Search as a Channel – Détails, épisodes et analyse

Most teams measure AI visibility as one blended score. New data across 3.7 million citations from ChatGPT, Perplexity, and Google AI Overviews shows why that's a problem: only 2.37% of cited URLs appeared across all three engines, while more than 91% showed up in just one.

In this episode, we unpack why presence is no longer enough and why portability, the ability of your content to travel across AI retrieval systems, is the metric search leaders should actually care about. We cover why guides and tutorials outperform homepages in cross-engine citations, why grounding answers is a different job than ranking pages, and a three-layer measurement model covering presence, portability, and concentration that you can bring into your next leadership meeting.

If your AI visibility looks healthy but rests on one engine's habits, you may be renting visibility rather than building it.

Your brand might be ranking just fine and still vanishing from the AI answers that drive pipeline. We unpack cluster collision, the moment LLMs decide your messaging sounds too much like your competitors and summarize you all away. If you lead an agency or own a growth strategy, this one reframes how you think about visibility.

Inside the episode:

Why pattern matching in SEO now works against you in AI search

The data on source rotation, citation, and why being cited isn't being recommended

How to spot where your messaging is interchangeable with competitors

What it takes to build a narrative AI systems retrieve, repeat, and recommend

Why your real competition is the cluster of brands an LLM can collapse you into

The question to bring to your next leadership meeting: is your content making your brand more visible, or more interchangeable?

While everyone's debating what AI is doing to Google, a different search engine is quietly becoming one of the most valuable organic channels in digital marketing.

YouTube processes over 3.5 billion searches every day. It's deeply integrated into Google's ecosystem. Its videos are 200 times more likely to surface in AI-driven search results than other video formats. And most agencies are still treating it like a social platform.

In this episode, we make the case for YouTube Search as a strategic growth engine and break down exactly how agencies should be deploying it for clients right now.

We cover why YouTube's algorithm has shifted away from keyword density toward behavioral signals like retention rate and intent matching, how the "pre-qualification effect" makes video search traffic convert differently than traffic from any other channel, and why a single well-optimized video can keep generating leads for years. We also get into the tactical side — spoken keyword optimization, using Shorts to capture top-of-funnel micro-intent, and how to structure topic clusters that the algorithm actually rewards.

In a zero-click world where traditional organic visibility is getting harder to defend, YouTube Search is one of the few channels where the arbitrage opportunity is still wide open.

The traffic numbers look fine. The revenue story is more complicated.

AI-powered search is no longer coming, it's already reshaping how users find information, evaluate brands, and decide what to buy. AI search traffic is up over 500% year over year. Zero-click searches now account for roughly 60% of all queries. And the attribution models most marketing teams are still relying on? They were built for a different internet.

In this episode, we get into the actual data behind AI's impact on search — what's changing, what it means for organic traffic, and why the businesses that adapt fastest have a real advantage over the ones waiting to see how it plays out.

We cover why AI search visitors convert at dramatically higher rates than traditional organic traffic, how zero-click search is forcing a complete rethink of what a "high-value URL" actually means, and why last-click attribution is quietly causing teams to undervalue their most important pages. We also break down the shift from SEO to Generative Engine Optimization — what it is, why traditional brand strength no longer guarantees AI visibility, and what a smarter content strategy looks like in this environment.

The data is clear. The question is whether your strategy has caught up.

Your leads are coming from AI. Your attribution model has no idea.

As more consumers turn to ChatGPT, Google AI, and other large language models to research products and make decisions, a growing portion of your pipeline is being influenced by interactions that never show up in your analytics. No click. No UTM parameter. No referral source. Just a direct visit from someone who already made up their mind thanks to an AI recommendation you can't see.

In this episode, we break down why traditional attribution models are failing in an LLM-driven world and what marketers actually need to do about it.

We cover the "dark AI" problem and why so much LLM-influenced traffic looks like direct, the metrics that matter for AI visibility citation share, sentiment analysis, and brand voice consistency and how first-party data, schema markup, and RAG are becoming essential attribution infrastructure. We also get into multi-touch attribution for AI exposure, how to run incrementality studies to measure LLM-driven lift, and why asking customers directly is making a comeback.

If your attribution stack was built for a world where every touchpoint gets a click, this episode will show you what you're missing.

More content isn't always better. Sometimes it's the problem.

Most websites grow the same way pages get published to meet immediate needs, then never touched again. Blog posts drift. Landing pages go stale. Duplicate content piles up. And quietly, all of that dead weight starts dragging down the pages that actually matter.

In this episode, we break down content pruning, what it is, why it's one of the most underrated levers in SEO, and how to do it without accidentally killing pages that are driving revenue.

We cover how low-quality and outdated content dilutes your topical authority and wastes crawl budget, why branded and non-branded content require completely different pruning strategies, and which metrics actually tell you whether a page should be kept, updated, consolidated, or cut. We also walk through the most common pruning mistakes, including the ones that look like progress but quietly cost you rankings and link equity.

If your site has been growing for years without a real content audit, this episode is your starting point.

Everyone's tracking AI search. Almost no one is tracking it correctly.

As AI platforms like ChatGPT, Google AI, Claude, and Grok take over how people discover and evaluate brands, marketing teams are scrambling to monitor every prompt variation they can think of. The result? Noise, false confidence, and a whole lot of wasted effort.

In this episode, we break down which LLM prompts are actually worth tracking and why the answer might be far fewer than you think.

We cover why AI systems care about intent categories, not individual phrasing, the five core prompt types that genuinely influence AI search visibility, and why branded and nonbranded prompts need to be tracked completely separately. We also explain how to turn prompt tracking from a data collection exercise into a real feedback loop for your content strategy.

If your brand looks fine in traditional search but keeps disappearing from AI-generated answers, this episode explains why and what to do about it.

Google just got a patent that should terrify every marketer.

It describes a system where Google uses your product data, your brand assets, and your conversion metrics to build its own landing pages and serve them in search results instead of your website. If your site doesn't hit Google's quality benchmarks, they don't send traffic your way. They just… replace you.

In this episode, we break down exactly what this patent reveals, how Google plans to evaluate your site (and what happens when you fail), and what it means that your website may already be quietly transitioning from a destination into a data source feeding Google's own commerce ecosystem.

This isn't speculation. It's filed, granted, and coming.

We cover what marketers and business owners need to do right now  from structured data architecture to building brand independence before Google finishes cutting you out of your own sales funnel.

Between 65% and 85% of what buyers now ask AI has no matching keyword in traditional databases. If your strategy still starts with keyword reports, you are using a shrinking map to describe a growing territory, and that is a dangerous place to be in a board meeting.

In this episode, we break down why search volume is becoming a lagging indicator, how to spot the demand your tools cannot see, and what the smartest CMOs and agency owners are doing instead, from mining sales call language to tracking AI citations and the "ghost citation" problem.

If your traffic is flat but your pipeline questions are getting sharper, this is the conversation that explains why, and what to do next.

If your brand is ready for AI answers but not AI actions, you're already behind. Most marketing leaders are still thinking about AI as a smarter search engine. But the real shift is bigger: AI isn't just answering questions anymore. It's learning to take action on behalf of customers. Booking, buying, comparing, recommending. And the brands that win won't be the ones with the most content. They'll be the ones AI can actually do business with.

In this episode, we break down what the "agentic web" means for agency owners, CMOs, and marketing leaders, no engineering degree required. We cover why being findable by AI is no longer enough, what it takes to become actionable inside AI-driven customer journeys, and the practical steps your team should take in the next 90 days. If AI agents became a real acquisition channel tomorrow, would your business be ready? That's the conversation we're having.