AEO benchmarking measures your brand’s AI search visibility against competitors and market trends. It tells you whether a change in your visibility comes from the market or from your own brand, so you can prove performance to leadership before you change tactics.

Like a hammer or even a hair dryer, AI is just a tool. It needs to be wielded skillfully by an expert to achieve greatness. And in a world increasingly full of “AI slop,” this is especially true when exploring how to use AI to write a blog post.

Picture two shoppers. One asks ChatGPT, “Are Nikes good shoes for marathon runners?” The other asks, “What’s the best running shoe?” Both want top-notch athletic shoes. Only one specifically wants to know about Nikes. That’s the idea behind branded vs. unbranded queries in AI search.

Most obstacles in marketing automation aren’t actually automation problems. 86.4% of marketing teams now use AI somewhere in their workflows. Yet, measuring ROI still tops the challenge list at 33%, according to HubSpot’s 2026 State of Marketing Report.

More of your audience now gets answers from AI instead of a list of links. So when someone asks an assistant about your category, the response draws on sources you may never even see, and your brand either shows up in it — or doesn’t.

To improve visibility in AI answer engines, content and SEO marketers need to add AEO keywords gap analysis to their strategies. Traditional SEO keyword gaps show which terms a company isn’t ranking for versus the competition. An AEO keywords gap uses the same principle but with broader criteria, identifying the prompts and questions where a given brand is cited in AI search, but another isn’t.

Measuring success is a leading challenge for answer engine optimization (AEO) that marketers report today. In HubSpot’s State of AEO 2026 report, it was the top challenge among B2B marketers at 23%; among B2C marketers, 26% cited it, behind only understanding how AEO works at 29%.

Struggling to track SEO results through privacy and consent blind spots? Learn how to use GSC, GA4, and CRM data to explain SEO impact when the full customer journey isn’t visible.

Most marketers use an AI assistant at work, but constantly switching between Claude, a CRM, and other apps breaks focus. That is where Claude integrations come in.

AI maturity explains why 98% of marketing teams now use AI in some way, yet only 10% report transformational results, according to our 2026 State of AI in Marketing research. AI maturity measures how consistently a customer-facing team turns AI into measurable business outcomes, and it matters more than the number of tools or pilots you’ve launched.