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Tag: Content Optimization

ChatGPT Prefers Early Content: 44% of Citations from Opening Sections

I recently stumbled upon a fascinating study that shows how ChatGPT pulls most of its references from the beginning sections of content. It’s clear from this research that the AI favors straightforward definitions, a balanced tone, and densely packed entities.
According to Kevin Indig, a Growth Advisor who analyzed 1.2 million AI responses and 18,012 citations, ChatGPT has a strong preference for using citations from the top of the content. This was a revelation for me and definitely something to keep in mind when writing.
Why we care. The traditional search landscape often rewards depth and gradual payoffs. However, AI is changing that game by favoring clear entities and direct answers right at the start. If I don’t make sure my key information is front and center, it’s less likely to be cited by AI.
By the numbers. In examining various datasets, Indig’s team found a “ski ramp” pattern—44.2% of citations originate from the first 30% of content, 31.1% from the middle, and only 24.7% come from the final third, with a noticeable drop towards the end.
Breaking it down even further, I learned that at a paragraph level, AI citations largely come from the middle sentences (53%), with 24.5% from the first sentence and 22.5% from the last.
The big takeaway. This really drives home the importance of front-loading critical insights at the article level. Within paragraphs, focusing on clarity and meaningful content rather than trying to hook readers with a dramatic first sentence seems to be more effective.
Why this happens. Large language models like ChatGPT are trained on various styles of writing that prioritize a “bottom line up front” approach. It seems these models use the early sections as a framework for interpreting the rest of the data.
Efficiency and context establishment remain key priorities for these models, even though they can process large sets of data.
What gets cited. Indig noted five key traits of content frequently cited by ChatGPT: definitive language, a Q&A structure, entity richness, balanced sentiment, and business-grade clarity. Learning this has been incredibly insightful for how I craft my content.
Indig’s team looked at a massive volume of data, identifying the traits of highly cited content by analyzing 18,012 verified citations from ChatGPT responses. The study focused on where and why the AI pulls content, using advanced techniques to match responses to source sentences.
Bottom line. It seems the narrative approach of crafting an “ultimate guide” might not be the best for AI retrieval. Instead, a more structured, briefing-style format appears to be more successful.
This study convinced me that writers now face what Indig calls a “clarity tax.” We need to present definitions, entities, and conclusions upfront rather than saving them for the conclusion.
The report. For those interested, you can delve deeper into these findings in The science of how AI pays attention.

Inspired by this post on Search Engine Land.

February 18, 2026
Unlock AEO Success with Content Siloing: Boost Authority & Crawlability

Do you want to take your Answer Engine Optimization (AEO) to the next level? Content siloing might just be the strategy you need. It’s a tactic that has transformed how I approach structuring topics to enhance authority and improve crawlability. Let’s delve into what content siloing is and how you can successfully implement it to boost AI citations.

Think of content siloing as creating a tightly knit topic network within your website, where each piece of content supports and strengthens the others. By organizing related content into isolated ‘silos,’ you not only streamline user navigation but also make it easier for search engines to index and understand the relevance of your content. This improved visibility can lead to better ranking in AI-powered search results.

Implementing content siloing involves a strategic approach to linking content. Begin by identifying your core topics and create subtopics that branch off these main areas. Each article within a silo should link to related content, reinforcing the overall theme and strengthening your site’s authority on the subject matter. This method ensures that your website becomes a trusted source of information in the eyes of both users and search algorithms.

Inspired by this post on HiGoodie Blog.

February 12, 2026
Enhance Marketing Success with Profound’s Knowledge Bases

As someone deeply involved in marketing, I know how crucial it is to have access to accurate and comprehensive company information. That’s why when our marketing team uses Profound to upload Knowledge Bases, it gives us a single source of truth for company-specific data.

This capability empowers us, as agents, to provide the right context about your brand every time we execute a marketing action on your behalf. This streamlined approach ensures consistency and accuracy in representing your brand.

Inspired by this post on Try Profound Blog.

