Where Does Your Brand Rank in AI Search? That's the Question Every Marketer Should Be Asking in 2026

A while back, a friend of mine who runs B2B software invited me out for a drink.

He had this worried look on his face. Last month, his marketing team had churned out dozens of blog posts, and their SEO rankings had actually gone up. But the sales team was telling him the leads coming in were getting worse, not better.

Why?

He pulled out his phone and showed me. A potential customer had asked ChatGPT, "What are the best CRMs for a small-to-mid team?" — and the AI handed back a list. His product wasn't on it.

I said, "That's exactly what everyone's talking about right now. AEO."

AEO — Answer Engine Optimization.

It used to be that you optimized for Google's search results page. Now, you optimize for the answer that ChatGPT, Gemini, and Perplexity hand back to the user.

He immediately asked: "So what tool should I use to track this?"

Now that's an interesting question.

Because the two tools most often compared on the market happen to represent two completely different philosophies. One is HubSpot's AEO tool. The other is Otterly. Today, let's break them down and talk about where they really differ.

One is a "Security Camera," the Other a "Factory Assembly Line"

Let me ask you something first: when you buy an AEO tool, what are you actually buying it for?

Most people blurt out: "To know whether my brand shows up in AI answers, obviously."

Right. That's the most basic need. Both tools can do that.

HubSpot AEO watches ChatGPT, Gemini, and Perplexity for you — how often your brand shows up in their answers, which pages get cited, how your competitors are doing. Otterly does the same job, and it actually watches even more engines. ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, Microsoft Copilot — five right out of the gate. Gemini and Claude are supported too, but those cost extra.

But the real split happens after the data comes in.

HubSpot AEO lives inside the HubSpot stack.

What does "lives inside" mean?

It means when it catches your AI visibility dropping on some key question, you can write a blog post to plug that gap in the very same place, line up a LinkedIn post, even go engage on Reddit. No switching windows, no exporting data, no opening another browser tab.

And Otterly?

Otterly is a pure monitoring layer. It measures your AI visibility data clearly and precisely, then hands you three paths: export it into Looker Studio for reports, pipe it into your BI system through the API, or use the MCP server so tools like Claude and Cursor can query it directly. The reports are genuinely professional.

But it doesn't do the hands-on work for you.

Spotted a problem? Great — take the insight, switch to your content tool, write, publish. Then come back to Otterly to see whether it moved the needle.

Man, that's a hassle.

But hold off on a verdict. For some teams, that crisp boundary of "I only measure; how you act is your business" is exactly the virtue. If your company already has a content production workflow humming along nicely, Otterly just sits quietly on top of your existing tool stack and doesn't change a single working habit.

So really, the whole thing boils down to one question:

Do you want a platform that works alongside you, or a monitor that only sounds the alarm?

CRM Data — The Thing Everyone Underestimates

Let me make another point that's easy to miss.

When you do prompt tracking with Otterly, you're starting from zero. It has a tool called Query Fan Out that's actually pretty interesting: you give it one starting question, and it spreads out all the related queries an AI engine might spin off into, laid out for you to see. Great for prompt discovery and gap analysis, especially if you're building a prompt library from scratch.

But HubSpot AEO isn't like that.

Because behind it sits your CRM. It knows what industry you're in, who your competitors are, what your customer personas look like. So the prompts it recommends can dodge the generic "what's the best CRM" kind of question and land right on the things your actual buyers ask.

That gap is actually pretty big.

Think about it. A marketing manager sits down at their desk at 9 a.m., opens the tool, and stares at a blank page trying to come up with 15 prompts from scratch — that's exhausting. But if the tool just tells you, "Based on your customer data, these 15 questions are the most worth tracking," haven't you just cut your ramp-up time in half?

That's the value of the CRM connection. It means your AI visibility comes with your business context baked in from the very start.

HubSpot's own data even shows that leads from AI search convert at three times the rate of leads from traditional search.

Three times.

If you're a sales leader, you care about that number a lot. The question is, can you see that in the same system — both how often your competitors show up in AI answers and how much your own sales pipeline is getting hit?

If your AEO tool and your CRM are two separate systems, that closed loop is hard to close. You have to drag Otterly's data out over the API and join it against the sales data sitting in another system. Doable, but a slog.

