Is AI Stealing Your Traffic? LLMs, Zero-Click Searches, & the Future of SEO

The web marketing environment is experiencing a shift from users clicking and scrolling through many sources and now limited to zero position. Search engine results pages (SERPs) have transformed from simple lists of blue links to rich, interactive platforms designed to keep users within the interrelated services and products.

Furthermore, the rise of AI-powered search tools and large language models (LLMs) is leading to a core change in how people find and consume information online.

Perhaps the most striking indication of this evolution is the rise of zero-click searches. Recent studies reveal that approximately 60% of searches now end without a click on any result.

Huh, are marketers on vacation? Not really…

This statistic represents not just a change in user behavior but a turning point for digital marketers and SEO professionals.

In this research guide, we will explore zero-clicks, understand how large language models (LLMs) are reshaping search behavior, and provide actionable strategies to adapt your SEO approach for maximum visibility in the new AI-dominated search market.

Part 1: Is AI Stealing Traffic? – Understanding Zero-Click Searches

What Are Zero-Click Searches?

A zero-click search occurs when a user conducts a search but does not click(thanks to Gen. AI.) on any of the search engine results pages (SERPs) displayed. Instead, they either:

• Find their answer directly on the search results page through the AI overview and many other factors.
• Refine their search query without clicking through.
• End their session entirely.
• Move on to a different search.

Why Are Zero-Click Searches Increasing?

1. Evolution of Search Engine Results Pages (SERPs)

Google and other search engines have transformed their results pages from a long time to provide instant answers through:

• Featured snippets
• AI Overview
• Knowledge panels
• People Also Ask (PAA) boxes
• Local packs
• Weather forecasts
• Currency converters
• Calculation tools
• Dictionary definitions

These SERP features are designed to provide information directly on the results page, eliminating the need for users to click through to websites.

2. Changing User Behavior and Expectations

Today’s users expect immediate answers and information without delay:

• The average attention span has decreased
• Mobile search has conditioned users to expect quick answers
• Voice search has normalized question-based queries with direct answers
• Users are increasingly refining searches until they get the exact answer they need

3. Google’s Strategy to Keep Users in Their Ecosystem

Google’s business model benefits from keeping users within its properties:

For the EU, 24% of clicks go to Google properties, with 374 clicks per 1,000 searches going to the open web.

The study notes that while the EU’s Digital Markets Act may be having some effect, the difference isn’t serious. More concerning is that clickthroughs to the open web are at “historic lows” in both regions, with Google sending a decreasing percentage of search traffic to independent websites.

The Mobile Factor

The mobile search experience has further accelerated zero-click searches:

• Almost half of mobile searches in both the US and EU end the browsing session completely.
• The desktop figure for session-ending searches is approximately half of the mobile rate.
• Around 22% of all searches result in another search query going without any clicks.

The Impact on Website Traffic and Business

For businesses that rely on organic search traffic, the zero-click trend poses significant challenges.

• Reduced website visits even with improved rankings.
• Decreased opportunities for conversion as users don’t reach your site.
• Brand exposure without the corresponding engagement metrics.
• Difficulty in measuring search visibility’s actual impact on business outcomes.

Part 2: LLMs and the Evolution of Search – The New Engagement Killers

What Are LLMs and How Are They Changing Search?

Large Language Models (LLMs) like ChatGPT, Gemini, and others represent the next evolution in how users access information. They go beyond traditional search engines by generating detailed, conversational responses to user queries.

LLMs are reshaping how search works in several ways:

1. Direct Answer Generation

Unlike traditional search engines that primarily point to other sources, LLMs collect information from various sources to generate complete answers directly within their interface. This creates an even more pronounced zero-click environment, as users can get what they are looking for without ever leaving the AI platform.

2. Conversational Interface

LLMs allow users to ask follow-up questions, request clarifications, or dig deeper into topics in a natural, conversation-like manner. This keeps users engaged with the AI interface rather than clicking through to external websites.

3. Source Citation Without Clicks

Many LLMs cite sources in their responses, but even with these citations, users often do not feel the need to click through to verify the information or obtain additional details. The AI’s summary feels sufficient for many users’ needs.

The Dual Nature of LLMs for Website Traffic

LLMs to Webmasters: Hey, try this chocolate donut. Oh no, no there’s a hole in it…

LLMs present both opportunities and challenges for website owners:

The Promise of Referral Traffic

LLM-driven referrals are growing:

• Referral traffic from LLMs has increased eightfold since March 2024
• ChatGPT has dominated referrals since August, overtaking earlier platforms
• Perplexity’s referral traffic has doubled over the past year, though its market share remains smaller than ChatGPT’s

For websites and brands, LLMs can function as discovery channels:

• They can surface niche content that might rank lower in traditional search
• They respond to natural language queries that might uncover different brands than keyword-based search
• They can provide links as citations or direct references for users who want to explore further.

