{"id":7242,"date":"2026-04-16T12:58:15","date_gmt":"2026-04-16T16:58:15","guid":{"rendered":"https:\/\/beomniscient.com\/?p=7242"},"modified":"2026-04-16T12:58:16","modified_gmt":"2026-04-16T16:58:16","slug":"ai-search-faqs","status":"publish","type":"post","link":"https:\/\/beomniscient.com\/blog\/ai-search-faqs\/","title":{"rendered":"AI Search FAQs"},"content":{"rendered":"\n

I recently did a webinar with Jason Widup<\/a>, Rahul Jain<\/a>, and Josh Budman<\/a> from Noble. <\/p>\n\n\n\n

We covered a lot of ground on AI search, what\u2019s real, what\u2019s hype, what to actually do about it. <\/p>\n\n\n\n

Rather than making you\u00a0watch the full recording<\/a>, here\u2019s the distilled version: the questions we tackled and what I think the honest answers are.<\/p>\n\n\n\n

What\u2019s the biggest misconception about AI search?<\/strong><\/h2>\n\n\n\n

There are many misconceptions, but the two we covered relate to the misunderstanding of what AI search actually is. <\/p>\n\n\n\n

There\u2019s a spectrum of misconceptions. <\/p>\n\n\n\n

One extreme says AI search is a nothing burger: just do the same SEO work (oh and tack on \u201calso do brand marketing\u201d as an hand-wavy afterthought). The other extreme says everything is new: de-invest from SEO entirely, go all-in on AEO, adopt whatever tactic dropped on LinkedIn this week.<\/p>\n\n\n\n

The truth sits in the middle, as it usually does. The ingredients look similar. You\u2019re still publishing and optimizing content. You\u2019re still building off-page trust and verification. But the math is different. <\/p>\n\n\n\n

Off-page signals like brand mentions, third-party citations, earned media have moved from \u201cnice to have\u201d to primary driver, and the mechanisms are different. Backlinks and brand mentions, while cosmetically similar, have different utility functions. Brand mentions, especially co-occurring with categorical phrases (e.g. \u201cNike\u201d next to \u201crunning shoes\u201d) build associations with your brand beyond the value of high DR links. <\/p>\n\n\n\n

That shift matters because it wasn\u2019t traditionally under SEO\u2019s purview. Most SEO teams don\u2019t own brand mentions, public relations, customer marketing (e.g. review sites like G2<\/a>), as these are broader marketing activities. Most marketing orgs haven\u2019t built the muscle for it, at least in an integrated and holistic motion.<\/p>\n\n\n\n

The related misconception: your website is the holy grail. A lot of AI visibility platforms focused on on-site optimization \u2014 restructure your headings, add FAQ schema, format for AI extraction. That created the impression that on-site changes are what move the needle. They\u2019re part of the story. Not the whole story. And probably not even the biggest part for most brands. <\/p>\n\n\n\n

Does \u201conly 2% of traffic comes from LLMs\u201d mean AI search doesn\u2019t matter?<\/strong><\/h2>\n\n\n\n

This is an attribution problem<\/a>, not an importance problem. <\/p>\n\n\n\n

Data is all over the place, but I\u2019ve seen studies showing Google AI Overviews show up<\/a> anywhere between 13% and 60% of the time. Many users who see a brand in an AI overview don\u2019t click through it. They\u2019ll often open up a new tab and search for the brand directly, splintering your channel and source attribution. That shows up as organic or direct traffic, not LLM traffic.<\/p>\n\n\n\n

The delta at our own company is massive. <\/p>\n\n\n\n

Click-based telemetry says 5\u201310% of traffic is LLM-attributed. Self-reported attribution says 50\u201370%. That\u2019s not a rounding error. It\u2019s a measurement failure that\u2019s causing people to deprioritize a channel that\u2019s influencing the majority of their pipeline.<\/p>\n\n\n\n

It\u2019s also a numerator\/denominator trap. <\/p>\n\n\n\n

Fewer people click through from LLM answers, so the conversion rate on those clicks looks inflated. But many more people see your brand than ever click. The exposure is enormous. So the talk of \u201cLLMs converting 10X higher\u201d than other channels is also a measurement mishap, not proof of higher intent per se. <\/p>\n\n\n\n

The attribution just hasn\u2019t caught up to the behavior.<\/p>\n\n\n\n

Related deep dive: <\/em>How Much Traffic Does ChatGPT Send?<\/em><\/a><\/p>\n\n\n\n

Do brands show up at the top of the funnel in AI engines?<\/strong><\/h2>\n\n\n\n

Generally, no. <\/p>\n\n\n\n

When someone asks \u201cWhat is an AI agent?\u201d the LLM answers the question. It doesn\u2019t (usually) recommend vendors. Even before AI search, we deprioritized very high level top-of-funnel content. It was low intent and rarely tied back to meaningful conversions (and usually resulted in brand\u2019s entering what we call the \u201ctraffic trap<\/a>.\u201d)<\/p>\n\n\n\n

