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LLM SEO
LLM SEO: get your brand into AI answers
LLM SEO is the work of getting large language models to mention, cite and recommend you. WriteWorks measures how the models answer your buyers' prompts, checks whether their crawlers can read your pages, and turns every gap into content your team ships and measures.
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Measure/AI visibility
Search brands, prompts, competitors…⌘K
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Brand-by-platform performance heatmap. Spot the AI engines where you’re winning vs the ones quietly handing every mention to a competitor.
The challenge
Why LLM SEO needs its own measurement
Search rankings and AI answers are different outcomes. These are the gaps that keep brands out of model answers.
Rankings don't tell you what a model says
A page can sit on page one of Google and never appear in a ChatGPT or Gemini answer. Classic rank tracking can't see the answer, the brands named in it or the sources behind it.
Every model answers differently
The same prompt returns different brands on different models. Optimising for one assistant and assuming the rest follow leaves most of the answer surface unmeasured.
Models can only use what their crawlers can read
Pages rendered by JavaScript, blocked in robots.txt or missing structured data are hard for AI crawlers to use, however good the writing is.
Tactics without a feedback loop
Most LLM SEO advice is a checklist. Without a baseline and a measured re-run, nobody can say whether the change moved the answer.
The solution
How WriteWorks runs LLM SEO
Measure the answer, find the cited sources, fix crawler access, ship the content, then measure again.
Track the prompts your buyers ask and see, for each AI platform, whether you are mentioned, where you sit in the answer and who is named instead. Visibility is the share of answers that mention you.
Captured answers keep the pages each engine cites, so you can see which of your URLs earn citations, which competitor pages win them, and where a third-party source is doing the work.
The AI discoverability crawl checks bot access, raw-HTML content, structured data, answer-first structure, speed and freshness, then scores each page and lists the fixes.
Gaps become briefs and drafts in the editor, reviewed on the Search, Human and Brand tabs before they ship. Re-runs on the same prompts show whether the answer moved.
Success story
What real brands fixed with WriteWorks
What each brand fixed, measured before and after with the same audit, in their own words.
“Turning caching on made our pages 2.5 times faster for crawlers. While we were in there, we fixed the headings too: guides with a clean heading structure went from 32% to 100%.”
S4
Capabilities
LLM SEO capabilities
The measurement, audit and content tools behind an LLM SEO programme.
Multi-model prompt tracking
Prompts captured daily on every engine your plan includes, with mentions, position and sentiment.
Citations and cited sources
Which pages each engine cites, weekly citation history, and the domains models lean on.
Query fan-outs
The sub-queries behind each tracked prompt, so content covers what a model is likely to search for.
AI discoverability score
A 0 to 100 crawl score for how easily AI crawlers can fetch, read and trust your pages.
AI crawler analytics
27 AI crawler signatures, classified as citation, indexing, training and assistant bots (Growth and above).
Editor reviews
Search, Human Signal and Brand reviews on every draft, before it is published.
Time savings
What changes when LLM SEO is measured
The manual checks a tracked programme replaces.
TaskBeforeWith WriteWorksTime saved
Check what models say for a promptTyping prompts into each assistantCaptured daily per engineRepeat checks gone
Find the pages models cite instead of yoursClicking through sources by handCited sources per promptHours per topic
Audit a site for AI crawler accessLog files and spot checksScheduled discoverability crawlDays per audit
Prove an LLM SEO change workedAnecdoteSame prompts, before and afterBuilt-in
Included
What's included
Everything an LLM SEO programme needs, in one platform.
Prompt tracking on 10+ AI platforms (engines vary by plan)
Mentions, position, sentiment and share of voice per prompt
Citations, cited sources and weekly citation history
Answer X-ray: the stored answer behind any chart point
AI discoverability crawl with page-level fixes
Schema markup checker and generator
Query fan-outs for every tracked prompt
Briefs, drafts and Search, Human and Brand reviews in the editor
Built for
Who runs LLM SEO
SEO, content and technical teams working from the same data.
SEO leads
Extend the SEO programme to AI answers with a baseline, a backlog and a measured result.
Content teams
Write for the questions models get asked, with the sources and sub-queries in the brief.
Technical SEOs
Find the rendering, schema and crawler-access issues that keep pages out of AI answers.
Marketing leaders
Report AI visibility and share of voice against competitors, by platform and market.
Featured story
GoTeachingJobs
“Honestly, the jobs board looked fine in a browser, so we never questioned it. The audit showed that only 5% of our job pages gave crawlers real content. We moved the listings into the server HTML, and the re-audit came back at 100%. The typical job page now carries 73% of its content before any JavaScript runs, and we're working through the rest.”
GoTeachingJobs team
Read the full story5% → 100%
Job pages AI crawlers can read
18% → 100%
Median share of page content in the HTML crawlers get
45% → 99%
Pages passing the answer-first check
FAQ
Frequently asked questions
Everything teams typically ask before getting started.
What is LLM SEO?+
LLM SEO is optimising your brand and content so large language models such as ChatGPT, Claude, Gemini and Perplexity mention, cite and recommend you in their answers. It covers what the models say (measured with tracked prompts), what they can read (crawler access, rendering, structured data) and what they find worth citing (clear, specific, answer-first content).
How is LLM SEO different from traditional SEO?+
Traditional SEO measures rankings and clicks on a results page. LLM SEO measures whether a model includes you in a single generated answer, and which sources it uses to build that answer. Much of the groundwork overlaps (crawlable pages, structured data, authority), but the outcome you track is the answer, not the position.
Which AI platforms does WriteWorks track?+
WriteWorks covers 10+ AI platforms. Coverage depends on the plan: Starter tracks ChatGPT; Growth tracks ChatGPT, Google AI Overviews and Google AI Mode; Enterprise and agency plans track every platform, including Claude, Gemini, Perplexity, Microsoft Copilot, Meta AI, Grok and Brave AI.
How often are answers captured?+
Tracked prompts are captured daily. Citation history is shown in weekly buckets, so you can line a content change up against what happened to citations afterwards.
Is there an LLM SEO checklist in the product?+
The AI discoverability crawl acts as the technical checklist: bot access and robots.txt, raw HTML versus rendered content, structured data, answer-first structure, response time and freshness signals, each with the affected pages and a fix.
How is this page different from the ChatGPT SEO page?+
The ChatGPT SEO page covers one assistant. LLM SEO is the cross-model method: the same prompts measured on every engine your plan includes, so you can see where one model cites you and another doesn't.
Explore more
Keep exploring
Related solutions, adjacent use cases, and platform features.
Start measuring your LLM SEO
Track the prompts that matter, see which models mention you and which sources they cite, then ship the fixes and content that change the answer.