The Challenge of Zero-Click Results in LLMs

Despite growth in referral traffic, LLMs intensify the zero-click problem:

• They satisfy user intent directly, often eliminating the need to visit external sites
• For simple queries, factual questions, or general information, LLMs rarely drive users to click external links
• The chat interface encourages users to stay within the experience rather than leave to browse websites.

The Change in User Intent and Behavior with LLMs

User behavior with LLMs differs from traditional search engines:

• Users tend to ask more complex, conversational questions.
• They often engage in multi-turn conversations to refine their understanding.
• They expect complete answers rather than links to explore.
• They use LLMs for creative tasks, not just information retrieval. Read that again!!

This behavior represents a fundamental change in how people access information online, requiring an equally significant adaptation in SEO strategy.

Part 3: Adapting SEO Strategy for AI Visibility

Rethinking SEO: From Rankings to References

In the market of AI search and zero-click results, traditional SEO metrics like rankings and clickthrough rates are no longer sufficient indicators of success. Instead, we need to work for:

• Being referenced or cited by AI systems
• Having content extracted and featured in AI-generated responses
• Building brand visibility even without direct clicks
• Creating authority that transcends traditional search metrics

Let’s explore specific strategies to achieve these goals.

1. Prioritize Long-Tail Keywords and Natural Language Queries

As search evolves toward conversational AI, keyword strategy must adapt:

• Utilize low-volume keywords – Don’t filter out keywords just because they have low search volume.
• Identify conversational queries – Use tools like Google’s People Also Ask, AnswerThePublic, and Reddit discussions to find natural language questions in your niche.
• Incorporate semantic variations – Include synonyms, related phrases, and natural language variations throughout your content.

Implementation Example:

Don’t take it seriously!!
Instead of targeting “best protein powder,” expand to questions like:

• “What protein powder is best for muscle recovery?”
• “How do vegan protein powders compare to whey?”
• “Which protein powders have the least artificial ingredients?”

2. Improve Content Clarity and Structure

AI models extract concise and structured information. Organizing your content to fulfill this extraction is crucial:

• Lead with key takeaways – Start articles with summary points that AI can easily extract.
• Use proper heading hierarchy – Implement clear H1, H2, and H3 structures that organize information logically.
• Include tables of contents with jump links – Make content navigable for both users and AI systems.
• Create scannable content – Use bullet points, numbered lists, and short paragraphs to improve readability.
• Refresh existing content – Update your content library to match these structural best practices, rather than just focusing on new content.

Implementation Example:

For a guide on digital marketing strategies:

• Begin with a concise summary of key findings or recommendations
• Structure with clear headings for each strategy category
• Include a table of contents with links to each section
• Add callout boxes with key statistics or quotes
• Summarize the main points at the end of each section

3. Present Balanced Perspectives

AI models prefer balanced, unbiased content that considers multiple viewpoints:

• Include pros and cons sections – Clearly state benefits and drawbacks for products, services, or approaches.
• Use comparison tables – Create structured comparisons that AI can easily extract and reference.
• Avoid absolute language – Use comparative and nuanced language rather than definitive statements.
• Address counterarguments – Include sections like “Considerations,” “Limitations,” or “When This Approach Isn’t Ideal.”

Implementation Example:

For content about investing strategies:

• Present the pros and cons of each approach
• Create a comparison table of different investment vehicles
• Use phrases like “generally suitable for” rather than “always the best.”
• Include sections addressing risk factors and alternative approaches

4. Strengthen Technical SEO for AI Crawlers

While traditional technical SEO remains important, specific optimizations can help AI systems better understand and reference your content:

• Consider an LLMS.txt file – While standards are still evolving, this file can surface content and information not directly available via traditional crawling.
• Ensure server-side rendering – Make important content visible in raw HTML, not just loaded via JavaScript, as many AI crawlers don’t execute JavaScript.
• Optimize site architecture – Maintain logical structure, strong internal linking, and minimize unnecessary redirects.

Implementation Example:

For an e-commerce product page:

• Add FAQ schema addressing common customer questions
• Ensure product descriptions are visible in the HTML source, not just loaded dynamically
• Create logical category and subcategory structures with clear internal linking

5. Build Authority Through Data-Driven Content

AI models prioritize authoritative, credible information:

• Generate reliable data – Conduct original research, surveys, or case studies to create unique data sets.
• Cite reputable sources – Reference and link to credible external sources to establish authority.
• Create comprehensive resources – Develop content that thoroughly covers topics rather than surface-level overviews.
• Update content regularly – Keep information current and indicate last update dates prominently.

