Michael Transon

Episode 17  ·  The Search Signal Anthropic Bans Fake Sources for AI Search October 22, 2026 · 33 min · Hosted by Michael Transon Listen on: Spotify Apple Podcasts YouTube About this episode The conversation Search marketing has always offered two ways to look credible: build a brand that holds up under scrutiny, or fake the appearance of one. AI search has made the shortcut tempting again because an AI assistant deciding who to recommend leans heavily on what other...

Episode 16  ·  The Search Signal How To Create a Mention Building Program October 8, 2026 · 31 min · Hosted by Michael Transon Listen on: Spotify Apple Podcasts YouTube About this episode The conversation A lot of AI search advice still centers on a company’s own website: fix the technical setup and publish better content, and visibility will follow. But when ChatGPT or Google’s AI Mode answers a question about a category, it builds its answer mostly from other...

When marketing leaders ask whether their technical SEO covers them for AI search, Michael's answer is mostly yes. Google's AI Overviews and AI Mode run on Google's regular index, and most of a standard technical audit carries over to the other platforms. This week he sorts technical work into what to keep, what to start, and the short list of things to skip, including a training-bot decision that removes your own description of your company from what the next model...

For most of the last decade, brand was the marketing line item hardest to defend, because there's no click to track when a buyer arrives already knowing who you are. AI search changes that math. An assistant reads your website, your listings, your reviews, and every page that mentions you in passing, hands the buyer one summary, and decides whether to name you at all. This week Michael connects brand entity work to the brand building marketers already know how...

For 15 years, marketing measurement got more precise every year. AI search is moving the other way. An assistant's recommendation happens in a conversation you can't see, and no platform will tell you what was asked. So how do you measure and report on it? Listen to find out.

With searchers seeking recommendations on AI platforms, your bottom-of-the-funnel strategy has to account for increasing mentions in those answers as well as what they'll find when they finally visit your site.

Publishing informational content used to have a clear return: the post ranked, people clicked, and the traffic showed the work was paying off. Now that traffic to TOFU pages has fallen dramatically, is creating informational content still worthwhile? In this episode, Michael makes the case that the part of your content AI can't produce is the part that earns the citation.

The need for a full funnel search strategy doesn't go out the window because of AI search. In this episode, Michaels lays out the foundation for what an integrated AEO and SEO strategy should look like.

Google is rebuilding search around AI Mode, and in this episode, Michael Transon makes the case that it will become the default way people search. Listen as he walks through the evidence, from the rapid spread of AI Overviews to the rise of zero-click results, and explains why AI Mode's modest adoption numbers understate what's coming. Plus, get practical tips for how to update your strategy so you can stay visible on every Google surface.

ChatGPT, Claude, Gemini, Perplexity, and Google's AI surfaces all arrived at practically the same time, so most marketers built one AI search strategy to cover them all. This week, Michael makes the case that these platforms have grown too different for a single playbook and walks through how to decide which ones deserve a dedicated strategy.

Marketing budgets have dropped to less than 8% of company revenue, roughly 18% below where they sat four years ago, and the AI line item inside those smaller budgets keeps climbing. Put those two numbers next to each other and one move looks obvious: hand the search work to AI, stop paying for the people, and bank the difference.

Many AI search plans rest on a comforting assumption: teach the model what you do, describe yourself clearly enough, and the recommendations will follow. It feels right, and it's shaping how a lot of marketing budgets get spent. In this episode, we share what happened when we tested this assumption.