All Things Growth and Marketing

YouTube is already a major part of how people discover content, learn new skills, and research products. And AI search is creating more ways for video content to surface outside YouTube itself.

But for B2B marketers, the interesting question isn’t whether YouTube is big. It’s whether they understand which videos actually perform, and why.

So why are so many marketing professionals avoiding this opportunity for YouTube growth?

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Search isn’t just about finding the right website anymore.

Google can answer a question directly through AI Overviews. ChatGPT can compare five products without sending someone to a single review page. And buyers can research an entire category, narrow their shortlist, and decide which brands are worth considering before visiting a company’s website.

That’s a fundamental change to how discovery works.

AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) are the names marketers have given to adapting to that shift. There’s still plenty of hype around both. But the changes to rankings, citations, brand visibility, and organic traffic are measurable.

The more useful question isn’t whether AEO/GEO is just SEO with a different name. It’s how AI has changed the search journey, and what marketers need to do differently.

Here’s what the data tells us.

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When it comes to AI, most of us are already using it in one way or another. While marketers may lean on it for data analysis, to clean up some copy, or automate repetitive tasks, most marketers primarily use it as a search engine.

Whether it’s ChatGPT, Claude, or Gemini, chances are you’ve already used one of these tools to research something. But what if, instead of using existing AI to gather insights on your audience, you could build your own AI research tool?

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AI Overviews have changed the relationship between ranking and getting traffic from Google.

In Ahrefs’ analysis of 146 million desktop search results, AI Overviews appeared for roughly 21% of keywords. And the click impact has become harder to ignore. In another 2026 study of 300,000 keywords, Ahrefs estimated that AI Overviews were associated with a 58% lower average click-through rate for the top-ranking organic result, compared with the rate expected without an AI Overview.

That doesn’t mean every AI Overview causes a 58% drop. It’s an observational estimate. But it shows why rankings alone don’t tell you the whole story anymore.

Your content can still rank well while Google answers part of the question directly in search results. The challenge for content teams is understanding what those AI-generated answers cover, which sources appear alongside them, and where their own articles fall short.

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People aren’t just Googling anymore; they’re asking ChatGPT, Claude, and Perplexity to make decisions for them. “What’s the best CRM for startups?” “Which landing page builder should I use?”

The challenge is that you can’t see where ChatGPT looks before it picks a winner: the queries it uses to retrieve information and build AI recommendations are completely invisible.

Until now.

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The problem with B2B AI marketing tactics right now is that everyone’s selling certainty in a system that’s changing weekly.

LinkedIn is drowning in posts about “guaranteed” AI strategies: screenshot after screenshot of viral wins, tools that “definitely” get you ranked, and carousels that “always” perform. 

But when you actually test them, most fall apart. Not because the tactics are completely wrong, but because they’re presented without context, caveats, or an honest assessment of what changed since they stopped working.

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Planning content around search volume data alone while LLMs are running numerous backend queries is the fastest way to miss out on content opportunities.

Seer Interactive found that 95% of the queries that answer engines actually execute have zero tracked search volume. Zero.

So every time you open your keyword tool and filter by volume, you’re systematically ignoring what ChatGPT, Perplexity, and Gemini are searching for.

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You’ve been there. You start building lead scoring in HubSpot or Marketo, and immediately fall into dropdown purgatory: endless clicking through menus, assigning point values to job titles, email opens, and webinar attendance.

Weeks later, you launch it. Before you know it, you’re stuck QAing, checking how your rules affect MQL flow, and realizing you may have over-scored or under-scored in ways that ripple through your ABM funnel. 

The problem isn’t the tool. It’s the approach.

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