Implementation Example:

For a marketing blog:

• Run an annual survey of industry professionals and publish the findings
• Create data visualizations of proprietary statistics
• Cite academic research and industry reports with proper attribution
• Update benchmark articles annually with current data

6. Optimize for Entity Recognition

AI models rely heavily on entity recognition to understand content context:

• Define key entities clearly – Make sure people, places, concepts, and relationships are explicitly defined.
• Create consistent entity references – Use the same terminology throughout your content.
• Build entity associations – Connect related concepts and terms in logical ways.

7. Produce Quotable Content

Create content elements that AI systems can directly extract and quote:

• Craft concise, stand-alone statements – Write sentences that can be quoted exactly without losing context.
• Use definition-style formatting – Create clear “X is Y” statements that define concepts.
• Include summaries and takeaways – Add conclusion sections that summarize key points into quotable passages.
• Format statistics clearly – Present data points in consistent, extractable formats.

Implementation Example:

For a health and wellness article:

• Include statements like – “Intermittent fasting is a dietary approach that cycles between periods of eating and fasting, typically with a daily 16-hour fast and 8-hour eating window.”
• Format statistics – “According to a 2023 study in the Journal of Nutrition, participants who practiced intermittent fasting for 12 weeks lost an average of 7.3 pounds (3.3 kg) compared to the control group.”

8. Leverage Digital PR for Authority Building

AI search engines take into account online mentions, citations, and brand authority:

• Secure mentions in high-authority publications – Work with journalists and industry publications for coverage.
• Participate in industry conversations – Contribute to online discussions, forums, and communities.
• Build a strong backlink profile – Focus on quality rather than quantity in link building.
• Create shareable content – Develop resources others naturally want to reference and link to.

Implementation Example:

• Develop a strong industry report that publications will want to cite
• Create an expert roundup featuring insights from recognized industry leaders
• Build relationships with journalists covering your industry
• Contribute guest posts to authoritative publications in your niche

9. Consider Wikipedia Optimization

Wikipedia serves as a significant training source for many AI models:

• Establish notability – Build sufficient third-party coverage to qualify for a Wikipedia page.
• Follow Wikipedia guidelines – Adhere strictly to neutrality and citation requirements.
• Create properly sourced content – Ensure all information is backed by reliable third-party sources.

Implementation Example:

• Gather published, third-party sources that mention your brand or organization
• Draft content following Wikipedia’s neutral point of view policy
• Work with experienced Wikipedia editors who understand the platform’s rules

10. Implement Measurement & Tracking

To optimize for AI visibility, you need to track new metrics beyond traditional SEO:

• Track LLM referral traffic – Monitor traffic from AI platforms like ChatGPT and Perplexity.
• Measure AI overview presence – Use tools like Semrush to track your presence in AI-generated summaries.
• Compare performance with competitors – Benchmark your AI visibility against industry experts.
• Monitor brand mentions in AI responses – Test queries related to your industry and track how often your brand appears.

Implementation Example:

• Set up a dashboard tracking LLM referral traffic sources and conversion rates
• Use tools like Scrunch AI or the Semrush AI toolkit to monitor AI platform visibility
• Conduct regular competitor analysis of AI response positioning
• Establish KPIs for AI visibility improvement

Part 4: Advanced Strategies for AI SEO

Creating LLM-Friendly Content: A Specialized Approach

Beyond the fundamental strategies, consider these advanced techniques to optimize content specifically for LLM extraction:

1. Fact Density Optimization

LLMs favor content rich in verifiable facts and data points:

• Incorporate relevant statistics with clear attribution
• Present research findings in digestible formats
• Use data visualizations alongside textual explanations
• Update facts and figures regularly to maintain recency

2. Topical Authority Clusters

Create in-depth coverage across related topics:

• Develop pillar content that broadly covers the main topics
• Create supporting content addressing specific subtopics
• Link content together in logical clusters
• Answer every potential user question within your topic area

3. Content Format Diversification

Different content formats improve visibility across AI platforms:

• Create concise how-to articles for procedural information
• Publish original research with detailed methodology
• Produce expert roundups featuring multiple perspectives
• Maintain updated glossaries of industry terms

The focus from TOFU to MOFU Content

As AI compresses the discovery phase of the buyer’s journey, consider adjusting your content strategy:

• Reduce focus on top-of-funnel (TOFU) keywords
• Increase investment in middle-of-funnel (MOFU) content
• Create content that guides users toward conversion
• Develop comparison and consideration content
• Address specific pain points and solutions

Balancing Traditional SEO and AI Optimization

Rather than abandoning traditional SEO, integrate AI optimization into your existing strategy:

• Layer AI-specific optimizations on top of SEO fundamentals
• Focus on Experience, Expertise, Authority, and Trustworthiness (E-E-A-T)
• Create content that serves both human readers and AI systems

The Future of SEO: Beyond Zero-Click and AI Visibility

Keeping in mind the current situation, it’s essential to look ahead at how SEO will continue to evolve.

