We Spent Three Weeks Testing the HubSpot AEO Grader. Here’s Our Honest Take.
AI search is changing how people find information. AI tools like ChatGPT, Perplexity, Google AI, and other AI platforms are increasingly the first stop for questions that used to go straight to Google. For marketing teams, that creates a new challenge: traditional SEO tells you where you rank in search results, but it doesn’t tell you whether your brand is showing up in AI answers at all.
That’s the problem that answer engine optimization (AEO) tries to solve. Where traditional SEO optimizes for search engine rankings, AEO focuses on whether AI engines cite your content when generating responses.
The new HubSpot AEO tool is genuinely useful for understanding where your brand appears in AI answers, but it requires more setup and patience than early reviews suggest.
Here’s what we learned running it across three very different clients: a law school, a medical practice, and ourselves.
What Is HubSpot’s AEO Tool and Why Did We Test It?
When HubSpot launched its AEO tool as a beta feature, early coverage from different marketing companies showed promising results. We wanted to see what the tool looked like for smaller organizations across different industries and competitive landscapes.
The goal wasn’t to prove that HubSpot’s AEO tool works, but to understand what it requires to set up and whether it’s worth building into a content workflow.
How to Set It Up
The HubSpot AEO grader is available in Marketing Hub Pro (25 prompts) and Marketing Hub Enterprise (50 prompts). There’s also a free AEO Grader with no CRM account required that runs a one-time brand visibility snapshot, which is a useful starting point before committing to the paid version.
Pricing aside, setup involves four steps:
- Choosing the AI platforms you want to track
- Identifying your competitors
- Defining your ideal customer profiles (ICPs)
- Adding the prompts you want to monitor. This last piece is the most labor-intensive and the most consequential.
The auto-setup option, which lets HubSpot automatically select your competitors and ICPs, isn’t reliable enough to trust at the moment. For all three clients, we had to configure these manually. The auto-generated competitors were close but not quite right, and the auto-generated ICPs were too broad to produce useful data. Anyone expecting to turn this on and get meaningful results in an afternoon should budget significantly more time.
Prompt selection also matters more than the tool’s setup flow implies. Prompts tied to content you’ve already published, at the specific topic level, produced more useful data than the generic category-level prompts HubSpot starts you with.
Three Clients, Three Very Different Baselines
None of these organizations started from zero. All three had active SEO strategies and published, optimized content before this experiment began. The HubSpot AEO grader adds a measurement layer on top of your existing work. It doesn’t create search visibility where none exists. That distinction matters for interpreting the results.
Stetson University College of Law: 24–34% Visibility Score
Stetson brought the deepest content foundation of the three organizations we tested the tool with. The law school has been publishing SEO-optimized content for years, holds national rankings in trial advocacy and legal writing, and has been working with us at Big Sea on blog refreshes and new content targeting prospective students for several years.
The results reflected that foundation. Stetson’s visibility score ranged from 34% at the start of the measurement period to 24% by June 1, with a 38% share of voice against direct Florida law school competitors. That fluctuation in score doesn’t mean brand visibility dropped. It reflects the tool averaging across more prompt runs over time as the baseline stabilizes.
The strongest individual prompts mapped directly to Stetson’s content strengths. “What are the best law schools for trial advocacy?” came back at 100% brand AI mentions across ChatGPT, Perplexity, and Gemini. “What are the best law schools in the Tampa Bay area?” was also at 100%. “What law schools are best for elder law?” scored 74%. These are areas where Stetson has published content specifically structured to answer those questions, and the AI engines are finding it.
One result was particularly instructive. The prompt “What law schools have part-time JD programs in Florida?” returned solid brand mentions, but the ChatGPT response pulled from ABA Standard 509 reports rather than Stetson’s content. For factual, verifiable claims, AI models default to authoritative data sources. No owned content will out-cite the ABA database on enrollment figures. For qualitative comparisons and reputation-based queries, strong content wins. Understanding which type of query you’re dealing with shapes what kind of content is worth creating.
The Recommendations tab for Stetson also flagged something worth noting: several high-priority suggestions were Reddit posts rather than blog content. AI-powered engines index forums, and prospective law students do significant research in those communities. That’s a separate strategic conversation, but it’s useful data.
Big Sea: 1.56% Visibility, 92% Share of Voice
For our own brand at Big Sea, the tool showed lower overall visibility, but with meaningful concentration in a specific niche. The “best HubSpot agency for nonprofits” prompt showed Big Sea being named specifically in Perplexity and Gemini AI answers, described in language that reflects our actual positioning. Perplexity described Big Sea as emphasizing “nonprofit experience, fundraising-oriented growth, and guidance tailored to mission-driven organizations.”
Gemini included Big Sea in a list of agencies with documented nonprofit HubSpot expertise. Those are real brand mentions in real AI-driven answers, shaped by the content investment we’ve made in this space.