February 12, 2026
Google AI Mode: Why Content Placement Isn’t Key

I recently came across an intriguing study by SALT.agency, focused on Google’s AI Mode and its citation practices. Contrary to popular belief, this analysis shows that AI Mode doesn’t have a preference for content placed “above the fold.”

After sifting through over 2,300 URLs cited by AI Mode, researchers discovered no link between a text’s vertical position on a page and its likelihood of being cited by Google.

Pixel depth is irrelevant. The study revealed that AI Mode pulls text from all over a page, even from content located thousands of pixels down.

Page layout vs. content visibility. While different layouts like large hero images or narrative formats might push text deeper down the page, this doesn’t impact whether it gets cited.

Subheadings make a difference. One key pattern identified was AI Mode’s tendency to highlight a subheading and the subsequent sentence. This suggests Google’s heading structures are crucial for content navigation.

Google’s approach. The assumption is that AI Mode employs fragment indexing technology, breaking pages into sections and pulling the most relevant fragment, irrespective of its position.

Dan Taylor, a partner at SALT.agency, confirms that there’s no secret formula for appearing in AI Mode citations. The focus should always be on crafting well-structured, authoritative content that meets customer needs.

Our takeaway. This study challenges the notion that specific AI-focused templates or rigid structures enhance content visibility in AI Mode. The real work lies in creating meaningful, structured content.

Research background. SALT scrutinized 2,318 URLs in AI Mode responses. The vertical pixel position of each cited fragment was meticulously recorded using a Chrome bookmarklet and a 1920×1080 viewport.

The study. Research: Does Structuring Your Content Improve the Chances of AI Mode Surfacing?

Inspired by this post on Search Engine Land.

February 9, 2026
Unlocking AI Visibility: Why Ranking Content Falls Short

I’ve been contemplating how even when content ranks well on search engines, it can still falter when it comes to AI retrieval. These AI systems assess pages very differently, based not just on their rank, but also on how information is extracted, embedded, and structured.

There’s an intriguing disconnect between traditional ranking and being successfully parsed by AI. A webpage can comply with excellent SEO guidelines and still miss the mark with AI-generated responses and citations.

In many situations, content quality isn’t the issue. It’s about whether the information can be reliably extracted after being segmented and embedded by AI systems.

This challenge is becoming increasingly common as search engines view pages as complete entities, but AI systems dive into the raw HTML to extract meaning from fragments rather than entire pages.

Crucial insights can get lost if they’re not appropriately structured or if they rely too heavily on visual rendering or inference.

This leads to a divergence between what’s visible in search and what’s accessible via AI, where content might exist in an index but lacks substantial meaning for AI retrieval.

The visibility gap is something I’ve been grappling with: Understanding the difference between ranking versus retrieval is key.

As search winds its processes around rankings, AI systems engage with fragments operated within a different representation of similar information. It’s here the visibility gap takes shape.

A page might rank high, but if its embedded content is incomplete or poorly organized, then the AI retrieval process becomes unreliable.

Treat retrieval as an entirely unique visibility factor. It doesn’t override SEO, but increasingly defines whether content can be effectively surfaced, summarized, or cited when AI filters come into play.
Dig deeper: What is GEO (generative engine optimization)?

Another structural issue arises when content never even becomes accessible to AI. Many AI crawlers only parse raw HTML without executing JavaScript or client-side rendering. This creates blind spots, especially for JavaScript-heavy sites where the core content may appear in Google’s index but remains invisible to AI.

Testing if your content appears in initial HTML is quite straightforward. Simply inspect the HTML response at fetch time rather than the version rendered in a browser.

Running requests with AI user agents like “GPTBot” reveals if your site returns blank HTML even if it appears fully populated to users, highlighting its absence in initial responses.

Tools like Screaming Frog can validate this at scale. Disabling JavaScript rendering can reveal what AI systems see—if your essential content only displays with JavaScript, it can be indexed by Google’s search but not by AI retrieval systems.

Keep in mind that even with content returned, excessive code and scripts can hinder extraction by AI systems. Cleaner HTML results in more reliable embeddings, enhancing AI visibility.

