity.
Align Traditional SEO with GEO
The data shows that traditional SEO still supports GEO. Pages that perform well in human search results tend to perform well in bot-driven searches, especially within the Google ecosystem. High-quality backlinks, fast loading speeds, and mobile optimization remain the foundation upon which AI visibility is built.
Optimize for Specific Models
Tailor your content based on your target audience’s preferred AI model. If your audience primarily uses Copilot for work, prioritize brevity, clear bullet points, and data-dense summaries. If you are targeting Gemini users, you have more room to be expansive, providing detailed explanations and a higher word count, provided the structure remains rigid.
Participate in the Ecosystem
Since earned media and affiliate sites like Forbes Vetted are such massive sources for AI citations, your strategy must include a robust PR and outreach component. Being mentioned in a listicle on a high-authority site is often more effective for AI sentiment and visibility than hosting the same list on your own domain. Aim to appear in independent, third-party rankings to build “off-page” AI authority.
The Future of Discovery
The Evertune study clarifies that the “listicle” isn’t just a relic of the BuzzFeed era; it is the fundamental building block of the AI-driven web. As search engines transition into answer engines, the way we structure information must change. By focusing on highly structured, authoritative, and specific content, brands can ensure they remain at the center of the conversation, whether the “searcher” is a human or an algorithm.
As we move forward, the successful digital publisher will be the one who understands that AI models don’t just want information—they want information that is already organized, compared, and ready to be delivered. In the world of AI search, the list is the most powerful tool in your arsenal.