On-page content formats answer engines actually favor [new research]
It seems like every brand is scrambling to get a piece of the pie in this new answer engine optimization (AEO) world. But what if you could get ahead of the curve by knowing the best on-page content formats...
It seems like every brand is scrambling to get a piece of the pie in this new answer engine optimization (AEO) world. But what if you could get ahead of the curve by knowing the best on-page content formats for AI as verified by research? I pored over results from the new HubSpot State of AEO 2026 report and Wix Studio’s AI Search Lab research on most-cited content types to find out. In this article, I’ll cover which formats earn the most citations across ChatGPT, Gemini, AI Overviews, and Perplexity, why LLMs favor them, and how to apply them to both new and existing pages on your site. You’ll also find format-by-format templates, a five-step audit for legacy content, a measurement framework for AI visibility, and a governance model for keeping cited pages fresh. Table of Contents The best on-page content formats for AI across the board are listicles, articles, product pages, and category pages, while comparison content tops ChatGPT specifically, at a 95% citation rate — the highest of any format on any engine. These conclusions come from two independent 2026 datasets — HubSpot’s State of AEO 2026 and Wix Studio’s AI Search Lab — which analyzed over a million AI citations between them. Content type is one of the three layers that influence citations. Cited pages pair the format with an intent-matched title pattern (“What is X,” “X vs. Y,” “How to X,” “Best X”) and citation-correlated structural elements: statistics and data, visible last-updated dates, author bios, and FAQ sections with schema. Match the format to buyer intent, then layer the title pattern and structural signals on top. Listicles, articles, product pages, and category pages are the four most-cited content types overall, and comparison content wins ChatGPT outright with the highest single-citation rate in either dataset. That’s the picture across two independent datasets: HubSpot’s State of AEO 2026, which analyzed thousands of citation themes between December 2025 and March 2026, and Wix Studio’s AI Search Lab, which indexed over a million citations across 75,000 AI answers. A scope note: This article covers on-page content formats — the pages you publish on your own domain. Third-party discussion content (Reddit, G2, LinkedIn, Quora) sits outside that scope, but it’s worth flagging that discussions account for 17.35% of Perplexity citations in the Wix dataset, more than double the cross-engine average. If Perplexity matters to your buyers, an off-site discussion strategy is a parallel effort to the on-page work in this piece. A taxonomy note: Both studies treat “blog posts/articles” and “listicles” as separate categories, even when the listicle lives on a blog. So throughout this article, “article” and “blog post” refer to informational long-form content (the “What is X” or explainer kind), and “listicle” is treated as its own format. Content type is only one of three on-page layers that correlate with high AI citations: For the rest of this article, I’ll use “format” as the umbrella term under which all three sit. Both datasets from HubSpot and Wix agree on the same top three formats as cross-engine safe bets: listicles, articles, and product pages. Wix, in particular, found category pages as the fourth most-cited, and HubSpot discovered that comparison pages are favored by ChatGPT specifically. Here is the engine-by-engine breakdown from State of AEO: State of AEO 2026 measured citation rates — the share of queries where the answer engine cited at least one page of that content type — across eight content categories. The per-engine leaders: Caveat on ChatGPT: Every content type measured on this answer engine scored 69% or higher, with most clustered between 86% and 95%. ChatGPT is comparatively format-agnostic. Content type matters more in AI Overviews, where rates vary widely, from 5% (news) to 42% (blog posts). State of AEO’s top-three claim rests on three layers of evidence in the report: Wix Studio’s AI Search Lab, built with Peec AI, looked at the same question from the opposite angle: share of citations across all engines, not rate within each. Their top three: Those three formats earned more than half of every citation Wix measured. The practical takeaway: Listicles, articles, and product pages are the safe cross-engine bets. Comparison content earns its place by winning ChatGPT outright, and how-to earns its place by leading on title pattern in AI Mode and Perplexity and over-indexing on informational queries in the Wix data. Layer engine-specific tweaks on top: comparison framing for ChatGPT, informational depth for AIO and Gemini, and step-by-step structure for AI Mode. In State of AEO’s dataset, title pattern is the single most significant citation factor when writing meta titles. Here’s what it found: Including the year in the title and H1 correlates with higher citations in AI Overviews, according to State of AEO. My advice would be to only commit if you’ll genuinely refresh the post each year; a title that still says “2024” in 2026 might hurt your case. Per HubSpot’s State of AEO 2026: Pro tip: HubSpot AEO tracks how your brand shows up across ChatGPT, Gemini, and Perplexity, surfaces which content types