Passage Optimisation: How to Get Your Content Cited in Google AI Overviews and ChatGPT

Your content might contain the perfect answer to a searcher's question, but if it's buried in a wall of text, neither Google nor AI platforms will find it. Passage optimisation is the practice of structuring your content so search engines and large language models can extract, understand and surface specific sections as direct answers. Google first introduced passage ranking to its traditional search algorithm back in 2020 - well before AI search platforms like ChatGPT emerged - stating it would improve 7% of search queries globally. With AI Overviews now appearing for a meaningful share of queries, often in the low-to-mid tens of per cent, varying by market, device and query intent. This guide reveals exactly how to optimise your content at the passage level for both traditional search and AI platforms.

A Quick Guide to Passage Optimisation

Passage optimisation involves structuring individual sections of your content so search engines can rank them independently for specific queries. Rather than evaluating only page-level relevance, Google identifies individual passages that directly answer your questions, even when buried within longer content. Effective passage optimisation combines clear heading hierarchies, self-contained paragraphs that make sense in isolation, and precise language that AI systems can easily extract for citations and summaries.

What Is Passage Optimisation?

Passage optimisation is the practice of structuring content so search engines and AI systems can identify, extract and rank individual sections independently from the overall page. Instead of treating pages as monolithic units, modern search technology evaluates content at a granular level and returns specific passages that best answer your queries.

Google introduced passage ranking in 2020, describing it as a breakthrough that allows it to find the "needle in a haystack" information you seek. The system uses AI to understand the relevance of specific passages, not just overall page relevance. This means a well-structured section can rank for relevant queries even when the broader page covers multiple topics.

The technical mechanism operates via Google's SMITH algorithm (Siamese Multi-depth Transformer-based Hierarchical Encoder), which processes document passages independently while modelling their relationships to the entire page. Unlike the BERT algorithm, which focuses on sentence-level understanding, SMITH excels at comprehending longer passages and their context within comprehensive content.

Why Passage Optimisation Matters Now

Three converging trends make passage optimisation essential for 2025 and beyond.

1. First, AI platforms like ChatGPT, Perplexity and Claude use Retrieval Augmented Generation (RAG) to answer questions. RAG systems don't read entire pages; they break content into chunks, store them in databases, and retrieve the most relevant passages to generate responses. Clear structural elements (headings, lists, tables) make content easier for both search engines and LLMs to parse and cite.
2. Second, Google AI Overviews appear for a meaningful share of queries, often in the low to mid tens of per cent in recent studies. Presence varies by market, device and intent with measurement is still evolving. These summaries synthesise information from multiple sources and frequently cite specific passages rather than whole pages. Structure clear, self-contained passages to improve your chance of citation and track AIO visibility cautiously as it can fluctuate over time.
3. Third, voice search continues growing, with digital assistants pulling answers from well-structured content. Voice responses demand concise, extractable passages that can be spoken aloud naturally, making passage-level optimisation critical for this growing search channel.

How Google's Passage Ranking Works

Understanding the mechanics behind passage ranking helps you structure content effectively. Google's approach differs fundamentally from traditional page-level ranking.

The Technical Foundation

When Google crawls your page, it still indexes the entire document. However, its AI systems now also process individual passages to understand their standalone relevance. According to Google's official documentation, passage ranking uses AI to identify sections or passages of a web page and assess their relevance to a search.

This doesn't mean Google indexes passages separately from pages. Instead, it considers passage relevance as an additional ranking factor alongside traditional signals like:

• Page authority
• Backlinks
• Overall content quality

A page with strong domain authority and a highly relevant passage can rank well for specific queries even when competing against pages more narrowly focused on that topic.

What Passage Ranking Means for Rankings

The practical impact varies by content type and query intent.

• Long-form content with multiple subtopics gains the most from passage ranking. A comprehensive guide covering ten aspects of a topic can now rank for specific questions about any of those aspects, not just the primary topic. This rewards depth and comprehensiveness over narrow, siloed content strategies.
• Pages with poor structure but valuable information also benefit. Google explicitly stated that passage ranking helps surface content that might otherwise be overlooked because information is "buried" on less-organised pages. However, this doesn't excuse poor structure; well-organised content with clear passages still outperforms disorganised alternatives.
• Highly specific, long-tail queries see the greatest impact. Google designed passage ranking to help with "very specific searches" where the exact answer might be just a single sentence within a broader page. If your content thoroughly covers a topic and includes specific answers to niche questions, those passages can now surface for relevant searches.

The Connection Between Passage Optimisation and AI SEO

Passage optimisation has become inseparable from AI SEO because both Google and AI platforms process content through similar mechanisms. Understanding this connection reveals why proper structuring delivers compounding benefits.

