Jason W.

AI Mode in Google Search is rolling out in the US today. This is a huge shift for search as it will provide a direct response to user queries and allow for chat-like follow-up conversations to occur. Some implications from this feel fairly obvious -- organic traffic will decline for most sites assuming this new feature gets widespread adoption. The question of how publishers are expected to make money if they don't get the same level of traffic definitely remains unanswered. What I keep getting stuck on is if publishers go under, what will AI train on in the future? If partnerships start to emerge between large publishers and companies like OpenAI and Google, we're going to lose smaller, niche publishers. And I'm not sure I want an internet that only consists of content from a handful of parent companies like Conde Nast. What a depressing thought. So I really hope companies like Google are looking further down the road at implications for publishing. I'm not convinced they are though. I am not someone who thinks this is the end of the road for SEO. The fight to get into the results is only going to get more competitive. There will always be opportunity to help sites optimize and grow. But, there are definitely going to be fewer sites to help in the future, and that feels like a shame. What makes the internet great is the diversity of voices out there. Wired did a good writeup on this and some of the accuracy concerns they have with the results in AI Mode and their generative AI experiences in general. It's worth checking out. It's posted in the comments below. ⬇️

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Skip this and watch Meta drain 40% of your ROAS every month: Most ad accounts treat every buyer like a new one. That means you’re paying acquisition rates to reacquire customers who already love your stuff. I see tons of brands spending $50 on “wins” that email could have gotten for $10. It happens because Meta forgets who people are once they leave the in-app browser. Someone taps your ad, drops their email, and comes back a month later…and Meta counts them as brand new. This breaks your Klaviyo flows and you end up paying Meta just to buy back your own customers. Clever media buying can’t fix that. But here are two things that will: 1) Make sure returning buyers are identified and tied to their email. 2) Add three columns in Ads Manager:  • Purchases • New-customer purchases • Subscription purchases Once you see those clearly, you stop judging ads on blended CPA and start judging on new-customer CPA and New Customer ROAS. That’s the difference between scaling profitably and lighting money on fire. So let Meta handle acquisition.  And let email and owned channels handle retention. Clean your feed, separate your metrics, and stop letting Meta charge you twice for the same customer.

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This morning, AdWeek published my thoughts on how a new era of AI search is upon us. The "Searchpocalypse" is already reshaping discovery—and expectations. As SEO collapses and AI-native consumers demand instant answers, brands must rethink demand gen, retool content for agents, and meet users where AI lives. https://lnkd.in/gjkeQqWR

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If an agency claims to do everything, run. B/c what they really offer is mediocrity. It sounds great—everything under one roof. But "full-service" is just code for “we’re average at everything.” You can’t excel when spread thin. You can’t win when you go wide. Full-service exists to boost their profits, not yours. In the end, they lose. And so do you. I learned this the hard way— 10+ years in-house (CMO). I tested many full-service vs. specialists. The best agencies dominate 1-2 channels. Anything more, and they can’t be the best.

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Manual targeting used to feel like a superpower. In 2026, it’s just one small lever. Here’s what actually changed. The algorithms got better at predicting buyers than any interest stack ever could. These platforms sit on years of engagement, purchase, and behavioral data. They don’t need you playing detective with 50 interests and 10 lookalikes anymore. What they need now is much simpler: Clear signals. Clean setups. Strong creatives. That’s why manual targeting matters less today. Broad targeting, Advantage+-style setups, and simplified structures are winning. Not because platforms are being “nice”, but because they learn faster when you stop over-controlling everything. The game has shifted. It’s no longer: “Who can find the most niche interest combo?” It’s now: “Who can send the smartest signals into the system?” Those signals come from a few core places. → Creatives that clearly call out a problem, desire, or identity → Landing pages that actually match the ad promise → Clean event and pixel setups sending reliable data → Offers that make it easy for real buyers to convert → Simple account structures that let learning happen fast Manual targeting still has a role. But it’s not the hero anymore. It’s for edge cases. Not a belief system. If you’re obsessing over interests while ignoring creative and offers, you’re optimizing the wrong layer. In 2026, real leverage comes from: → Creatives that pre-qualify the right people → Offers that lift conversion rate and AOV → Clean data so the algorithm knows what “good” actually looks like Fix those first, and you can go broader, learn faster, and scale smoother. If performance is struggling, the real question isn’t: “Which interest should I test next?” It’s: “What signals am I sending the algorithm and are they any good?” Manual targeting didn’t die. It just got demoted. The real boss now is your creative, your offer, and your data.

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Factors.ai just released their LinkedIn Benchmark Report and the results are impressive. They analyzed 100+ B2B marketing teams and found: Traditional lead-gen tactics are seeing diminishing returns. @LinkedIn ad budgets are growing 5x faster than Google Ads. 92% of buyers have a preferred vendor before formal evaluation begins. This isn't a minor course correction; it's a fundamental shift in strategy. The data shows that top-of-funnel brand building is no longer a "nice-to-have"—it's the new competitive battleground. Download Factors' LinkedIn Benchmark Report to get the data-backed playbook for navigating this new reality: https://lnkd.in/gV5PC2r2 #B2BMarketing #MarketingROI #LinkedInAds

