Your buyers are asking questions inside ChatGPT, Gemini, and Perplexity that never surface in a keyword report. HubSpot AEO captures those questions as tracked prompts, then shows you how your brand appears in the answers, which competitors get named when you don't, and which pages the answer engines cite as evidence.
That last layer is where content strategy begins. A relevant prompt with no strong page behind it is a content gap. A prompt where a competitor is recommended, and your brand never comes up, is a coverage problem you can diagnose. A prompt that pulls citations from a review site or an industry publication tells you something about the format buyers trust for that question.
This guide walks through the full sequence: reading prompts as buyer research, auditing your library against them, using competitor and citation data to explain what's missing, deciding which gaps to work on first, and turning each decision into content an answer engine can actually use.
HubSpot AEO prompts show you the questions, problems, comparisons, and buying considerations your audience brings to AI search. They function as a research feed about buyer thinking, not only as a visibility metric.
HubSpot suggests prompts using your business details, products and services, tracked competitors, and ideal customer profiles, and you review and refine that list before tracking begins. The suggestions draw on real signals in your CRM, including deal stages, buyer personas, and sales conversations, which is what separates them from a manual brainstorm.
A practical starting point is 20 to 30 prompts spread across two or three focus areas, tight enough to read carefully and broad enough to expose patterns.
You can filter prompts by buyer journey phase, product and service relevance, answer engine, date, group, and ideal customer profile. This helps multi-product companies isolate patterns within specific segments.
One scope note before you read the data: HubSpot AEO tracks ChatGPT, Gemini, and Perplexity. As of mid-2026, its core tool does not monitor other assistants such as Claude. Your visibility covers three engines, which is enough to identify useful patterns as long as you understand the boundary.
With these segments in place, it starts to show how buyers research, compare, and evaluate your business. This gives you a clearer basis for deciding what content needs attention.
Take each relevant prompt and ask one question: does a page on your site give a direct, complete, current answer? Where the answer is no, you have a gap worth documenting.
Running prompts through the same sequence keeps the audit consistent and makes the output sortable later.
Say HubSpot AEO surfaces the prompt "What is the best CRM for a growing B2B company?"
You may already publish a general CRM guide, so the prompt looks covered. It isn't. The buyer is asking a sizing and fit question, and your page likely skips the specifics that decide it: headcount thresholds, implementation effort, integration requirements, pricing at scale, and the operational load on a small team. The page answers a category question while the prompt asks a selection question.
That distinction changes the action. The fix here could be a dedicated selection resource, a sharper comparison, or a substantial expansion of the existing guide. Which one you choose depends on what the competitor and citation data show next.
Competitors appear where AI answers mention them, cite their content, or give them stronger visibility across the same buyer questions your brand is trying to answer.
Three measurements do different jobs, and mixing them up leads to bad decisions.
HubSpot also scores sentiment from -100 to +100, showing if answers describe your brand positively, negatively, or neutrally when it does appear. A negative or flat description on a decision-stage prompt is its own kind of gap.
Strong Google rankings do not guarantee strong visibility in AI answers. Your content can rank well in traditional search and still fail to become the source an answer engine uses when buyers compare options. Competitor data shows which questions you are losing. Citation data shows what sources and content types are helping competitors win those questions.
Learn how to Find Which Content AI Is Citing with HubSpot AI Visibility in this guide.
Citation analysis breaks down which domains, pages, and content types show up in AI answers for your brand and for your competitors. Read it as evidence about what answer engines find usable for a given question.
Separate the results into owned pages, competitor domains, third-party publications, review and community platforms, and social sources. Perplexity is especially informative here because of how heavily it relies on web retrieval, and HubSpot analyzes the specific URLs and content types it references, including blogs, news, and Reddit threads. Each source type points somewhere different:
For any prompt you're losing, compare the cited page against yours and name the difference:
Copying the cited page is the wrong move. Naming the specific deficit is the right one, because a deficit converts cleanly into a task.
Prioritize gaps that combine buyer relevance, high purchase intent, a competitive opening, and a clear content action. A prompt can score well on AI visibility potential and still carry no commercial value, so relevance leads.
The Recommendations tab converts citation-gap data into a prioritized list with a content type, a suggested channel, a priority ranking, and a content brief for each item. Recommended actions range from creating a new blog post to updating an existing page, publishing a social post, or reaching out to a third-party source.
Treat that list as input and not as a work order. AEO metrics help you prioritize, though they aren't a direct measure of pipeline, so pair them with Search Console data, conversion data, sales feedback, and content QA before committing budget.
A ranked shortlist of five or six gaps beats a backlog of forty. Once it's ranked, the work shifts to building answers strong enough to get pulled into the response.
Match the action to the gap type you diagnosed, then write for retrieval as deliberately as you write for the reader.
|
What the data showed |
What to do |
|
No page exists for a relevant prompt |
Create a focused resource on that single question |
|
A page covers the topic partially |
Expand it with the subtopics cited competitors cover |
|
Information is dated |
Update the facts, examples, and figures, and show the revision date |
|
Several pages fragment one intent |
Consolidate into one authoritative page and redirect the rest |
|
Competitors win on evidence |
Add original data, benchmarks, screenshots, or named client outcomes |
|
Third parties own the citations |
Pursue reviews, guest contributions, analyst mentions, and directory listings |
Content that answers a question directly, uses clear structure, and demonstrates real expertise stands a better chance of earning AI citations, and consistent publishing around one subject strengthens topical authority across related prompts.
In practice, that means leading each section with a direct answer before the supporting detail, keeping passages self-contained enough to quote without surrounding context, using descriptive subheads phrased the way buyers ask, adding tables and steps where the question implies a comparison or a process, and stating specifics such as numbers, timelines, and named tools that a generic page never commits to.
Portals with Content Hub Pro or Enterprise can create a blog post directly from an AEO content recommendation and have the tool draft the targeted post. Use that as a first draft and not a finished asset. The differentiator on a cited page is the expertise and evidence your team adds, which is exactly the part a draft can't supply.
Run it on a cycle, because a single check won't hold. AI-generated answers vary across prompts and across runs, which makes one-time visibility snapshots unreliable and recurring optimization cycles far more useful than isolated audits.
A workable cadence looks like this:
One caution as you report on progress: a visibility score alone shouldn't stand in for success, since mentions shift as engines, sources, prompts, and product information change. Pair visibility movement with organic traffic, conversions, and pipeline on the pages you touched, and you'll know which content decisions were worth repeating.
If you want a structured process to help you run your AEO and AI search visibility analysis, identify content gaps, and prioritize what to improve next, download The Modern Guide to AEO & AI Search Visibility.
HubSpot AEO helps you uncover the buyer questions your keyword research may miss, see where competitors are appearing, and identify the sources answer engines rely on. These insights show you what content is missing, what to prioritize, and why it matters.
Campaign Creators can turn these insights into a clear content plan and create content that answers real buyer questions and strengthens your visibility across search and AI platforms.
Don’t have AEO data yet? We can help you identify the questions, content gaps, and opportunities you need to build your AEO strategy from the ground up.