How AI Platforms Process Your Content

Large language models and AI search engines don't read content as humans do. They tokenise text into chunks, create vector embeddings to understand meaning and store these in databases for retrieval. When you ask questions, the system searches for passages whose embeddings are most similar to the query and uses those passages to generate responses.

This retrieval-then-generate approach means your content competes at the passage level rather than the page level. A single well-structured paragraph can be retrieved and cited even when competing against thousands of other documents. Content with clear formatting sees 28-40% higher visibility in LLM responses because it's easier for systems to parse and extract.

Why Structure Determines AI Visibility

AI systems rely on structural cues to understand content organisation and identify key passages. Headers signal topic transitions and passage boundaries. Short paragraphs create distinct, self-contained units that can be extracted independently. Lists and tables provide structured data that AI systems can easily parse and present.

Search Engine Journal analysis found that LLMs use heading structure to understand hierarchy, favour self-contained thoughts in short paragraphs, and extract content most easily from bullet points, tables and FAQ formats. Clean structure ensures your content is "selectable for citation or summarisation, even if the rest of the page isn't used."

At Rankmax, we've implemented passage-level optimisation across all client campaigns. Our B2C AI SEO case study demonstrates how semantic HTML and passage-level optimisation helped a client achieve $7.7M in organic revenue within 11 months while gaining visibility in AI search platforms.

How to Implement Passage Optimisation

Effective passage optimisation combines content structure, writing style and technical implementation. Each element reinforces the others to maximise both Google rankings and AI citations.

1. Create a Clear Heading Hierarchy

Your heading structure signals passage boundaries to search engines and AI systems. Use H2 headings for major topic sections, H3 for subtopics and H4 for specific details when needed. Each heading should clearly describe what follows, helping systems understand content organisation without reading whole paragraphs.

Effective heading hierarchies flow logically from general to specific. Start with foundational concepts, then progress to implementation details, edge cases and advanced considerations. This structure mirrors how both humans and AI systems process information, improving comprehension and extraction accuracy.

2. Write Self-Contained Paragraphs

Each paragraph should make sense when read in isolation. Avoid references like "as mentioned above" or "this approach" without clarifying what you're referring to. AI systems extract individual passages without surrounding context, so each section must provide complete information.

Keep paragraphs focused on single ideas. When you shift topics, start a new paragraph with clear topic sentences. This practice creates natural passage boundaries that align with how search systems parse content.

For passage optimisation, aim for paragraphs of 2-4 sentences that deliver complete thoughts. We recommend using frequent subheadings about every 300 words and concise, focused paragraphs to aid LLM comprehension.

3. Include Direct Answers to Questions

Structure content around the specific questions your audience asks. Use those questions as headings or lead with direct answers in your first sentence, then expand with supporting details. This pattern matches how both featured snippets and AI Overviews select content to display.

The most effective pattern: question heading, direct answer in 1-2 sentences, supporting explanation and examples or data. This structure works for both human readers scanning for answers and AI systems extracting passage content.

4. Use Structured Formats for Key Information

Lists, tables and FAQ sections create explicitly structured content that AI systems can parse reliably. When presenting multiple options, steps or comparisons, use formatted lists rather than embedding information in prose paragraphs.

Tables work particularly well for comparisons, specifications and data summaries. They present information in a structured format that AI systems can interpret accurately and present clearly in generated responses.

FAQ sections serve dual purposes: they address specific questions and create well-structured passages with clear question-and-answer pairs. Including comprehensive FAQs improves both user experience and AI citation potential.

5. Implement Semantic HTML

Proper HTML markup reinforces your content structure for search engines. Use semantic elements like headings (H1-H6), lists (ul, ol), tables, and definition lists where appropriate. Avoid overly complex templates that obscure the content structure.

Schema markup provides additional signals about content organisation. Article, FAQ, and HowTo schemas help search engines understand your content type and structure, potentially improving both rankings and eligibility for rich results.

Common Passage Optimisation Mistakes

Understanding what doesn't work saves time and prevents damage to rankings. These common mistakes undermine passage optimisation efforts.

1. Writing for Keywords Instead of Answers

Stuffing keywords into passages without providing genuine answers hurts both rankings and AI visibility. Modern search systems use semantic understanding, not keyword matching. They evaluate whether passages actually answer your questions, not just whether they contain relevant terms.

Focus on comprehensive answers that demonstrate expertise. Include specific details, examples and data that prove your content deserves ranking. AI systems increasingly favour content with verifiable statistics, with visibility 30-40% higher for content featuring original research and concrete data.

2. Creating Long Paragraphs Without Structure

Dense paragraphs bury the information AI systems need to extract. When passages run 200+ words without breaks, systems struggle to identify discrete, extractable units. The result: your valuable content gets overlooked in favour of competitors who structure information more clearly.

