Jason Hobbs

Today we're changing Clay's pricing. Pricing changes are scary (for you and me!), but we are trying to do this in the most authentically Clay way possible - thoughtful, transparent and community-first. We've been thinking about this for almost a year (maybe too long Karan!), and have talked to hundreds of customers and partners. We want to align our business model with how our product is being used today, and set us up to grow sustainably together. When we launched, our customers used us for data enrichment. And now our community is using Clay to power their GTM engineering motions. But the pricing model hasn't evolved, so we're making some changes to reflect that. Here’s what’s important to note: First: nobody is getting forced off their plan. Every existing customer can stay on their existing plan. We have to earn the right for you to move to a modern plan. Second: most customers will see better value for their money with this change. If we think you'll save money by switching to the new pricing, we're going to reach out and tell you proactively. Third: we're separating the cost of data from the cost of the platform. We want to keep bringing down the cost of data in Clay, and make the value tied to what you orchestrate and build with it. Fourth: our best features are now more accessible. The new Growth plan includes things that used to live exclusively on Pro at a 38% lower price. Many of our most advanced users will save thousands a year. Our plans now come with a new metric called Actions, which measures the orchestration work Clay does for you: the workflows, AI research, and logic that turns raw data into a GTM motion. 90% of customers will never hit their Actions limit. We want most people to never think about it. That way, we’re only winning if you are. Data Credits now cover just the data - and they're cheaper. We’re reducing the cost of the data in our marketplace by 50–90%, making prices comparable to what you’d pay externally. Karan and I recorded a video walking through the full reasoning and who gets affected - positively and negatively (including us – we’re taking a 10% revenue hit). If you're a Clay customer and have questions, we want to hear them! Full pricing announcement and the internal memo we sent our team below. Announcement: clay.link/nF1eKMH Internal memo: clay.link/wiw2NHK

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If you heard about the IAB's AI Accountability for Publishers Act but aren't sure what exactly it means for the industry, this is a good summary. Essentially, it's raising the legal and reputational risks of ignoring publisher restrictions on "no crawl" specifications - something that's been notoriously hard to enforce so far. If it passes, the legal burden still lies on publishers to prove "illicit scraping", BUT it would be a powerful disincentive for AI companies to do so. Of course, we'll have to wait and see.

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The amazing Ron Jaworski and Noa Bonné from Trinity Audio had me over for a fun conversation about news publishers in the age of generative AI - full episode coming soon to a shelter near you!

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This is Big. And part of a trend. For years there has been a open v closed ecosystem debate. I have long said a pure open auction is not the way. Some walls are needed. This trend has long been apparent and now extending particularly in ctv. Youtube is no 1 in ctv and its got high walls. Netflix is number 2 in viewership (not yet ads) and whilst its ad platform is new, it definitely has walls. Here Amazon plus Roku is a clear no 2 in ads. More trends. The collaboration between tv networks in the US, the UK and globally. Broadcast quality ctv almost exclusively has walls. This is a good thing. Death of a DSP? Well thats click baitey but it does relegate the importance of the DSP. That being said the likes of TTD have their own powerful ecosystems. Its these private ecosystems that then fight for share.

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The industry keeps telling artists to "build superfans." Almost no one tells them how. A recent study by Luminate said that DSP's lead the way in in discovery for Superfans streaming platforms, then convert to shows and merch purchases. The first part is wrong. Discovery doesn't happen on streaming. It happens on social media. Instagram, TikTok, YouTube, wherever attention already exists and connection is possible. Streaming is where consumption deepens after discovery happens elsewhere. So, you can choose to not be on social media as an act of defiance (I get it ) but know this will make finding fans much harder. The old saying "go where the fish are" still applies. Discovery demands intentional visibility. But discovery is just the starting point. Once someone finds you, passive consumption isn't enough anymore. The bar has moved. People don't just want to hear the music. They want to understand the person making it. "I just want the music to speak for itself" sounds noble. But it's also a convenient excuse. The music has never spoken for itself — someone always had to tell the story. Connection at scale requires storytelling. Not confessional oversharing, but enough humanity that an audience feels like they know you. Then there's the infrastructure problem. Social platforms are discovery engines, not relationship engines. You can't build depth in an algorithm-driven feed designed for scroll velocity. The strongest artist-fan relationships happen off-platform: → Email lists → Discord servers → Patreon communities → Private podcasts Anywhere the artist owns the relationship and can communicate without platform intermediaries. And finally, monetisation. The study defines superfans by spending behaviour: ticket purchases, merch sales, physical format buyers, subscription supporters. Which means if an artist never creates offers, they can't develop superfans by the industry's own definition. Superfans need something to buy. Many artists resist this. It feels commercial, inauthentic, uncomfortable. But if someone wants to support your work and you don't give them a pathway to do it, you're not protecting artistic integrity — you're just making it harder for the people who already care. The ecosystem that actually works (and I've tested with 200+ artists): → Discovery (social presence, live shows, wherever your audience already is) → Depth (storytelling that builds connection beyond the music) → Owned infrastructure (email, community, platforms you control) → Income pathways (offers that let people support financially) Superfans aren't built through streaming algorithms. They're built through human connection at scale, supported by infrastructure most independent artists don't have yet. The industry won't build it for you. So you'll probably have to build it yourself. (Betty just asked what a superfan is. I told her it's someone who really, really likes you. She said "like Nana?" Close enough.)