The top-cited pages from our website also tell a consistent story. Our community health marketing post was cited 14 times, our HubSpot for nonprofits post was cited 9 times, HubSpot integrations for nonprofits was cited 8 times, and museum website design was cited 8 times. Each of those pages targets a narrow audience and addresses a specific question directly.
The visibility score dropped from 3.33% to 1.56% over the measurement period, reflecting the same baseline stabilization dynamic as at Stetson.
Whole Health Partners: 0.06% Visibility
Whole Health Partners is a North Carolina-based lifestyle medicine practice with a small but mighty content foundation Big Sea has been building out, and 0.06% brand visibility in AI search.
The top citation domains for health-related prompts were NIH (731 citations), Mayo Clinic (625), YouTube (380), Healthline (366), and Cleveland Clinic (324). Those are the sources AI models default to when answering health questions. The path to AI citation for a small, regional medical practice isn’t to compete with those websites on general topics, but to publish content specific enough that the major websites haven’t addressed it in detail.
One prompt showed movement: “Why is it harder to lose weight after 40” came in at 11% visibility, driven by a blog Big Sea wrote and optimized for WHP. That post is doing the right things.
What Gets Cited and Why
Across all three clients, one pattern held consistently: content cited by AI engines is structured around a single, specific question, with clear headers, FAQ sections, and schema markup. Posts targeting one focused topic outperformed broader overview content in every case.
AI models pull from content formatted to answer a question directly. A post titled “HubSpot Integrations for Nonprofit Fundraising” will generate more citations than a “Complete Guide to Nonprofit Marketing” because the first one signals clearly to the model what question it addresses. The LLM training data that shapes AI answers rewards specificity and structure.
Forums also appear as citation sources more often than most marketing teams expect. The Stetson recommendations explicitly flagged Reddit threads as high-priority targets for improving AI brand mentions. AI engines index public conversations alongside published articles. For some audiences, that community presence matters as much as owned content does.
What the Recommendations Tab Is Telling You
Speaking of those recommendations, there are three types that come from the tool: net new content, outreach, and social amplification.
The content recommendations are the most immediately actionable. They identify gaps between what you’re publishing and the prompts your target audience uses in AI search. For Big Sea, the tool flagged a dedicated HubSpot integrations for nonprofits page as a priority. We already had it published at bigsea.co/articles/hubspot-integrations, so we added it to citation tracking.
*One note: The tool may suggest content that you have already published on your website. We saw this happen across the board.
For Whole Health Partners, three recommendations aligned with content already in development: a perimenopause weight-loss explainer, a menopause stages guide, and a weight-loss after 40 post. All three were added to the tracking workflow.
The outreach recommendations require more than the tool provides. Suggestions like “get Big Sea featured in zeffy.com’s Nonprofit Marketing Agency Guide” point to genuinely useful targets. Acting on them requires relationship-building and editorial outreach rather than pure content production. For smaller organizations without dedicated PR capacity, the execution cost is higher than the recommendation implies.
The social amplification recommendations (which include short-form YouTube explainers and LinkedIn posts) assume production capacity that many teams don’t have. These were worth flagging as strategic directions, but not worth treating as an immediate action plan without evaluating what it would actually take to execute them.
One current limitation is that you can only track URLs that the tool recommends. You can’t add a URL you want to monitor independently. HubSpot has said this functionality is coming, and it will significantly improve the tool’s usefulness for teams with existing content they want to benchmark.
AEO Visibility Is a Long Game
AI engines weigh domain authority in source selection the same way Google does, so you can’t shortcut the underlying SEO work. A newer organization in the competitive health content space will see slow citation growth regardless of how strong individual pieces are because AI models weigh source credibility heavily when generating answers.
For organizations with established content and domain authority, the HubSpot AEO tool is a useful layer for measurement and gap identification. It tells you where you’re showing up, where you’re not, and which content investments might close those gaps. For organizations earlier in their SEO journey, the content recommendations are still worth acting on, but the citation movement will just take longer to materialize.
Is HubSpot’s AEO Tool Worth It for Your Organization?
The honest answer depends on where you are in your marketing strategy.
If you have an established content foundation and want visibility into how your brand appears across AI platforms like ChatGPT, Perplexity, and Google AI, the tool provides it. The visibility score, share of voice data, brand mentions tracking, and prompt-level AEO grader scores give you a benchmark that traditional SEO reporting doesn’t provide. That’s a meaningful addition to how marketing teams measure market position and brand recognition.
If your org is relatively new to content marketing, the free tool (the HubSpot AEO Grader) is the better place to start. Run it, get your baseline, and use it to inform content priorities before you commit to the paid tool.
For our own use, we decided the setup investment exceeded the actionable output at this stage. The tool confirmed that our niche content strategy is working and that our brand perception in AI answers reflects our actual positioning. We’ll revisit the tool when manual URL tracking rolls out and when the recommendation workflows allow more customization.
The most valuable thing the HubSpot AEO grader does is make AI citation visible. For any organization building a content strategy that accounts for AI search, that visibility is worth having, even when the numbers feel humbling.
Want to understand where your organization shows up in AI answers? Reach out to us.