To tackle this, deliver fully rendered HTML when AI systems fetch your content. Pre-rendering can often fix these retrieval issues, ensuring content is present in initial responses.

Delivery can be managed effectively at the edge layer, providing AI crawlers with complete pages instantly. Human users receive a dynamic version while AI sees what it needs to extract meaning.

If pre-rendering isn’t viable, focus on ensuring primary content is accessible in a clean initial HTML response, even without script execution.

Columns laden with excessive markup can interfere with proper extraction, diminishing the content’s value.

The next structural failure to consider is when content is optimized for keywords rather than the entities AI seeks. Traditional SEO applies keyword relevance, but AI retrieves based on entity relationships.

Without clear definition, entity signals can weaken, causing pages to underperform in retrieval even if they rank well for queries.

AI evaluates sections independently once extracted, making the consistency of header tags essential to maintaining coherence.

Ensuring sections have a single, defined purpose allows for better embedding when isolated from larger context.

Finally, conflicting signals or metadata can dilute the semantics retrieved by AI, creating noise and ambiguity.

SEO doesn’t have to mean choosing between ranking and retrieval anymore. Both must be prioritized to succeed in today’s landscape.

Inspired by this post on Search Engine Land.

February 6, 2026
How AI Search Shapes SEO Visibility in Higher Education

I recently delved into fascinating research that sheds light on how higher education data informs SEO visibility and AI search. This exploration reveals what truly enhances visibility in this AI-driven era.

Contrary to some beliefs, AI search hasn’t rendered SEO obsolete. Now, the challenge is to excel both in ranking and in earning those vital AI citations.

Every time I Google something these days, there’s a significant chance an AI Overview will appear before any organic results or ads, framing my query, shortlisting sources, and shaping which brands I consider.

According to Ahrefs, AI Overviews now feature for about 21% of keywords. This means that while search rankings remain crucial, AI summaries increasingly dictate early brand consideration.

I’ve noticed that brands aren’t losing visibility just because they slip from the third to the seventh position on search engines. They’re often losing because they’re not even mentioned in AI answers.

Research conducted by Search Influence and UPCEA, where I serve as CEO, reveals insights into AI-assisted search usage and organizational adaptation in the higher education space.

Key Takeaways

AI citations are emerging as a trust signal: Being cited by AI can enhance credibility and secure early user consideration before direct source comparison occurs.

AI visibility is collective: AI pulls from various sources like YouTube, LinkedIn, and beyond—your URL isn’t everything.

Established brands need to adapt: Even well-known brands can be overlooked if their content doesn’t align with how users ask questions.

Most organizations recognize AI’s importance but lack action plans: Awareness exists, but execution is hindered by a lack of ownership and processes.

Content structure determines inclusion: Content that is structured for easy retrieval and decision-making often gets cited over long narratives.

To grasp the evolving search landscape, we need to examine both user behavior and organizational responses.

The study “AI Search in Higher Education: How Prospects Search in 2025” surveyed prospective adult learners and revealed significant patterns in online discovery using AI tools.

The findings show increased AI-assisted discovery and shifts in trust signals. Meanwhile, a UPCEA member institution poll uncovers gaps in AI strategy adoption.

The question isn’t whether AI search will impact your field; it’s whether your brand will be cited, overlooked, or represented by competitors.

Inspired by this post on Search Engine Land.

February 4, 2026
LinkedIn Learns to Thrive Amid AI-Powered Search Challenges

Have you heard the news about LinkedIn’s recent experiences with AI-powered search? It turns out that Google’s AI Overviews have significantly impacted our non-brand B2B awareness traffic, cutting it by up to 60% in some areas, even while rankings remained steady. This shift compels us to rethink our discovery strategies fundamentally.

I’ve noticed we’re transitioning from the traditional ‘search, click, website’ model to a more dynamic approach: ‘Be seen, be mentioned, be considered, be chosen.’ This new paradigm reflects a deeper understanding of modern digital visibility.