Break long explanations into shorter paragraphs with distinct focuses. Use lists to present multiple items. Insert subheadings when topics shift. These structural elements create natural passage boundaries that improve both human readability and machine processing.

3. Relying on Context From Other Sections

Passages that depend on earlier content for context fail as standalone units. Phrases like "this method," "the above approach," or "as we discussed" create incomplete passages that AI systems cannot use effectively.

Each section should provide enough context to be understood independently. Repeat key terms rather than using pronouns. Briefly restate relevant background rather than assuming readers have absorbed earlier sections.

4. Ignoring the First 100 Words

Lead with the answer. Open with a concise, self-contained passage that states the definition, outcome, or key recommendation, then follow with supporting detail. Front-loading helps readers and retrieval systems quickly recognise relevance and increases the likelihood that a passage is extracted or cited, without implying a specific ranking weight.

Measuring Passage Optimisation Success

Tracking passage-level performance requires different metrics than traditional page analytics. Focus on signals that indicate passage extraction and citation.

AI Overview Citations

Monitor whether your content appears in Google AI Overviews for relevant queries. While no perfect tracking solution exists yet, manual checking of key queries reveals AI Overview visibility. Tools like Semrush and Ahrefs do offer AI Overview tracking features.

Featured Snippet Acquisition

Featured snippets indicate Google selected a specific passage from your page as the best answer. Track snippet appearances for target queries using Google Search Console or rank tracking tools. Increasing snippet wins suggests effective passage structure.

Search Console Impression Patterns

Pages with well-optimised passages often receive impressions for queries beyond their primary target. Check Search Console for long-tail queries where specific passages might be ranking. Growing query diversity suggests passages are earning independent visibility.

Click-Through Rates on Specific Queries

Compare CTR across different query clusters. Queries where your content appears as a featured snippet or in AI Overviews often show different CTR patterns. Understanding these patterns helps refine the passage optimisation strategy.

Frequently Asked Questions

How is passage optimisation different from on-page SEO?

Traditional on-page SEO focuses on page-level signals like title tags, meta descriptions and overall keyword optimisation. Passage optimisation goes deeper, structuring individual sections so they can rank independently for specific queries. While on-page SEO helps pages rank in search results, passage optimisation ensures specific content sections surface for relevant searches. Both work together; passage optimisation builds on solid on-page fundamentals rather than replacing them.

Does passage optimisation work for short content?

Passage optimisation delivers the most significant benefit for long-form content that covers multiple subtopics. Short, focused pages already function as single passages. However, even shorter content benefits from clear structure, direct answers and self-contained paragraphs. The principles apply universally; the impact scales with content length and topic diversity.

How long should optimised passages be?

Optimal passage length depends on the question being answered. Simple definitions work well in 1-2 sentences. Complex explanations may require 3-4 paragraphs. The key is completeness, so each passage should fully answer its target question without requiring readers to look elsewhere. For paragraph-type featured snippets, 40–60 words is a common sweet spot according to industry studies.

Will passage optimisation help with ChatGPT and Perplexity citations?

Passage-level structure can increase citation likelihood, but visibility varies by platform's crawling, indexing and retrieval. Perplexity, for example, often retrieves sub-document units (passages) before generation.

How quickly does passage optimisation show results?

Timelines vary. Google crawling and indexing can take days to weeks; meaningful ranking movement often takes weeks to months. AI platform citations depend on each platform’s crawl/index refresh and aren't guaranteed to be faster.

Should I restructure existing content or create new content?

Both strategies have merit. Restructuring high-performing pages that lack passage optimisation often yields quick wins, since authority already exists. Creating new content with proper structure from the start builds a foundation for long-term visibility. Prioritise restructuring for pages ranking positions 5-20, where improved passage relevance can push content into featured snippet territory.

Does passage optimisation affect voice search?

Yes. Clear, self-contained passages can increase the chance your content is used in voice responses across platforms. Sources vary by assistant and are not always disclosed, so treat this as a best-practice benefit rather than a guarantee. Prioritise speakable writing: lead with the answer, use everyday language, short clauses and scannable numbers, and avoid long, nested sentences.

Start Structuring Content for the AI Search Era

Passage optimisation has evolved from a nice-to-have into a ranking essential. Google's passage ranking was estimated at launch to improve about 7% of searches, and AI Overviews now appear for a meaningful share of queries, with the share varying by market and intent. Start with your highest-potential pages, apply the principles in this guide, and measure gains in snippet acquisition, AIO citations and query coverage. Ready to accelerate results? Book a 45-minute discovery call with me to map your path to visibility across Google and AI search.