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Yes, the best way to show up in the new world of search is to revamp your information architecture. But I'm seeing a lot of very sketchy content structure and navigation design recommendations coming from the SEO influencer hive. Their solutions for "query fan out" are.... middling, at best. No, you don't need "fraggles" or "chunking" or whatever term they've invented related to 1980s kids' entertainment. The concepts behind these recommendations are worth your attention, but the methods SEO leaders are advocating to your UX and info architecture are... less than ideal. They've nailed the cause, but not the cure. "Chunking" is trying to reverse engineer what UX folks call Content Modeling. Content Modeling is an established concept in content strategy that identifies core components of content and creates structured interfaces like SERPs. Or streaming platforms. Or AI overviews. (I learned it in 2014.) Another, similar approach is called object-oriented UX (OOUX). Both OOUX and Content Modeling are top-down structural evaluations based on the neuroscience of how people process and evaluate content. When people like and use your content because it's well-structured, it becomes mentioned and recommended more often, builds authority, EEAT, etc. (And yes, I have proof.) If you value your audience: don't change your navigation and page linking strategy without consulting someone who knows UX. SEO folks have a long trail of web garbage behind them, especially in structure and navigation. I saw a prominent influencer recommend "more in-line links" for "better UX" and... clearly he has never read the many pieces of research that say in-line links make navigation more confusing for all but the heaviest internet users. Navigation and information architecture belong with systems thinkers and editorial organizers who understand big-picture content strategy. I'm slotting some tips on info architecture optimization into my newsletter for the next month. (And the newsletter resumes tomorrowI I promise!) And in the meantime: - The great Sophia V Prater has many OOUX resources to share. Google "OOUX," and she owns it. - Button is an upcoming virtual conference about Content Design from the legendary creators of aforementioned Confab. - Greg Dunlap recently published a book called Designing Content Authoring Experiences, if you're looking for a more advanced look at creating systems that creators can use to build better structure. If you've never taken a content design or UX course before, the above are great places to start, before you go tearing up your navigation because some dude thinks you'll be mentioned in LLMs with the chunking. And if you need support on an upcoming IA project (especially prepping IA for AI), raise your hand and I'll send the names of some very smart structural thinkers.

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Got into a heated debate last night about product marketing hires—specifically, whether or not subject matter expertise (SME) should be a requirement for a PMM role. The setting was a swanky dinner roundtable in SF with a dozen or so growth and marketing leaders—no actual product marketers were present (or harmed) at this meetup. The general crux of the debate was whether SME could/should be learned on the job and, if so, on what time horizon. The group fell into two camps: 1) Camp SME required 2) Camp SME not required Here’s a case for and against each camp… 🏕️ Camp SME required Case for 👍 - Faster onboarding cycle - Built in empathy with core ICP - More autonomy (fewer asks of others to review work) Case against 👎 - Longer time to hire - Smaller candidate pool - More challenging to scale - Too close to the problem (grasping at straws a bit here) Disclaimer: It should be noted that I fell into this camp. Reflecting on my marketing failures, I realize it’s often been where I lacked firsthand experience of the target audience’s pain points and lost trust with both them and the CEO. –––––– 🏕️ Camp SME not required Case for 👍 - Faster time to hire - Larger candidate pool - More repeatable/scalable motion - Not jaded by the curse of knowledge - Flexibility to move to alternative product lines Case against 👎 - Longer time to ramp - Risk of losing credibility with core audience - Slower to ship (e.g., asking SME for feedback) –––––– Anyway, I don’t think we got to a consensus but it was definitely a fun and lively debate. Would love to hear from some ACTUAL product marketers and others with strong opinions on the matter—you know the drill :) ======= P.S. Big thanks to Theory Ventures and Tomasz Tunguz for hosting!

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🔍 LLMs are the new homepage but most brands don’t even show up. Today we launched something at Wix that changes that and we’re the first CMS to do it 🙌 It’s called AI Visibility, and it’s built for the new rules of discoverability. Not just SEO. This isn’t about chasing rankings. It’s about understanding how models view your brand and even how you compare to competitors. 🚀 And it’s available now, built into Wix There’s a lot more coming on this front from us... ... But for now, if you’re wondering what it looks like to optimize for AI, this is your starting line. Watch the video 👇 #AIVisibility #LLMSEO #ZeroClickGrowth #ProductAsPrompt #Wix #AIContentDiscovery

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Modern measurement needs to move from just reporting on outcomes to driving more of them. That's why we're launching the Meridian Scenario Planner. This will help marketers ask "What if I move 20% of my TV budget into YouTube next month?" instead of "How did YouTube perform last month?" Nearly 40% of marketers struggle to connect MMM outputs to real-world business decisions. The Scenario Planner addresses this gap in 3 ways: 1️⃣ You can see straight away what’s working in your strategy and how to drive the best results. 2️⃣ The interface lets you experiment with different budget scenarios in real-time and see potential ROI instantly – without needing to code. 3️⃣ It shifts focus from "what happened" to "what’s next," and can build forward-looking plans to move forward with confidence. Catch more details in the blog:  https://lnkd.in/e5ci9qBZ

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In 2026, ABO is no longer the best way to test creatives. I didn’t want to believe it either. But after testing CBO since September across five different accounts, the data was very clear. CBO was ~27% more efficient on average. Here’s the CBO testing structure I’m running now: - Exclude all existing customers (Klaviyo + Pixel) - 100% Broad targeting - Set a minimum spend per ad set to force learning - Use Flexible Ads when I’m testing very similar creative variations What happens next is key 👇 Winners move into CBO Scaling Top performers also get pushed into Whitelisting & Partnership campaigns That said… I still see ABO outperform CBO in some accounts, especially smaller ones. So make sure to test both and see what works best for your account.

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