Tim Vanderhook

@oliviaakory Imagine what their revenue would have been if they were all in the office…

In the remote v office debate, no one talking about how Grüns just proved you can build a unicorn fully remote.

@cvanderhook youtu.be/8Az8kp2NnuU?si…

Viant $DSP jumps 16% after smashing Q4 expectations! Revenue up 22% to $110M, adj. EBITDA surges 45% to $25M. Real AI-powered ad tech is winning big. 🚀 #ViantTech #EarningsBeat

@aakashgupta You just described how Google is a Monopoly and the quality of the product doesn’t matter when you monopolized distribution! Turns out it is impossible to beat a monopoly!!

Sam Altman just admitted defeat in an image generation war he didn’t know he was fighting. GPT Image 1.5 was scheduled for January. OpenAI pulled it forward by a full month because their internal dashboards showed something terrifying: Gemini’s weekly download share climbed from 29% to 33% in a single week. That’s the kind of trajectory that compounds into market position collapse. The timing tells you everything. December 1st: Altman sends “code red” memo. December 11th: GPT-5.2 ships. December 16th: GPT Image 1.5 ships. Three major releases in 15 days after months of nothing. This isn’t a product roadmap. This is a company in crisis mode, burning through its bench depth to stop the bleeding. Here’s what most people don’t understand about the image generation market: it’s not about quality. It never was. Nano Banana went viral in September because people could share their AI-generated Thanksgiving dinner with fake celebrity guests. They could turn their pets into Ghibli characters. Google turned image generation from a utility into a social behavior. OpenAI had no answer for three months. Look at the engagement data. Gemini users now spend 120% more time in the app compared to March. ChatGPT users saw time spent decline 10% since July. The product works fine. The distribution is the problem. Google has something OpenAI can never replicate: Android. Twice as many US users access Gemini directly through the operating system versus downloading the standalone app. Billions of devices with AI image generation baked into the home screen. OpenAI has to convince people to download an app. Google just turns on a feature. The LMArena benchmarks show GPT Image 1.5 leading text-to-image by 29 points. Sounds impressive until you see image editing: it’s ahead of Nano Banana Pro by exactly 3 points. In blind user testing, the gap between these models is essentially noise. OpenAI won on a technicality while Google won on cultural adoption. The 20% API price cut reveals the strategy shift. OpenAI knows it can’t win the consumer market on quality alone, so it’s pivoting hard to enterprise. The pitch: better logo preservation, consistent brand elements across edits, full product catalog generation from a single source image. This is a “please buy our enterprise tier” play, not a consumer play. The financial math gets brutal from here. OpenAI is burning $22 billion this year against $13 billion in revenue. $1.69 spent for every $1 earned. Cumulative cash burn through 2029: $115 billion. Revenue needed to justify this: $200 billion by 2030. The entire business model assumes ChatGPT dominance persists for five more years. Sensor Tower data says market share dropped 3 points in four months. The Disney deal tells you where OpenAI sees the escape hatch. $1 billion equity investment in exchange for 200+ character licenses starting in 2026. OpenAI gets exclusive rights to generate Baby Yoda images. Disney gets shares in a company valued at $500 billion on the assumption it remains the market leader. Both parties are betting that licensed IP becomes the moat around AI image generation. Google doesn’t need licensing deals to grow. It has distribution. It has Android. It has Search. It has YouTube integration. It has Workspace. OpenAI has to buy cultural relevance one IP deal at a time while Google distributes to billions for free. This release isn’t OpenAI maintaining leadership. This is OpenAI discovering that first-mover advantage has a half-life, and theirs is decaying faster than their burn rate can sustain. The real question isn’t whether GPT Image 1.5 is technically superior. On specific benchmarks, it probably is. The question is whether technical superiority matters when your competitor’s distribution advantage grows by 30% quarter-over-quarter while yours grows by 6%. At $22 billion in annual spend, OpenAI is paying roughly $60 million per day to find out.

@jacob_posel @TaylorHoliday I still can’t figure out what would be different or unique based on what you mentioned above. Is this a CRM only for the social channel? Doesn’t seem possible via the Open Web with the descriptions you gave.

