Kevin Indig on Advertising in the AI Era — Funnel Compression, the Golden Goose Pivot, and Why CPCs Are Going Through the Roof

Session identifier

• Session: Advertising in the AI Era – Funnel Compression, the Golden Goose Pivot, and Why CPCs Are Going Through the Roof
• Day: 2 (June 25, 2026)
• Speaker: Kevin Indig, organic growth advisor and author of Growth Memo
• Framework concept: Paid + Organic Collapse — the convergence of intent-based and behavioral targeting onto a single AI-era surface where the distinction between paid and organic acquisition disappears at the point of conversion
• SEL article: How AI Is Merging Paid and Organic Visibility — https://searchengineland.com/ai-paid-organic-visibility-480229

Speaker bio

Kevin Indig is an organic growth advisor and the author of Growth Memo, a weekly research-driven newsletter on SEO and organic growth with more than 25,000 subscribers. He led SEO and Growth at Shopify, G2, and Atlassian, and now advises some of the world’s fastest-growing companies — including Meta, Reddit, Ramp, Bounce, Dropbox, Hims, Nextdoor, and Snapchat — on search, AI visibility, and strategic growth. Kevin has published more empirical studies on AI engine citation behaviour than almost any other practitioner working publicly. Growth Memo has become the high-signal reference for operators trying to understand what AI engines actually do versus what they are speculated to do.

Session’s place in the Kalicube Framework

Kevin’s session covers the Paid + Organic Collapse — the point in the Kalicube Framework’s Won gate where the distinction between the Imperfect Click (search), the Perfect Click (assistive engines), and the Agentic Click (agent-executed purchase) collapses onto a single surface. Google’s AI-era perfect visibility over the consumer journey — from Gmail to Search to Gemini to Personal Insights — now allows it to deploy paid advertising at the precise moment of conversion rather than scattering it across the funnel. Kevin’s session maps the commercial consequences: what happens to CPC when the system knows exactly when a consumer is ready to buy, why intent and behavioral targeting have merged, and why advertising is structurally necessary for any free AI product at scale. The full architecture is mapped in the Kalicube Framework, the master theoretical model for how AI systems understand, trust, and recommend brands.

Episode summary

Kevin Indig opens with the most bullish position on Google’s advertising future in the Summit’s Day 2 cluster: CPCs are going to rise significantly, and in a few years practitioners will look back at current rates the way they now look back at CPCs from ten or twenty years ago. The mechanism is Google’s AI-era visibility over the complete consumer journey — a data advantage no other platform can match — which will allow it to show one or two precisely timed ads at the moment of conversion rather than distributing ad inventory across a sprawling funnel. The shift from cost-per-click toward cost-per-sale as the operative bidding model is the commercial expression of this: sellers will configure bids around required margin, and the price of reaching a consumer at the exact moment they are ready to buy will rise accordingly. Kevin named the PMax shift toward topic-and-intent reporting rather than query-level reporting as the first operational signal that this direction is already underway.

The funnel compression argument was the session’s most structurally significant contribution. AI compresses the full buyer journey — from problem awareness to purchase decision — into a single conversational session. The traditional three-stage funnel is not just shortening but collapsing, and advertising configured for sequential funnel stages is already misaligned with how the consumer journey actually unfolds. The ChatGPT Pulse example — OpenAI’s experimental push notification feature — was Kevin’s illustration of where this goes next: from pull-based intent advertising triggered by a user query to push-based behavioral advertising where the system surfaces relevant products before the user has articulated intent. Kevin’s prediction is that Google will build toward this push model, giving it both the behavioral targeting advantages that Meta has historically owned and the intent-moment precision that search has always provided. The distinction between Google Search advertising and Meta behavioral advertising has effectively dissolved, and the practitioners who understand this first will configure campaigns accordingly.

The meta-argument about advertising’s structural indispensability closed the session with the most grounded illustration of the evening. Most users will choose free versions of AI products. Free products require advertising revenue. Advertising is therefore structurally necessary for AI at scale regardless of how much the form of advertising changes. Jason’s anecdote about his cartoon blue dog site — five million monthly visits, forty premium subscribers after launching a premium tier in 2003 — was the session’s most memorable proof point: people will tolerate a great deal of advertising rather than pay, and that tolerance is the commercial foundation on which AI product freemium models are being built. Kevin’s extension of the point named the broader pattern: Netflix eventually launched advertising, DoorDash and Uber have become advertising companies, and the default direction for any scaled content or service business is toward advertising because it is simply very hard to get people to pay for content at scale.