By the numbers. Early in 2024, our B2B organic growth team started researching Google’s Search Generative Experience (SGE). By the time SGE evolved into AI Overviews in 2025, the impact was undeniable. Our non-brand, awareness-driven traffic took a hit of up to 60% across specific B2B topics.

Yes, but. Many of the insights we’re gathering are reiterations of established SEO and AEO best practices. I’ve learned that LinkedIn’s guidance emphasizes strong headings, clear information hierarchy, improved semantic structure, and accessibility. It also stresses publishing authoritative, fresh content by experts and moving quickly to gain an early advantage.

Why we care. These strategies should be familiar to anyone versed in technical SEO and content-quality fundamentals. LinkedIn’s article may not present new tactics, but it highlights the relevance of modern SEO/AEO and AI-driven visibility.

Dig deeper. If you’re curious about optimizing for AI search, explore these 12 proven LLM visibility tactics.

Measurement is broken. A significant challenge we face is the ‘dark’ funnel—the difficulty of quantifying how visibility in LLM answers affects our bottom line when discovery occurs without a click.

LinkedIn has seen triple-digit growth in LLM-driven traffic to its B2B marketing websites. However, while we can track conversions from these visits, many websites are also experiencing similar growth. Although it’s an emerging channel, LLM-driven traffic still represents a small portion of overall traffic.

What LinkedIn is doing. To tackle these challenges, we’ve formed an AI Search Taskforce that spans SEO, PR, editorial, product marketing, and more. We’re correcting misinformation in AI responses, publishing new content optimized for AI visibility, and testing social content for AI discovery strength.

Is it working? It’s exciting to see our efforts yielding results. Our early tests are showing a meaningful increase in visibility and citations, particularly from our owned content. According to one external datapoint from Semrush, our structural advantage in AI search is significant, with Google AI Mode citing LinkedIn in 15% of responses.

Incomplete story. While LinkedIn’s developments are noteworthy, some details remain unclear. We’re still waiting on specifics like the exact topics behind the traffic decline, how much click-through rates have softened, sample sizes, and timeframes. These details could provide clarity on the broader industry impact.

Bottom line. I believe LinkedIn’s insights affirm that visibility is the new currency in digital marketing. However, there’s still much to prove if our playbook truly differentiates us from basic SEO practices.

Curious to learn more? Check out LinkedIn’s detailed article on our adaptation strategies: How LinkedIn Marketing Is Adapting to AI-Led Discovery

Inspired by this post on Search Engine Land.

February 3, 2026
How Human Experience Shapes Your Search Visibility Today

I’ve noticed that in today’s digital landscape, our search performance is heavily influenced by how people engage with and trust our content, even beyond the initial click. This concept of Human Experience Optimization (HXO) connects SEO with UX, conversion rate optimization (CRO), and brand signals.

I used to think of SEO as simply figuring out what algorithms liked best—focusing on keywords, links, and technical details. But now, things have changed.

Now, my visibility is more about earning trust and being useful. It’s not just about having the right signals or being easy to crawl; it’s about experience.

Search engines today pay attention to how people interact with brands over time, marking the rise of HXO. This involves enhancing how individuals experience, trust, and engage with my brand across search, content, product, and conversion channels.

Instead of replacing SEO, HXO broadens its perspective to match how search engines now evaluate performance. Experience, engagement, and credibility are becoming essential parts of visibility itself.

Let’s dive into why HXO is crucial now and its influence on the merger of SEO, UX, and conversion strategies.

Why HXO Matters Now

Contemporary search engines now reward outcomes over mere tactics. They align with Google’s focus on user satisfaction rather than isolated page signals.

In practice, we see signals relating to questions like: Do users engage or bounce? Do they come back? Do they recognize the brand later? Do they trust the information enough to act on it?

Today, visibility is influenced by overlapping forces like user behavior signals, brand signals, and content authenticity.

HXO arises in response to the saturation of AI-generated content and diminishing returns from traditional SEO tactics unsupported by a strong experience and brand coherence.