It\u2019s not never, though. Our own research found that up to 1\/3 of LLM outputs recommend brands<\/a>, even when users aren\u2019t explicitly asking for products or services.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

But there\u2019s another exception that I think is underexplored related to the top of the funnel, where users are wrapping their heads around a problem.<\/p>\n\n\n\n

If you create original research and distribute it well (get it cited across publishers, get it referenced in industry conversations), you can show up at the top of the funnel as a source rather than a vendor. A CMO searching \u201cWhat are AI overviews doing to traffic?\u201d might encounter your research, creating zero-friction awareness without you ever writing another \u201cultimate guide.\u201d<\/p>\n\n\n\n

My take: original research is in many ways the new<\/a> top of funnel for B2B. You can see this via organic social as well (not just in AI search). The old model was educational blog posts. The new model is being the cited source behind the education.<\/p>\n\n\n\n

What happens at mid-funnel and bottom-funnel?<\/strong><\/h2>\n\n\n\n

Mid-funnel is where things get serious. <\/p>\n\n\n\n

\u201cWhat\u2019s the best project management tool for remote teams?\u201d \u2014 brands show up in the outputs here, giving rise to real brand awareness and customer acquisition potential. Here, 85\u201395% of citations at this stage come from third-party sources (numbers vary, directional point is that much of it comes from off page sources). Review sites, editorial roundups, comparison posts, niche publications. Not just your website.<\/p>\n\n\n\n

Even well-established companies rarely exceed 50% citation share in their category. Off-page dominates at every funnel stage, but mid-funnel is where the gap is widest and the stakes are highest. This is where buyers are building their consideration set.<\/p>\n\n\n\n

Bottom-funnel or product\/brand aware is more specific, e.g. \u201cHow does Attio compare to Day?\u201d \u201cDoes HubSpot integrate with Gong?\u201d <\/p>\n\n\n\n

Our research on branded searches<\/a> found 48% earned media sources, 30% commercial content from other sites, and only 23% from the brand\u2019s own website. Even when people search for you by name, most of what the LLM tells them comes from elsewhere. <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

You don\u2019t fully control your own narrative. What others say about you matters more than what you say about yourself.<\/p>\n\n\n\n

What content types actually get cited in AI engines?<\/strong><\/h2>\n\n\n\n

This varies a ton depending on the prompts you track<\/a>. That\u2019s the big old grain of salt you need to take with any public research on AI search. <\/p>\n\n\n\n

Here, the long tail seems to matter a lot, and it\u2019s also highly context dependent. In aggregate, studies show the prominence of Reddit, Wikipedia, LinkedIn, but on an individual basis (i.e. for your brand), these sources are rarely the top influential surface areas. Rahul from Noble made this point well: there\u2019s a massive tail of third-party sources that don\u2019t fall under the Reddit\/Wikipedia\/Quora banner. Niche publications, industry analysts, vertical-specific review sites, comparison pages from publishers you\u2019ve never heard of.<\/p>\n\n\n\n

That\u2019s where the opportunity lives. Big competitors often have surprising gaps in these long-tail sources. There are more citation opportunities than traditional SERP analysis would ever surface.<\/p>\n\n\n\n

Further deep dive on content types and citation sources: <\/em>What We Know About Optimizing for LLMs<\/em><\/a><\/p>\n\n\n\n

Does personalization in AI engines make visibility data meaningless?<\/strong><\/h2>\n\n\n\n

This was an early objection from the SEO community: everyone gets a different answer, so why bother measuring? Rand Fishkin studied this<\/a>. Some people treated it as a gotcha, proof that AI search visibility doesn\u2019t matter.<\/p>\n\n\n\n

But this stuff works on probability distributions. While individual answers vary, the aggregated distribution shows real patterns. The same brands appear dominant across geographies and contexts despite personalization. The signal is there if you aggregate enough responses, forming a sort of digital mirror of your brand presence against your key competitors. It\u2019s directional, but when tracked well, it\u2019s very useful and actionable. <\/p>\n\n\n\n

Another possible practical approach to personalization: the reintroduction of buyer personas.<\/p>\n\n\n\n

These will vary by brand, but you could imagine a few industries, titles, and product lines (e.g. for Omniscient we could look at SEO, content, and digital PR, selling to tech, financial services, and healthcare, and targeting titles director, VP marketing, and CMO). Build a measurement grid. Personas (director, VP, CMO) crossed with company stage and industry. <\/p>\n\n\n\n

Run prompts across that matrix that best approximate the persona (knowing you\u2019ll never get to the N of 1 personalization or prompt). <\/p>\n\n\n\n

You\u2019ll approximate the real distribution well enough to act on. You won\u2019t get individual-level ChatGPT data, but you don\u2019t need to in order to understand, for example, that you\u2019re relatively weak with startup founders in FinTech compared to enterprise SaaS brands.<\/p>\n\n\n\n

What should a VP of Marketing do first for AEO\/GEO?<\/strong><\/h2>\n\n\n\n

Note: this is obviously one of those \u201cit depends\u201d questions, but we answered with as much practical substance as possible. <\/em><\/p>\n\n\n\n