How to Optimize Your Content for Gemini & ChatGPT Recommendations
Content gets quoted by AI engines when a single section of it can be lifted out, understood without context, and restated accurately. That is the whole optimisation target, and it explains almost every specific tactic below.
Retrieval systems do not read your article. They read a chunk of it — a few hundred words pulled out and dropped into a model's context window alongside chunks from four other sites. Your paragraph is competing with those, stripped of your navigation, your brand, your surrounding argument and your carefully built narrative arc.
This guide covers the on-page changes that improve your odds: how to structure sections, what makes a claim quotable, the formatting engines parse most reliably, and where Gemini and ChatGPT differ enough to matter.
Key takeaways
- Optimise the section, not the page. If a section needs the rest of the article to make sense, it will not be quoted.
- Answer first. The first two or three sentences under a heading must fully answer it.
- Engines quote specifics — numbers, definitions, named mechanisms. Adjectives are unquotable.
- Tables and clear headings are parsed far more reliably than the equivalent prose.
- Gemini rewards classic SEO strength and entity signals; ChatGPT rewards consistent presence plus current, specific pages.
The core principle: write for extraction
Here is the same information written two ways.
Before:
When it comes to measuring your visibility in AI search, there are a number of approaches that teams can take, and choosing the right one depends on a variety of factors that we'll explore in the sections below. Many marketers find this challenging at first.
After:
Share of Model is the percentage of tracked prompts in which an AI engine names your brand, measured against the competitors named instead. If you appear in 12 of 50 prompts and three competitors appear in 38, 31 and 27, your Share of Model is roughly 11%.
The first version defers. It promises value later in the page, contains no extractable claim, and depends entirely on sections that follow. The second answers immediately, defines a term, and includes a worked number.
A retrieval system extracting the first passage has nothing to work with. Extracting the second, it has a definition and an example. Everything below is a variation on this principle.
Structure: how to build a section
Answer first, then explain
Every heading is a question, even when it is not phrased as one. The first two or three sentences under it must fully answer that question. Then explain, qualify and expand.
This inverts how most people write. It also improves the article for human readers, who are scanning.
Make every section self-contained
Remove these phrases from your drafts:
- "As we mentioned above…"
- "In the previous section…"
- "This is why…" (referring to something in a prior section)
- "Building on the framework introduced earlier…"
Each one breaks the moment a chunk is extracted. Repeat the noun instead of using a pronoun that points outside the section: not "this metric", but "Share of Model".
Write headings that work alone
A heading is often the only context an extracted chunk carries.
| Weak | Strong |
|---|---|
| "The formula" | "How Share of Model is calculated" |
| "Getting started" | "How to build a prompt set in five steps" |
| "Why it matters" | "Why sentiment affects whether you get mentioned at all" |
| "Best practices" | "Six formatting rules that improve AI citation rates" |
Size sections deliberately
Aim for roughly 150–400 words between headings. Shorter sections fragment the idea; much longer ones risk being truncated mid-argument. If a section runs past 500 words, it usually contains two ideas that deserve their own headings.
Substance: what makes a claim quotable
Be specific enough to be repeated
Engines quote things that can be restated without loss. Compare:
| Unquotable | Quotable |
|---|---|
| "Most brands aren't visible in AI search" | "In our testing, brands appeared in fewer than a quarter of purchase-intent prompts in their own category" |
| "AI answers change frequently" | "Ask the same prompt three times and you may get three different brand sets, which is why single-run measurement is unreliable" |
| "Schema markup is important" | "Organization schema with a complete sameAs array connects your site to the knowledge graph entry engines rely on" |
The pattern: replace the adjective with the mechanism or the number.
Own at least one claim per article
If everything in your article is available in five other places, a model has no reason to cite you specifically — it will cite the more established source saying the same thing.
Cheap ways to own a claim:
- Run a small test and report it. Ten prompts across three engines is a dataset nobody else has.
- Publish a procedure with your specifics — actual steps, actual thresholds, actual failure modes.
- Report what did not work. Negative results are rare, credible and cited.
- Define something precisely. A clean definition, consistently used, becomes the version that circulates.
Do not fabricate specifics
The temptation to invent a statistic because "engines quote numbers" is real and it is a trap. Fabricated data gets contradicted by other sources, which damages the consistency signal engines use to decide whether to trust you. If you do not have a number, describe the mechanism instead — mechanisms are quotable too.
Formatting: what engines parse reliably
Tables. Any comparison, any set of options with attributes, any before/after. Tables survive extraction better than prose comparisons because the relationships are explicit.
Ordered lists for procedures, unordered for sets. Do not use a numbered list for things that have no order — it implies a sequence that does not exist and gets restated incorrectly.
Bold for the claim, not for emphasis. Bolding the sentence that carries the key assertion helps both scanning readers and extraction. Bolding random phrases for energy helps neither.
Real HTML semantics. Headings must be actual h2/h3 elements, not styled divs. Tables must be table elements, not CSS grids. Lists must be ul/ol.
Front-load the article. Put a short summary or key-takeaways block near the top. It is frequently the chunk that gets retrieved for broad questions.
Q&A sections. A FAQ block with question-shaped h3 headings maps almost perfectly onto how people prompt assistants. This is the highest-yield formatting change most articles can make.
The technical prerequisite
None of the above matters if the crawler receives an empty page.
Most AI crawlers execute JavaScript far less reliably than Googlebot. A site that renders perfectly in Search Console can return a shell to GPTBot or PerplexityBot.