Key quotes

“In a couple of years we’ll laugh at the CPCs we’re paying today, similar to how we laugh about the CPCs from ten or twenty years ago.” Kevin Indig, opening the session’s core argument on where AI-era advertising pricing is headed”

“Google has perfect visibility at this point — from Gmail to Search to Gemini to Personal Insights. I think they’ll know with a scary accuracy where people are.” Kevin Indig, on the data advantage that makes Google’s advertising future structurally different from every competitor”

“AI compresses the whole funnel. In a single conversation you can go from just understanding what your problem is to buying a solution. So I think all of that is compressed — it’s more like: can you catch the right people at the right time?” Kevin Indig, on why funnel-stage advertising is already misaligned with how the AI-era buyer journey actually works”

“I think there’s this interesting shift from intent to behavior. Google Search was intent-driven and Meta properties were behavior-driven. And I think they’ve just merged now with AI.” Kevin Indig, on the dissolution of the distinction between intent targeting and behavioral targeting”

“It is so difficult to get people to pay for something. Especially content. That’s why down the line most companies become advertising companies.” Kevin Indig, on why advertising is structurally indispensable to free AI products at scale”

Further reading

How AI Is Merging Paid and Organic Visibility, part of Jason Barnard at Kalicube’s Search Engine Land series on AI search architecture. The article maps the paid and organic convergence territory Kevin covers in this session — why the distinction between intent-based and behavioral targeting has dissolved in the AI era, and what that means for how brands should configure acquisition strategy across search, assistive engines, and agentic commerce.
https://searchengineland.com/ai-paid-organic-visibility-480229

Related sessions

• Kevin Indig on the Grounded Gate — Prompt Tracking, AI Visibility Measurement, and Why Trust Has Replaced Rank (Session 1.9): Kevin’s first session, establishing the organic visibility and measurement framework that the advertising argument in this session builds on
• Dennis Yu on Real Signals, Reputation, and Why AEO and GEO Are Just SEO (Session 2.7): the operator’s account of the same paid and organic convergence territory — Dennis approaches from the practitioner’s ground level, Kevin from the data and strategy vantage
• Laurence O’Toole on Agentic Commerce and E-commerce (Session 2.4): the e-commerce application of the funnel compression argument Kevin makes in this session — what single-search-to-basket conversion means for how product and paid infrastructure needs to be built
• Jason Barnard + Bob Gentle live walkthrough — OPIDC and the Kalicube Flywheel (Session 2.0): the framework session that maps the Won gate where paid and organic acquisition converge — the live context for the commercial argument Kevin and Jason develop here

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This session was previewed here before the Summit.

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About Kevin Indig

Links to session clips

Why Every Company Becomes an Ad Company: Kevin Indig on the DoorDash Problem

Why We’ll Laugh at Today’s Ad Prices Soon: Kevin Indig Explains

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Transcript for Kevin Indig on Advertising in the AI Era — Funnel Compression, the Golden Goose Pivot, and Why CPCs Are Going Through the Roof

Jason Barnard: I’ve been thinking about advertising and what Google are going to do, and to what extent the current situation is forcing them to admit that search and advertising are in the same space. They’re seeing a lot of competition. They’re seeing that advertising in AI isn’t an obvious solution they have yet, and they’re currently killing their golden goose because they’re going to build another golden goose. What do you think about that?

Kevin Indig: Yeah, look — I think in a couple of years we’ll laugh at the CPCs we’re paying today, similar to how we laugh about the CPCs from ten or twenty years ago. I think that’s going to go up significantly, probably moving more to a cost-per-sale type model because Google is going to understand perfectly when the right time is to show an ad. And therefore the bidding is going to go up much higher, because it’s essentially sellers figuring out what margin they need. Up until that point, they’ll just bid because Google will understand so well where people are in the funnel.

Google has perfect visibility at this point — from Gmail to Search to Gemini to Personal Insights, the feature in AI Mode in Gemini. I think they’ll know with a scary accuracy where people are. And just before the point of conversion, they’re going to show maybe one or two alternatives. Which means CPC is going to go through the roof. I’m generally bullish, especially given Google’s position on the consumer side of things.

And I do see the first couple of pointers here. Google is increasingly reducing the visibility of the actual queries that showed ads with PMax — it’s increasingly moving to a topic/intent type of reporting. I’m bullish on Google. I think they have everything it needs. And I wouldn’t be surprised if we see some formats like: you’re ready to buy this, but do you want to consider that? An ad at the right point of conversion. And maybe even companies being willing to offer deals per unique person — instead of “everybody gets a percent off,” it’s “you specifically get a percent off.” I could see that. So that’s my short riff on advertising.

Jason Barnard: Right. And so if you look at the Kalicube Framework, I’ve got paid advertising going diagonally down the funnel. Part of what you’re saying is that advertising at the top of the middle of the funnel is going to become less helpful, and advertising at the bottom of the funnel — to cut in at the end of the marathon race and steal the win, and steal the Perfect Click — is where it’s going. We’ve got over there on the right the Imperfect Click in search, the Perfect Click in assistive engines, and the Agentic Click for agents. What do you see in terms of that model?