are getting cited in your category, and recommends where to invest next. As the Wix Studio research notes, “User intent is the strongest predictor of which content types get cited.” A comparison summarizes differences. A best-of list ranks options. A step-by-step guide walks the reader through a procedure. An FAQ matches a natural-language question. Check out the table below to get suggestions on how to match user intent to content format. Buyer intent Content type Title pattern Structural must-haves Engines you're most likely to win Informational ("What is X?") Article/blog post "What is [X]?" FAQ section + schema markup, statistics, author bio AI Overviews, Gemini Comparative ("X vs. Y") Comparison article "X vs. Y" Side-by-side table, statistics, last-updated date ChatGPT, SearchGPT Commercial ("Best X," "X tools") Listicle "Best [X]" or numbered list Numbered H2s/H3s, last-updated date, FAQ section AI Overviews, Gemini, Perplexity, ChatGPT Procedural ("How to do X") Step-by-step guide "How to [X]" Numbered steps + HowTo schema, screenshots Google AI Mode, Perplexity Transactional/navigational (ready to buy) Product listing, landing page, or category page Product or feature name ItemList or product schema, specs in tables Perplexity, plus all engines for navigational queries The best content formats for AI search optimization have three things in common: They’re predictable to extract, they match patterns LLMs already produce, and they show citation signals to indicate they’re a trusted source. LLMs don’t read pages like humans do. They process tokenized chunks and weight information unevenly. Stanford research documented a U-shaped accuracy curve in which LLM performance drops when relevant information sits in the middle of long input contexts rather than at the start or end. Consistent headers, short sections, and front-loaded answers shift important content into the positions models actually use. A separate 2026 GEO-SFE preprint found that lists, tables, and similar structured formats had 43% better LLM extraction accuracy than similar prose. Schema markup (such as FAQPage, HowTo, ItemList, Article, etc.) tells crawlers what kind of page they’re on before they parse a word. Visible last-updated dates and author bios signal recency and authority. Declarative claims with named subjects and verifiable facts give models language they can lift directly. The same GEO-SFE preprint found that structural changes alone produced an average 17.3% citation lift across six generative engines, without changing the content’s actual meaning. None of these signals replaces good content, but they make good content easier to trust and easier to attribute. Some structural elements are specific to certain formats. Numbered steps belong in how-to guides, for instance, while side-by-side product tables belong in comparison pages. But the structural elements below apply to almost every page, regardless of content type. They create a baseline structure that makes any format easier for answer engines to understand, extract, and summarize. The universal structural elements: Map each schema type to the page that fits: Article for editorial posts, HowTo for procedural guides, FAQPage for Q&A sections, ItemList for listicles and ranked roundups. Include author and organization schema on every page so it declares who wrote it and which brand stands behind it. A note on schema markup: It’s debated in the AEO field. I can’t guarantee that implementing it will magically boost your AI citation rates, but I can say that it’s good hygiene. Adding schema markup is an SEO best practice, and because answer engines use search indexes (such as those from Google and Bing) to help generate answers, it may indirectly influence how AI interprets your content. A single page is one citation candidate; a topic cluster creates multiple connected entry points into the same subject. Build a pillar page that defines the topic broadly, link subtopic pages back to it, and cross-link related cluster pages where they share concepts, entities, or follow-up questions. Google’s own guidance treats internal links as a signal for both users and crawlers navigating between pages on a site, and its AI optimization guide confirms that generative AI features in Search pull from the same index — and the same ranking and quality systems — that traditional results do. In AEO terms, that means a well-linked cluster can make your site easier to crawl, easier to understand, and more likely to surface across the fan-out queries answer engines use to assemble responses. It does not guarantee citations, but it gives answer systems more relevant, connected pages to choose from. Five page types earn the bulk of AI citations across answer engines. Each maps to a different intent, takes a different shape, and rewards different structural choices on top of the universal structural elements from the previous section. The templates below assume you’ve already nailed the basics — H1 matching the intent, intro TL;DR, H2/H3 hierarchy every 150–200 words, descriptive FAQ section, last-updated date — and focus only on what’s distinctive about each format. Note: The five formats come from the State of AEO and Wix data. The structural choices inside each template are part measured (statistics, schema, FAQ, title patterns) and part principle-led — drawn from research and my own AEO work, but not from studies isolating those exact choices. Best