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Element: <payment> -> Reddit, Yahoo, Medium, Quora, People, O'Reilly, wikiHow, Ziff Davis, and others adopt the Really Simple Licensing (RSL) standard that sets terms for AI scraping "The RSL Standard builds upon the robots.txt protocol, which has long allowed publishers to provide instructions to web crawlers about what parts of their site they can and can’t access. But instead of just saying yes or no to specific bots, websites can now add licensing and royalty terms to their robots.txt file. They can also embed the terms in online books, videos, and training datasets that they may want compensation for." https://lnkd.in/e9tJQNtr

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Welcome to The Advertising Forum! It's the final episode of our Agentic Monetization series, sponsored by Mula, and Chief Product Officer Joshua Markham comes up to the plate to unpack what “agentic” actually looks like in the wild. We covered: -How publishers can fight AI with AI -Real-time decisioning that lifts revenue per session -Why Slack as an interface beats dashboards -How agents create smarter page experiences without killing editorial voice The takeaway: the open web does not have to lose. It just needs better tools. Online monetization is moving from static systems to living, learning agents. And the winners will be the ones who adapt first. Big thanks to Mula and all of our guests: Jason White, Stephanie Mazzamaro, Brandon O'Neal, Heather Carver, and Joshua Markham for the insightful convos! Fun discussions all around, ATG! Looking forward to our next series post Thanksgiving!

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Adtech Groundhog Day? Read the latest Digiday article on CTV in the US and… wow, what a hot mess. It really makes me wonder: have we learned anything from the programmatic era? How familiar do these problems sound? • High and opaque pricing • Ad tech fees and lack of transparency • Inventory mislabeling And yet, the US is facing the same issues all over again in CTV. If I had any hair, I’d be pulling it out. CTV is one of the few bright spots left for premium content owners, but confidence in the channel risks being eroded by these market dynamics. And it’s not just the industry that suffers-consumers feel the impact too, which ultimately affects campaign performance. This line from the article nearly made me howl: “Do you just lift all your frequency [caps] so you can just deliver in full? Because then, from an agency standpoint, if you deliver under [the client’s target], there’s consequences. But when the providers are setting up guaranteed deals, setting their impressions, but they’re not hitting them — the math isn’t mathing.” In the UK, frequency capping is already driving me absolutely crazy. Is ad wear-out a thing? It is if you see the same ad continuously for three weeks straight. Has anyone seem the Range Rover ad as many times as me? Still not buying one. So, the idea that frequency capping might be turned off-wow. Despite these challenges, CTV remains an incredibly powerful medium when done right. If we prioritise transparency, smarter measurement, and a better viewer experience, there’s a real opportunity for the UK market to lead. We’ve seen before, especially in social video, that those who set higher standards can become the lighthouse for the industry. Which is why Unruly and Teads won out. At some point, hard measurement metrics will catch up with all of this, and then the premium pricing of CTV will crumble. When that happens, we all lose. I get that this is part of the game, but doesn’t it all feel a bit short-term? In the end, does it just mean more money flows to the walled gardens? These problems aren’t unique to the US -they’re a warning-and a chance to find competitive advantage if we’re paying attention. https://lnkd.in/exmXheAB

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Did you know 85% of marketers already use AI for content ideation and strategy? Even Clorox created an entire product using AI. Wild. Here is Part 2 of our Flint talk series. 🎥 This one dives into the trends that slipped into your feed without you noticing… and how AI is shaping the way brands build, test, and launch faster than ever. 🤖 #FlintIgnitesGrowth #AIMarketing #ContentStrategy #MarketingTrends #FutureOfMarketing