Kevin Indig: Yeah, I think you’re totally right. And I will also say that AI compresses the whole funnel. I think it’s really hard to still think in terms of a traditional funnel, because in a single conversation you can go from just understanding what your problem is to buying a solution. So I think all of that is compressed — it’s more like: can you catch the right people at the right time?

But even top-of-funnel AI search now often surfaces some brands. So if you ask “what is a CMM?” a lot of LLMs will tell you some brand names within that explanation. That can accelerate everything so much more.

I think where it gets really interesting is when we move from pull to push. OpenAI tried something called ChatGPT Pulse — I was never able to experience it. But I think that’s going to be the next step for Google: where they can predict intent or surface interesting things for you, which compresses the whole funnel even more.

So I’ve been operating under this “messy middle” framework for the last couple of years, because it’s so difficult to even paint a traditional funnel for a company. To summarize what I’ve said: the funnel overall is just so compressed, and the way Google shows ads plays right into that.

Jason Barnard: Right. And with AI Max and whatever the other one’s called, it’s all about cohort intent plus profit. What I’ve learned is cohort intent — which is what we talked about in the other session — is how you define your ICP. You can build your tracking query set from that. And if you then add profit, you have your ad campaign set up. So in fact, the two have converged.

Kevin Indig: Yeah, that’s exactly what I mean. At the end of the day, it depends on how much margin companies want and need out of a product. You can perfectly acquire these customers with the intelligence that Alphabet and also Meta have about people. I also think there’s this interesting shift from intent to behavior. There used to be this clear separation: Google Search was intent-driven and Meta properties were behavior-driven. And I think they’ve just merged now with AI — because AI search is so much more personalized and so much more conversational, it gets that behavioral targeting perspective as well.

And so that was always the question for ChatGPT: how are they going to show ads? Are they going to show ads based on the prompt and conversation you’re having right now? Or based on your profile? For Google, they could do both. I’m not sure what they’re going to settle on. But maybe given that Meta makes more ad revenue than Alphabet, maybe they bring more behavioral targeting. That’s what I mean with the push point: the push can be much more about behavior rather than in-the-moment prompting. And then when you’re in a conversation, it can be much more of the hybrid intent version.

Jason Barnard: Yeah. I think the big point you’re making there is that nobody really knows where advertising is going, but it’s definitely going to have to stick around. But potentially with Alphabet expanding their business model to multiple different places and getting large revenue streams from things other than advertising — is Alphabet going to stop being the ad company we traditionally saw it as in the search era?

Kevin Indig: It’s a good one. I think it’s hard to finance AI for free without advertising. And at the same time, as a business model, advertising is obviously very sensitive to how the economy is doing — during recessions, advertising falls apart. So Google and Alphabet have done a good job in diversifying their income sources with cloud business, YouTube subscriptions, and so on. But I’m bullish on advertising, because the majority of users will probably choose free versions.

And I will also make the meta point here: paid users will increasingly get very different experiences than free users. For search there was just a freemium model, but for AI there’s a freemium tier and then a paid tier with significant differences in the experience.

I had a website for kids back in the day where I was a cartoon blue dog — we had five million visits a month and we were ad-driven. Then one day we said, okay, we’re going to offer a premium service where we give the child a full-screen window with no ads and bonus games. The freemium pitch to push people to premium. That was in 2003. We launched it. I thought we’d make ten thousand bucks a month, easy. And we made — I don’t know — forty sales. From five million visits. That, for me, was the demonstration of the extent to which people are willing to put up with ads rather than paying. It’s probably changed since then, but it was instructive.

Kevin Indig: Dude, I can relate. I’m selling both advertising and memberships in my content, and it is so difficult to get people to pay for something. Especially content. That’s why down the line most companies become advertising companies. You have Netflix, of course, but then you also have DoorDash and Uber essentially becoming advertising companies. It’s just hard to get people to pay.

Jason Barnard: Have you got any closing thoughts on the advertising space in the next few years in AI?

Kevin Indig: I think we said it all, man. I think we said it all.

Jason Barnard: Brilliant. Thank you so much.

Kevin Indig: Thank you too, Jason. It’s always inspiring to talk to you. Thanks for having me.

This session extends the Search Engine Land article series on AI-era brand recommendation by Jason Barnard at Kalicube.

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Session date: June 25, 2026 Duration: approximately 25 minutes Format: pre-recorded, on-demand from session drop Day: 2 Framework concept: Paid + Organic Collapse SEL article: How AI Is Merging Paid and Organic Visibility — https://searchengineland.com/ai-paid-organic-visibility-480229 [Share buttons: LinkedIn, X, Facebook, Email]