for: Informational queries (“What is X,” “Why does X happen,” “How does X work” as a concept) Blog posts and informative articles lead citations in AI Overviews (42% citation rate) and Gemini (76%) per State of AEO, and account for 45.48% of citations on informational queries in Wix Studio’s analysis — more than any other format on that intent. They’re the safest cross-engine bet when the searcher wants to understand a concept rather than buy something. Template: Best for: Commercial queries (“Best [X],” “Top [N] [X],” “[X] tools”) Listicles are the most-cited content type in Wix Studio’s cross-engine data, accounting for 21.9% of all citations and 40.86% of citations on commercial queries. In State of AEO, listicle title patterns (“Best [X],” numbered lists) work across AI Overviews, Gemini, Perplexity, ChatGPT, and SearchGPT. Template: Brand-name H2s make it clear which entity each section is about, while vague headings like “Our second pick” require LLMs to rely on surrounding text to identify the brand being discussed. Best for: Comparative commercial queries (“[Brand A] vs. [Brand B],” “Is [X] better than [Y]?”) Comparison content has the highest citation rate of any format in State of AEO at 95% in ChatGPT, and is the top title pattern for both ChatGPT and SearchGPT. Template: Best for: Navigational and transactional queries where the searcher already knows the brand or product (“[Brand] [product name],” “[Brand] [feature name]”) In Perplexity, product listings and landing pages earn an 84% citation rate per State of AEO — the highest of any format on that engine. Wix Studio’s analysis places product pages at 13.7% of all AI citations across engines, with the share concentrated where the buyer is closest to a decision — 24.88% of transactional citations and 21.95% of navigational citations. These pages aren’t where readers come to learn about a category; they’re where the searcher already knows the product and wants the specs or confirmation of a feature. Template: Best for: Navigational and commercial-exploratory queries where the searcher wants to browse options in a category, not read editorial commentary on them (“[Category] tools,” “[Category] software,” “[Category] in [location]”) Wix Studio treats category pages as a distinct content type from product pages, at 11.3% of all AI citations. The intent split is where they earn their place: 18.31% of navigational citations, 14.97% of transactional citations, and 12.42% on commercial queries. They’re even more visible in ecommerce (15.96%) and home repair (14.95%) than the cross-industry average. State of AEO doesn’t break category pages out separately from product listings and landing pages, so the segmentation here is Wix-only. Template: Start optimizing content for AEO on pages that already earn organic traffic. Structural updates alone may compound on the SEO equity you’ve built. The audit below targets the highest-leverage changes first. Long paragraphs are the best candidates for AEO optimization. When creating content for generative AI to extract from, restructure walls of text this way: Updating pages by hand gets tedious and tough to track. HubSpot Content Hub gives teams one CMS to update and republish content at scale, with built-in SEO recommendations that flag on-page issues as you work through the audit list. Be sure to check out our guide on how to use AI in your SEO workflow, too. The answer-engine-specific recommendations come from HubSpot AEO, which surfaces what to fix; Content Hub is where you fix it. Content format changes only matter if you can prove they moved the metric. AEO-savvy marketers measure AI visibility alongside page-level performance and regularly pull reports to track the progress of both. Three metrics form the baseline across ChatGPT, Gemini, and Perplexity for a tracked set of prompts: If you do it manually, you’ll have to run a pre/post comparison for every retrofitted page by sending its prompts through each engine before and after the update. But HubSpot AEO automates prompt tracking and provides brand visibility scores, share of voice scores, and information on citations. Pro tip: AEO Grader is a free tool that gives marketers a scored snapshot of how answer engines represent their brand today. HubSpot AEO automates prompt tracking across answer engines and benchmarks competitor share for those prompts, helping marketers improve their brand’s AI visibility. Visibility doesn’t always translate to revenue, so map each optimized page to its conversion role — demo signups, content downloads, trial starts — and track the engagement and conversion delta after the update. Referrer data from ChatGPT, Gemini, and Perplexity is incomplete or missing in many analytics tools, so AI-sourced sessions often land in “direct” traffic. Branded search volume and direct-traffic shifts are useful proxy signals when referrer data falls short. Set a monthly baseline and a quarterly deeper review. At least monthly, re-run your tracked prompts across the engines and log changes against the baseline. Quarterly, audit which pages gained or lost citation share and decide what to update next. HubSpot AEO sends you weekly score tracking and trend alerts, saving you time and helping you quickly assess results. Governance keeps every page updated and citable long after the first audit. Here’s a framework you can use to make sure your content stays fresh for your audience, search engines, and