The B2B marketing playbook has a new top metric: whether a product is cited when a consumer asks an AI assistant a question. Brands from within ChatGPT, Claude, and Google’s AI Overviews, with very few exceptions, are also well-placed brands from Google itself. AI visibility is tied to search rank, not down to it.
That relationship is more complicated than it first appears. SEO growth consultant Kevin Indig published a correlation analysis earlier this year, drawing on 30,000 AI citations across 500 software categories, and found that none of the classic SEO metrics he examined had a strong relationship with citation frequency. “LLMs have light preferences: Perplexity and AI Overviews have word weight and sentence count higher,” Indig wrote.” In a separate survey of 313 physicians, he found that 78 percent said their current method of measuring LLM visibility is inaccurate.
SEO growth consultant Kevin Indig
Some information suggests that AI response engines reward almost the same content qualities that Google does, even if the top-level metrics differ. Relevant content, primary source data, expert ownership, and structured EEAT signals are important in both areas. A growing consensus within the SEO community holds that the playbook teams should run for AI visibility is the one they should already be running for Google, which is used in a wide range of sources.
“In AI search, visibility depends on 3 factors,” SEO consultant Ben Goodey wrote in a recent review: “that AI can find you, or trust you, and that it can understand and interpret your content.“The result of a brand’s presence, with content published on YouTube, Reddit, TikTok, and industry forums where consumers really gather, is the first effective response of those three. AI engines extract quotes from those places, not just on the brand’s site.
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Hassan Rashid manages this playbook for B2B clients as managing editor at GrowthX AI, a pioneering content startup “software-as-a-service“A platform at the intersection of AI-augmented production and planning discipline. GrowthX AI received $12 million in Series A capital last year. Prior to Content, Rashid spent two years as associate product manager at Addepar, a wealth technology platform founded by Joe Lonsdale in 2009 with over $9T in AUM. His work includes the launch of B2pas Healthcare-Backup, HealthcareBack and Aldepar.
For the B2B SaaS business customer, some of the strongest evidence resides within the AI response engines themselves. AI Assistants is now posting about 174 referrals per month across its 26 articles, up from 23 last month, and its content has earned 794 LLM citations tracked across the site, more than a third of the total. Google’s side went the same way: for all 44 articles, the content now attracts about 1,731 live clicks, more than 660,000 impressions, and 5,751 live sessions per month, with one monthly click and impressions increased by 174 percent last month. In the same window, that activity drove 29 commercial conversion events, from free trial requests and demo completions to price inquiries and lead generation form submissions.
Capital firm Rashid has produced content that has shown a comparable trend. In the same 90 days, 27 articles on the company’s site took their content from poorly calculated to aggregate traffic: monthly organic clicks grew by 33x, from 34 to 1,108, and monthly impressions grew by 14x, from 57,000 to 820,000, while sessions reached 7 months, 72, 7 times, 72 and 7 times is a good forecast for the program. The work done on AI search very quickly, moving the company from a small share to the second-highest AI assistant visibility in its competitive set, with LLM referral traffic up 183 percent month-on-month and its page on the query “AI wrapper” now directly cited by ChatGPT.
At Alpaca Health, a chain of healthcare startups, Rashid led the redesign of the company’s planned content, replacing the 238 pages of a standard template with local pages built from primary source data in each city. The redesigned Texas pages alone drove 109 clicks on the company family’s intake form, 89 of which were through the Texas state center, which is now the highest converting site for the redesigned site pages and the second highest converting page on the site as a whole. Across the site, the family CTA taker recently reached 66 events in one week. And pages are starting to do what this type of content is built for in the AI search era: Alpaca is now cited within Google’s AI Overview answers to more than fifteen discussion questions, such as “which ABA therapy providers in San Antonio are in network,” each from 50 to 110 views.
The pattern shared by all three interactions is not a unique AEO discipline. Content flows through an editorial infrastructure using a master data object, personal review, and author authority specified in a structured schema. Those characteristics are also what Google’s ranking systems are tuned to reward, which is part of why the same content appears on both.
What seems to be new under the AEO label is mainly the urgency of brand presence that good SEO already requires. AI engines pull quotes from YouTube posts, Reddit threads, TikTok captions, chats on the wider web, and industry forums where domain experts gather. Brands that only publish on their own site, even if that site is well-developed, have no place to retrieve the AI from.
“Every company is now a content company,” Rashid said. “Consumers and decision makers are checking brands through Google, ChatGPT, Claude, and Gemini before they fill out a form. If you’re not showing up with relevant, expert-based content that AI engines trust, you’re losing to no one.”
Finding Indig affinity doesn’t make it difficult to look at the “similar playbook,” explaining the nuances within it. Many SEOs agree that the visibility of AI is strongly related to the Google ranking, even where some standard metrics such as page authority and link count do not predict AI citations cleanly. The number of words, sentence structures, schema specificities, and patterns that AI finders actually draw on may be more important than what conventional sign teams were preparing. AI engines reward most of what SEO rewards, and a few things they don’t, and plant operators now use a playbook while balancing what each site wants from them.
The discipline that comes under the AEO label is often the discipline that most B2B sales teams should have been working on all along, with a new urgency around omnipresence and location-specific measurement. The evidence cited in all of Rashid’s interactions points in the same direction: brands are investing now, in valuable content in areas where AI retrievers are actually pulling, already from all Google and response engines. Brands that wait lose those quotes to whoever moved first.
