AI Search Podcast

Boris Robles-SlyusarMarketer and doctoral researcher, Arizona State Universityoptimizehub.net

Who is Boris Robles-Slyusar?

Boris Robles-Slyusar is a marketer and a doctoral student in Information Technology at Arizona State University. His research looks at product rankings and the marketing tactics behind them, which in practice means reverse engineering why one product gets ranked above another. He went back for the doctorate while working as a marketer.

How does AI decide which products to recommend?

AI engines build a shortlist from what the web says about a product, and that list is different from what ranks on Google. An Ahrefs study found that only 12% of URLs cited by ChatGPT, Gemini and Copilot also rank in Google's top 10 for the same prompt, so a strong Google position tells you little about whether AI will name you.

That's why a brand can be cited in Google AI Overviews while missing from page one. The part I keep coming back to is the shortlist: when a buyer asks an AI engine what to buy, the decision is made the moment that list forms. If you're mentioned in the answer but not on the list, you lost the deal before anyone visited your site.

Key takeaways from Boris's episode

• Visible isn't recommended. Showing up in an AI answer and being the product it tells the buyer to pick are different outcomes. Only the second one moves pipeline.
• Google rank and AI citations barely overlap. Only 12% of URLs cited by ChatGPT, Gemini and Copilot rank in Google's top 10 for the same prompt.
• AI search leads convert. We get into why AI search may be the most valuable channel right now, with better CAC and better LTV.
• Entity consistency comes first. Your brand has to be described the same way everywhere AI looks before the rest of the work pays off.
• Build an answers page. Collect 30 to 50 real buyer questions and answer them on one page AI can cite, like our Arobis AI answers page.
• AI agents are starting to buy. A real example of a Claude agent booking a flight, and what it means for how software gets chosen.

Nathan OjaokomoB2B SaaS content writer, G2 Learn Hub contributornathanojaokomo.com LinkedIn

Who is Nathan Ojaokomo?

Nathan Ojaokomo is a freelance B2B SaaS content writer and a contributor to G2's Learn Hub. He started out freelance writing in Nigeria and later niched down into B2B SaaS content. He grew his own site from zero to roughly 5,000 monthly visitors and about 30k in traffic value with no backlink or PR process.

What is search everywhere optimization?

Search everywhere optimization is the idea that SEO is no longer only about ranking in Google. Buyers now search and shortlist across ChatGPT, Claude, Perplexity, Google AI Overviews, review sites and communities, so a brand has to show up consistently in all of those places, well beyond its own website.

That shift changes what you measure. Traffic and keyword rankings stopped being useful KPIs on their own, and the work should start at the bottom of the funnel, closest to the buying decision.

Key takeaways from Nathan's episode

• SEO became search everywhere optimization. Google is one of many places where buyers now form a shortlist.
• Rankings stopped being the KPI. Traffic and keyword positions say less than they used to in AI search.
• Start at the bottom of the funnel. Content closest to the buying decision is where to begin.
• AI content can rank, under one condition. Only use AI where you already have expertise, and give it enough context to produce something worth publishing.
• Great content alone isn't enough. Reviews, PR, Reddit, G2 and Trustpilot have to back it up, the way Canva and HubSpot built theirs for years.
• Tell one story everywhere. Your website, LinkedIn and PR have to describe your brand the same way.