answer engines. Assign one owner per content cluster. The owner runs the cluster’s review cadence and handles any updates triggered between reviews. Common update triggers worth noting: The internal QA checklist a cluster owner can run before re-publishing: Refresh the parts of the page that most directly carry citation signals. The prompts you track should reflect the concerns your potential buyers have. AEO in Marketing Hub Pro+ uses your Smart CRM data to inform prompt suggestions, so what you’re monitoring stays anchored to your business context (not made up from scratch). Pair that with AI content optimization tools to make changes to your content that can help boost AI citation. No. Schema isn’t required for AI citations, but the State of AEO 2026 dataset flagged it as a structural element worth implementing, particularly schema markup paired with a properly formatted FAQ section, which lifted citation rates in Gemini, Google AI Mode, and Perplexity. Treat schema as a way to tell crawlers what each page is, not a cheat code for citations. Apply Article, HowTo, FAQPage, or ItemList only where they accurately reflect the content; marking up elements that don’t exist on the page violates Google’s structured data guidelines. There’s no magic number for frequency of refreshing AI-optimized content, but there are some events that should trigger an update. Re-test a page’s target prompts as soon as you see a citation drop, a competitor enter the answer, or a major model release from OpenAI, Anthropic, Google, or Perplexity. Run monthly visibility re-checks across your tracked prompts, and quarterly audits of the pages that lost ground. HubSpot AEO automates the prompt-level tracking and flags trend shifts so you can act quickly. Yes, major AI companies separate training crawlers from search crawlers, and the directives go in robots.txt. Block GPTBot to stop OpenAI from using your content for training while keeping OAI-SearchBot allowed so ChatGPT live web search citations remain possible. Block Google-Extended to opt out of Gemini training while leaving Googlebot — which is used for Google Search — able to crawl. Check each company’s bot documentation to confirm what each user-agent actually does before adding it to your robots.txt. Start with the format that matches the dominant intent behind your buyers’ searches. If most of your high-value queries are informational (“What is X,” “How does X work”), articles are your best entry point; they lead citations in AI Overviews and Gemini per HubSpot’s State of AEO 2026. If they’re comparative (“X vs. Y”), prioritize comparison posts, which earn the highest citation rate in ChatGPT. If buyers come in through commercial queries (“Best X,” “Top N X”), listicles cover the broadest cross-engine range. From there, audit the pages already ranking for those intents and optimize them first. Building upon existing organic equity is the fastest path to citation wins.TL;DR The Best On-Page Content Formats for AEO
What are the best on-page content formats for AEO?
Content Types AI Engines Cite Most

Title Patterns That Get Cited

Structural Elements That Correlate With More Citations on Any Content Type
TL;DR — Which combination to use, by buyer intent
Why the Best On-Page Content Formats for AI Work for LLMs
Predictable Extraction
Citation Signals
How to Structure Pages Using the Best On-Page Content Formats for AI
Structured Data for AI
Internal Links and Topic Clusters
Templates for the Best On-Page Content Formats for AI

Long-Form Articles and Explainer Blog Posts
Listicles and Best-of Posts
Comparison Posts (X vs. Y)
Product and Landing Pages
Category Pages
How to Optimize Existing Pages with the Best On-Page Content Formats for AI
The 5-Step Quick Audit
Pick candidate pages. Pull your top 25-50 organic pages by impressions, then prioritize the ones whose target queries you’d want to win in ChatGPT, Gemini, or Perplexity. Re-run those queries through the engines and note which pages get cited and which don’t.
Standardize the heading hierarchy. Add an H2 roughly every 150-200 words and rewrite vague headings into descriptive, entity-anchored ones. For example, “Frequently Asked Questions About [Topic]” instead of “FAQ,” “Step 3: Add JSON-LD markup” instead of “Markup setup.”
Insert a TL;DR. Put the direct answer to the page’s primary question in the opening sentences or a dedicated summary box, before any history or framing.
Convert dense facts into tables and FAQs. Specs, pricing, study results, and side-by-side comparisons in tables are easier for AI to extract than if they’re buried in paragraphs. Move recurring reader questions into a descriptive FAQ section near the bottom of the page.
Apply the schema that matches the format. If applicable to your content, apply Article, HowTo, FAQPage, or ItemList, plus Author and Organization.
Making Content More “Chunkable”
Bulk Updates and Governance

How to Measure Results from the Best On-Page Content Formats for AI
AI Visibility Tracking
Page-Level Performance Mapping
Reporting Cadence
How to Govern and Refresh Pages Built with the Best On-Page Content Formats for AI
Governance Model
Refresh Tactics
Audience Alignment and Tooling
Frequently Asked Questions About On-Page Formats for AI
Do I need schema to rank in AI results?
How often should I refresh AI-optimized content?
Can I block AI crawlers while keeping search visibility?
Which format should I start with first?
AbJimroe 