In a nutshell, ignoring human experience is no longer an option if we want to remain competitive.

The Convergence: SEO, UX, and CRO Are No Longer Separate

SEO, UX, and CRO used to operate as distinct disciplines. But that separation doesn’t work anymore.

In modern search experiences, traffic alone means little without engagement. Engagement without a path to action limits impact. Conversion struggles without trust.

HXO acts as a unifying layer: SEO determines arrival, UX ensures understanding, and CRO transforms understanding into action.

In this realm, optimization focuses on supporting attention and trust over time, not just securing a single click.

E-E-A-T is a Business System, Not Content Guidelines

A common misconception is that E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) can be “added” to content with elements like author bios and citations. These help, but E-E-A-T requires more—it’s about long-term brand credibility.

E-E-A-T involves real expertise, transparency, consistency, and accountability, evaluated holistically by search engines.

The consistent systems and patterns reinforce E-E-A-T beyond little tweaks on a page.

First-Hand Experience Signals Are the New Differentiator

Today’s search landscape is filled with well-structured content. First-hand experience, such as original research and insights from lived experiences, sets content apart from mere aggregation.

Creators and operators excel by providing insights that reflect direct involvement and real-world expertise.

This emphasizes the importance of the human element in content creation.

Helpful Content Is a Brand Problem, Not an SEO Problem

Content that fails to be helpful often reflects a lack of clarity in a brand’s positioning and how it serves its audience.

When I look at content that resonates well, it reflects actual understanding of the audience and consistent intent throughout brand interactions.

SEO aids in discoverability, but genuine helpfulness requires brand consistency and deeper alignment.

Closing these gaps involves understanding how audiences experience and engage with the brand beyond a single interaction.

How to Start Practicing Human Experience Optimization

Practicing HXO starts with understanding people and why they search, not just focusing on keywords. It involves transforming keyword strategies into audience strategies and auditing experience across all user touchpoints.

1. Shift to Audience Strategy

Keywords are informative, but we need deeper insights into motivations and contexts.

2. Audit the Complete Experience

Consider trust, clarity, and consistency across all channels and touchpoints, not just individual pages.

3. Align Teams Around Experience Outcomes

Bridging gaps between marketing, product, content, and design teams can achieve more cohesive user experiences.

4. Measure What Truly Matters

Beyond traditional metrics, focus on engagement quality, brand recall, and trust-driven conversions.

Optimize for Humans to Earn Algorithms

Ultimately, HXO is about consistently delivering valuable experiences. Reliable brands in search are grounded in real experiences and useful content, earning visibility through the lasting impressions left on users.

Inspired by this post on Search Engine Land.

February 2, 2026
Boost Your Brand with CMS and Slack Integrations

When I integrated WordPress, Sanity, and Slack, I unlocked the ability to effortlessly manage and update content. This integration dramatically improved how customers discover my brand, products, and services through AI Search.

With these native integrations, I’ve streamlined my workflow, enabling me to publish, update, and coordinate tasks more efficiently. This not only enhanced my brand’s visibility but also optimized customer interactions at every touchpoint.

Embracing these tools has revolutionized my content operations, ensuring my digital presence is cohesive and compelling. The ease of use and the seamless syncing of data have allowed me to focus on what truly matters—creating value for my customers.

Inspired by this post on Try Profound Blog.

January 30, 2026
Mastering AI Search: Leverage Social Platforms Today

When diving into the complexities of AI search, I discovered that dominating social platforms is crucial. Recently, I explored a study of 6.1 million citations, which revealed an interesting trend: AI answers are increasingly influenced by social media.

Social platforms have become essential in the AI citation graph, and I’ve found that optimizing for this shift can significantly boost brand visibility. If you’re like me and want to stay ahead, integrating social strategy into AI search is a must.

By following these insights, I believe brands can enhance their online presence and ensure their content is favored by emerging AI technologies. Let’s embrace this evolution and maximize our impact in the AI-driven world.

Inspired by this post on HiGoodie Blog.

January 26, 2026

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