Let's Do the Math on Price

Let's talk money.

HubSpot AEO standalone is $50 a month, or $45 a month if you pay annually. Free trial is 28 days, gives you 25 prompts across ChatGPT, Gemini, and Perplexity, no card required.

Otterly's free trial is 7 days. Paid plans come in four tiers: Lite is $29 a month, with 15 prompts, 4 engines, daily tracking, and 1,000 GEO URL audits. Standard is $189, with 100 prompts and 5,000 URL audits, and it unlocks the Looker Studio connector, the API, and MCP. Premium is $489, with 400 prompts, 10,000 URL audits, and 5,000 API calls. Enterprise is custom-priced.

Sounds like Otterly Lite is cheaper?

But notice one thing: Otterly's base tiers don't include Gemini or Claude tracking. Those two are paid add-ons. If you want full coverage of every major engine, that add-on fee has to get folded into the grand total.

So how do you choose?

Here's what I told my friend:

If your team is small and you just want to keep an eye on 15 prompts or fewer to get a read on the lay of the land, Otterly Lite at $29 covers a wide range of engines and is genuinely good value.

If you're already using HubSpot for content and marketing, the $50 HubSpot AEO is the better deal. Because it comes with that closed workflow loop built in — and that's something none of Otterly's tiers can give you.

If you need 100+ prompts, want URL audits, and want API calls, then Otterly Standard at $189 has a depth the standalone HubSpot version can't match. You just have to accept managing those insights in another tool.

AEO and SEO — Do You Really Have to Pick One?

A lot of people ask: "My SEO is doing fine. Should I throw all my energy into AEO instead?"

Short answer: no. The two aren't substitutes; they're partners.

SEO optimizes for traditional search engine rankings — can the crawler reach your page, where does your keyword rank, do you have high-quality backlinks, is your structured data in good shape. AEO optimizes for how your brand shows up inside the answer an AI generates.

Here's the interesting part: the exact same article might rank beautifully on Google and get cited all the time by ChatGPT. Or it might only win on one side.

Why? Because the underlying logic overlaps.

A piece of content that's clearly structured and carries real authority is more likely to be cited by AI and more likely to climb the traditional rankings. Content written for AI search emphasizes clear answers, authoritative first-person sources, and structured data — which, conveniently, are also the fundamentals of SEO.

So the smart move is: use your AEO prompt data to find out what buyers are asking AI, then check whether you actually have content that answers those questions clearly and in a format that's easy for AI to cite. Your AEO gaps are very often your content-strategy gaps.

So What's the First Move for a Beginner?

Don't try to monitor everything on day one. That's where most people stumble.

Pick 10 to 15 prompts. That's enough. These prompts should map to the questions your buyers actually ask — things like "for this type of tool, which is the best fit for this scenario," or "how do I actually choose this product" — the evaluation-stage questions. How do you find them? Dig through sales calls, dig through support tickets, dig through customer interviews.

Once your prompts are picked, review them every 30 to 60 days. Buyers' questions shift, and so do the answers AI gives.

When should you graduate from a pure monitoring tool to a full platform?

When you realize you can see the visibility gap, but you're always half a step slow because you're constantly switching between your monitoring tool, your content tool, and your CRM. The hidden cost of that context switching is a lot higher than you think.

I told my friend: go run HubSpot's 28-day free trial first. It's enough to build a real visibility baseline and get your first round of optimization suggestions. Costs you nothing.

Then decide.

Back to That Night Over Drinks

As the evening was wrapping up, my friend asked me: "So you're saying Otterly is bad?"

No.

Otterly is genuinely solid at the monitoring part. Wide engine coverage, professional reports, flexible integration — and that Query Fan Out tool, I honestly think it's got something to it. If your company already has strong data infrastructure, likes building its own dashboards and piping its own pipelines, Otterly gives you more freedom.

But if what you want is to see the problem and immediately be able to act on it — and then see the results in the same place — that's HubSpot AEO's home turf.

The tool is the tool. The decision is the decision.

Figure out first whether what you're missing is "able to see" or "able to act," then come back and pick the tool. Don't get the order backwards.

As for my friend — he went with HubSpot in the end. Not because HubSpot is necessarily better, but because his company was already using HubSpot for content.

See, a lot of tech-selection questions, in the end, aren't really technical questions at all.