On this week's AI to ROI podcast, Ray Rike is joined by Stephan Bajaio, co-founder and CEO of VibeLogic and a former co-founder of Conductor, the enterprise SEO platform he helped build over 14 years, culminating in a WeWork acquisition, a management buyback, and a valuation approaching half a billion dollars. With 25 years spanning e-commerce, Yahoo, Time Inc., and a stint as a software CMO, Stephan brings an operator's view of what has actually changed in the buyer journey and what has not. The conversation centers on a hard number. When Stephan asked the marketing team at a $3 billion company what share of their web traffic was being driven by LLMs, the estimates ranged from 20 percent to 50 percent. The measured answer was 1 percent, with a high conversion rate on that small base. That gap between perceived and measured contribution is the core problem for any executive being asked to fund an AEO, GEO, or AIO program this year. Stephan introduces Web Presence Intelligence, a supply-and-demand framing designed for executive conversations rather than channel specialists. Demand is what goes into the search bar or the prompt. Supply is everything that comes back, including publishers, Reddit threads, affiliates, partners, and competitors. The strategic question becomes whether you are influencing where your buyer's opinion is formed, before you decide where to place the bets. Ray pushes back directly, arguing that understanding where models source citations should now outrank owned web properties. Stephan holds his position, and the exchange gets to the heart of the allocation decision facing CMOs and CFOs. In this episode: Web Presence Intelligence defined, and why supply and demand is the right executive language for a channel conversation The four P's of owned content: point, paragraph, page, path, and the audit finding that most sites never actually name the problem they solve in the customer's own words Why owned assets matter more when the interpretation layer keeps changing, illustrated by a professional who lost a decade of LinkedIn equity overnight Attribution reframed as a consequence of measurement rather than a measurement itself, and how to work backward from the sale to the second and third best proxies The baseline requirement, or what Stephan calls the before photo, and why AI deployed against a process you do not already understand produces outcomes you cannot judge Control groups in practice, including a market share test on terminology that showed one enterprise software company exactly what its brand guidelines were costing it in visibility Why the gold rush money went to the people selling pans, and where the actual near-term return sits: auditing your own sales calls, renewal conversations, and customer logs From funnel to hourglass, and why channel ownership models are breaking down as generalists get more capable with AI Augment, automate, or build net new: three different projects that require three different budgeting methods and three different attribution models The operator takeaway: control what you can control, establish a baseline before you fund the initiative, and structure AI marketing investments so the return can be defended against assets you own rather than placements you do not own. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