• Multimodal Search Integration

  Future SEO will likely center around multimodal search experiences:

  Visual-Text Hybrid Search – As AI models become increasingly sophisticated at understanding images alongside text, optimizing for these multi-search experiences will become crucial.

  Audio and Video Indexing – Future SEO strategies will need to include optimizing spoken content, implementing accurate transcriptions, and structuring video content for AI understanding.

  Augmented Reality (AR) Search Layers – As AR technology becomes more mainstream, we’ll likely see search capabilities embedded within these experiences.

• Personalized AI Search Agents

  The evolution of search will likely include personal AI agents that search on behalf of users:

  Agent-Friendly Optimization – Rather than optimizing for general search algorithms, future SEO may involve making content easily digestible for personalized AI agents that have learned user preferences and needs.

  Intent-Based Discovery – These agents will understand user intent at a deeper level, requiring content that addresses specific user needs rather than just matching keywords.

  Relationship Building with AI Systems – Establishing your brand as an authority that AI agents recognize and trust could become as important as traditional ranking factors.

• Semantic Web Evolution

  The future web will be increasingly structured around meaning rather than just keywords:

  Knowledge Graph Integration – Deeper integration with knowledge graphs will require content that explicitly defines entities and their relationships.

  Web of Facts – Content will need to clearly distinguish between facts, opinions, and perspectives in ways that AI can easily parse.

  Machine-Readable Content Layers – Creating content with layers of structured data specifically designed for machine understanding will become standard practice.

• Privacy-Centric Search

  As privacy concerns grow, the search will adapt accordingly:

  First-Party Data Optimization – With third-party cookies phasing out and privacy regulations increasing, SEO will need to leverage first-party data more effectively.

  Anonymous Discovery Mechanisms – New ways of making content discoverable without tracking users will emerge, requiring new optimization approaches.

  Local-First Search – More search experiences may be processed on-device rather than in the cloud, changing how content is indexed and discovered.

• Real-Time SEO

  The increasing expectation for immediate information will transform SEO:

  Instant Indexing Requirements – Content must be discovered and indexed almost immediately upon publication.

  Live Content Optimization – Strategies for optimizing streaming and live content will become more critical.

  Dynamic Content Updates – Content that updates automatically based on new information will gain preference over static content.

• AI-Assisted SEO Creation

  The tools used to create SEO content will themselves be AI-powered:

  AI Content Collaboration -Working alongside AI to create content optimized for other AI systems will become the norm.

  Predictive Optimization – AI tools will predict future search trends and recommend content strategies before human analysts identify them.

  Automated Testing and Optimization – Continuous testing and refinement of content by AI systems will replace periodic manual updates.

• The Human Element – Expertise and Experience

  There are many instances where humans outsmart AI. Despite these technological stretches, human expertise will remain vital:

  Experience Differentiation – Creating content that provides unique human insights, experiences, and perspectives that AI cannot replicate will become a key differentiator.

  Ethical Authority Building – Demonstrating ethical practices and genuine expertise will become more important as users grow wary of AI-generated content.

  Emotional Connection – Content that establishes emotional connections with audiences will maintain an edge that purely informational AI-generated content cannot match.

Preparing for the Future of SEO

To prepare for these future developments, businesses should:

1. Invest in technological literacy – Ensure your team understands the fundamentals of AI, machine learning, and emerging search technologies.
2. Focus on building genuine authority – Rather than chasing algorithms, establish your brand as a true expert in your field by consistently delivering value.
3. Diversify discovery channels – Don’t rely solely on search engines—build multiple pathways for users to discover your content.
4. Prioritize user experience – The most future-proof strategy remains to create genuinely valuable experiences for your audience, regardless of how they find you.

Oo-oo-aa-aa! Give a halt to monkey 🐵 practices…

The future of SEO will be less about manipulating algorithms and more about creating content ecosystems that naturally align with how people want to discover information.

Brands that focus on providing genuine value, structured in ways that both humans and machines can easily understand, will thrive regardless of how search technology evolves.

Accepting the New Search Model

The rise of zero-click searches and AI-powered search platforms brings not just a challenge but an opportunity for advanced marketers.

The key to success in search is no longer measured solely by rankings and clicks but by strong differentiated visibility across the digital ecosystem.

Brands that optimize for AI visibility now will gain a major advantage as these technologies become increasingly dominant in how people discover and consume information.

The future of SEO isn’t about choosing between traditional search and AI optimization, it’s about creating an integrated strategy that matches both.

Remember – Being visible doesn’t always mean being clicked, but visibility remains the essential first step toward engaging your audience and achieving your business goals.

(Visited 10 times, 10 visits today)