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Will Regulations Ever Be Enforced? | A clip from my Substack post, The ad industry isn’t broken, it’s been stolen by Google and Meta. Watch it here: https://lnkd.in/gj_4HKWJ

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Did you build this for ad tech? No, but this is what old friends and colleagues keep asking after I show them Vursu. The piece that never makes it into the stack is the operator-side context, how the team actually runs things, day to day. DSPs and SSPs handle the transactions. Native MCP tools handle the automation. The knowledge of how to run any of it lives in people's heads, in old Slacks, in spreadsheets nobody else opens. Every operator deals with some version of this. Vursu wasn't built for ad tech. The fit just keeps showing up. Every conversation with someone still in the trenches ends in the same place. The pattern has been too consistent to ignore. If any of this rings a bell, I'd love to hear what you're seeing on your end.

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A better user experience, a faster website, and a higher conversion rate just by moving from WordPress? Where do I sign?!?

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In film, producers own outcomes. In software, product managers own both user experience and business results. In creative work, ownership gets split until no one owns anything. This is why most agencies think they have a talent problem. In reality, they have an ownership problem. Complex digital spans product, web, data, commerce, CRM. Every change reverberates. If no one owns the whole system, you optimize parts and degrade the whole. Account management sells. Project management schedules. Creative makes it pretty. Engineers “build it”. No one owns outcomes. We solved this with a Production team who owns Agency, Client and Team management. The Producer owns trade-offs. When the client wants speed but the team is burning out, they decide. When elegance pushes a project out of budget, they find a solution. They have authority to kill features and reallocate budget. They're accountable for business results, not status reports. Traditional structures can't adopt this. Their economics depend on billable hours - more people, more meetings, more coordination. The Producer Model eliminates coordination overhead by design. These are opposite business models: When ownership splits, coordination cost becomes the business. When ownership consolidates, the business becomes the business. This creates compounding advantages. When one person owns outcomes across engagements, they learn what moves metrics on all sides. After five engagements, a Producer can know more about what drives results than your own team. Traditional structures reset this knowledge with every team reshuffle. This shift was not inevitable, but we are so glad we made it. Complexity is exploding. AI is commoditizing execution. What remains scarce is judgment about what and how to build. At scale complexity takes over, coordination becomes everything. The industry will split: subjective work stays with distributed ownership, measurable work moves to consolidated ownership. If you're building anything hard or complex in digital space, the choice is either/or or you could make features forever. Either accept coordination overhead and endless alignment as the cost of split and fragmented ownership. Or consolidate ownership under a Producer. We chose ownership.

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Chartbeat helps publishers strengthen content strategy and deepen reader loyalty, while Tubular Labs helps creators and brands uncover what drives momentum across social video platforms. Together, we reveal how audiences think, engage, and evolve so you can keep a pulse on the attention economy.

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If you're running a newswire - or just trying to syndicate your own content - there's one resounding reason publishers aren't posting your stories. Relevance. Every six months, we survey the Stacker Publishing Network and ask why they WOULDN'T publish a story. For the last two cycles, the no. 1 and 2 reasons were related to relevance. To their audience. And to their geography. The "oh it doesn't integrate well with my CMS" or "the workflow is janky" excuses are a cop-out. When the content is good and the content is relevant, journalists will take that extra manual step or two. So the next time you're writing a story or hoping to get a story syndicated, ask yourself one question: who is the audience and why is it relevant to them? (OK two questions...) The days of just plugging content gaps or volume for volume sake are long gone. If there isn't an answer to "why is this relevant to my audience" and "why is this relevant TODAY" that story is just getting put to the bottom of the pile, and it perpetuates that false narrative that wire content can't be engaging or high-performing. (Hint: it can 🙃 )

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Observations of founder Alex Mashrabov in creating Higgsfield AI: - rise of the app CapCut for video editing. - trend of creators getting burned out trying to create multiple videos per day. - brands having tens or hundreds of millions in advertising budget but not enough production capabilities.

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Some honest feedback for the Anthropic team: Opus 4.6 was magnificent. Opus 4.7… has been a step back in my workflow. A few things I'm noticing: Token burn is significantly higher. On the Max plan, I rarely hit usage limits before. Now I'm hitting them in ~2 hours and waiting 3 hours to get back in. Output quality requires more review cycles. I'm catching multiple errors per response, which means refactoring, re-prompting, and burning even more tokens to fix what should have been right the first time. The compounding effect is what stings... more errors... more tokens... more time spent. I've been a heavy daily user and fan of what Anthropic is building. I'm hoping 4.7 is just a blip in an otherwise strong release cadence. Anyone else seeing the same pattern?

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