Check it in one command:
curl -s https://yoursite.com/your-article | grep "a sentence from the middle of your article"
No match means no visibility, regardless of content quality. Also confirm your robots.txt allows the agents you want to be visible to — GPTBot, ClaudeBot, PerplexityBot, Google-Extended, CCBot — and add Article schema with datePublished and dateModified.
Where Gemini and ChatGPT differ
The fundamentals above serve both. The differences are real but narrower than most commentary suggests.
| Gemini / AI Overviews | ChatGPT | |
|---|---|---|
| Grounding | Google's index and Knowledge Graph | Own index, live search, plus stored knowledge |
| Search behaviour | Search-first for most queries | Mixed — answers from memory unless the question implies recency or specifics |
| What moves it | Classic SEO strength, structured data, entity signals | Consistent long-term presence plus current, specific pages |
| Fastest lever | Rank for the underlying query; strengthen schema and entity data | Publish specific, current, well-structured pages; earn third-party mentions |
| Freshness sensitivity | High | Moderate — depends on whether it searches |
| How to test | Check whether you rank for the query behind the prompt | Compare answers with browsing on and off |
The practical reading: if you are strong in Google and weak in ChatGPT, your problem is not on-page — it is that the open web does not describe you consistently. If you are weak in both, start with retrievability and structure, because those gate everything.
Use Perplexity as your diagnostic tool for both. It shows its sources, so it tells you which pages are winning the retrieval competition in your category — information neither Gemini nor ChatGPT will give you directly.
Which content formats get cited most
Not all formats compete equally for retrieval. Some are structurally advantaged because they match the shape of what buyers ask.
| Format | Why engines favour it | Priority |
|---|---|---|
| Comparison pages ("X vs Y", "alternatives to Z") | Explicitly evaluative and structured — directly answers a very common prompt shape | Highest |
| Definitions and explainers | Self-contained, quotable, unambiguous | High |
| Original data and small studies | Nobody else has the number, so you become the source | High |
| Procedures with specifics | Steps, thresholds and failure modes are hard to synthesise from elsewhere | High |
| Buying guides | Serves the question that precedes product selection | Medium–high |
| FAQ blocks | Question-shaped headings map onto prompts almost exactly | Medium–high |
| Opinion and commentary | Rarely cited unless the author is an established authority | Low |
| Company news | Almost never retrieved for category questions | Low |
The pattern is that evaluative and definitional content outperforms narrative content. An article that decides something — this versus that, when to use which, what a term means precisely — gives a model something to repeat. An article that muses does not.
What to stop doing
Stop writing introductions. The 150 words of throat-clearing before the actual content is a pure loss: it wastes the most valuable position on the page and it is what gets extracted for broad queries.
Stop burying the definition. If your article explains a concept, define it in the first two sentences, not in section three after the history.
Stop using pronouns across sections. "This approach", "that metric", "it" — each one breaks when the chunk is lifted. Repeat the noun.
Stop hiding comparisons in prose. Three paragraphs comparing two options is a table that has not been built yet.
Stop publishing without a claim. If you cannot name one thing in the article that no other page in your category says, the article has no reason to be cited over its established competitors.
Stop treating updates as optional. A page with a stale dateModified and a two-year-old price is worse than no page, because the wrong facts get repeated to prospects.
A practical rewrite checklist
Apply to your top ten pages before writing anything new. Most teams get more from rewriting twenty existing pages than from publishing twenty new ones.
- Does the first paragraph answer the title's question outright?
- Is there a key-takeaways block near the top?
- Does every section answer its heading in the first two or three sentences?
- Can each section be understood if you delete everything around it?
- Are the headings descriptive enough to stand alone?
- Is there at least one claim only you can make?
- Are comparisons in tables rather than paragraphs?
- Are there any unsupported adjectives standing in for specifics?
- Is there a FAQ block with question-shaped headings?
- Does
curlreturn the article text? - Is
dateModifiedaccurate? - Are the facts — pricing, features, integrations — current?
Item 12 is not cosmetic. Stale facts do not merely fail to help; they get repeated to your prospects.
Frequently asked questions
Does content length affect AI citation?
Not directly. What matters is whether a section fully answers a question. Long articles get cited when they contain well-structured, self-contained sections; they get ignored when length comes from padding. Depth helps because it produces more extractable sections, not because word count is a signal.
Should I use FAQ schema?
The rich results are largely gone, but the format still helps: question-shaped headings map onto how people prompt assistants, and Q&A blocks are clean, self-contained chunks. Keep the format for the structure; treat the schema as optional.
Can I just publish AI-generated content?
It reproduces the consensus models already hold, which makes it close to the least differentiated content you could publish — and gives an engine no reason to cite you over an established source. Use it for drafting and structure, then add the testing, data and specifics that make a page worth quoting.
How long until a rewritten page gets cited?
On the retrieval layer, days to a few weeks once recrawled. Changing what an engine says without searching depends on accumulated coverage and takes considerably longer. See how AI search engines decide which brands to recommend for why the two timelines differ.
Is on-page enough?
No. On-page work makes you quotable; it does not make you recommended. Most of what a model says about your brand was written by someone else — see 7 key factors that influence your brand's visibility in LLMs and the role of sentiment and credibility. The broader discipline is covered in our complete guide to Generative Engine Optimization.
Find out which of your pages engines actually cite — free
You can apply every rule above and still not know whether it worked, because the feedback loop is invisible: nothing in your analytics tells you that Gemini quoted your comparison page last Tuesday.
Geomyze closes that loop. It runs intent-based prompts for your brand across the major AI engines and reports which of your URLs are used as sources, where you appear, and which competitors are named in the answers where you are not.
Run your first AI visibility report free → — one full report, no card required. You will get your Share of Model, citation-level data on your own pages, and a prioritised list of what to fix first.