Well you know the kind of conversations that happen during a sales process, and you know the kind of services we deliver, so it doesn’t take much imagination to draw the dots. I don’t know where blood type comes in. Experiences, preferences, goals, what’s worked, what hasn’t, brand dna all are things you might discuss that are important.

We built a CRM It tracks the entire sales journey (and beyond). Every conversation, every document. Why? Because a customers expectations and needs are essential context for service delivery. When a deal is closed, they become a client in the agency platform. That means every person who is responsible for execution truly understands the entire customer context. What was promised, why it matters, and how success is defined. Nothing lost through misinterpretation or disconnected handoffs. Every data point anchored by expected outcomes. Quantitative married to qualitative. Sales and service, inextricably linked. This is what a true AI native business looks like.

@AdtechGod It’s just ‘Artificial’

Has anyone figured out what Apple Intelligence is yet?

Here is why: one consumer visiting Google and searching used to mean 1 to 2 ‘clicks’ to per search. NOW, one prompt in an LLM produces ‘25 simultaneous search clicks’ and thus everyone is seeing inflated numbers but bots make it easy. Same volume from a consumer perspective but the LLM executes 25 times the search referrals. Really quite simple.

@neilpatel Wild that AI traffic is already the #1 source at 9.2%. Makes me think I’m on the right track with my project. The compounding effect here is going to be huge.

Here are the top converting digital marketing channels. You know many of them, but the highest-converting ones are ignored by many companies. They may not drive the volume, but every bit adds up.

@AdtechGod I want a robot SO SO BAD! Mainly for two items: washing dishes and accessing ViantAI without a keyboard. Can’t wait for @Tesla_Optimus

It’s crazy to think that my grandchildren may be in a relationship with a robot.

What I think you should do is stick with your current setup for now. Side by side you should run an additional test using us. Load in whatever data you want. I will pay for half the media up to 50k and match any budget up to that amount. Then you can look at the results side by side. You should only allow your current setup to use retargeting and exclude it from Viant. That way, we have one hand tied behind our back against your current provider. Viant will demolish whatever setup you have in place. Our data feeding the models will outperform whatever you are doing. Would you stop having FOFO and let’s go! How many ad platforms have offered you $50k to test?

I find it really cool you remember our conversation from a few months ago, founder mode to the fullest 👍🏼 . To clarify, the horror story I mentioned was not about me but one of my incoming clients, and it is a recurring issue I have heard before. Regarding our services, we do offer a managed service solution (you caught me 😊 ) to activate our data, so we are not JUST curators. But, we do not buy out of The Trade Desk, we have our own bidder. Our curation works really well with SSP integration. We can push our data to any DSP without sacrificing our ability to adapt to their supported features, and SSPs pass us bid requests in real time, which we process in milliseconds in our system. Within that millisecond timeframe we score each request against our clients’ custom models, and if it is a strong match, we assign a PMP ID and push the bid request to the client’s line item. Our models internally are updated every five minutes to ensure maximum freshness. On the DSP side, our managed service requires bidder integration for the same functionality we get on the SSP side, which many DSPs do not support. I am not sure if Viant does, but I think what you are building is definitely cool, and there is definite potential for synergy. Our solution is really built for incrementality and I know Viant is all about driving real outcomes. Integrating our custom data solution into Viant’s DSP could create a powerful offering. That’s why I said before if we had the potential to possibly integrate as a data provider in Viant, I think together we could do a lot of good.

Public service announcement, as I’ve seen others get burned: never enable auto-accept deals in your DSP. Bad actors may send you “deals” to piggyback on your media spend if you don’t regularly review the deals you buy against.

@chenkoposts @EricTilbury_RTB I don’t understand…. You don’t think the data is good or real?

TradeDesk has been releasing cool tool after cool tool lately. A lot of their tools being released make it so the average buyer can easily point their buys in the correct direction. There are very many ways a buyer can mess things up, simple buttons to fix this is a very good thing. Platform costs are totally worth it if your buy reaches humans.

@EricTilbury_RTB @chenkoposts Also - congrats on your Q1!

@TimVHook @chenkoposts The test is good to keep in mind! I’m talking about us being a data provider in Viant. But I also don’t have a seat in trade desk just a fan of their products. Inuvo is a data company.

@EricTilbury_RTB @chenkoposts Would love to discuss integrating you into the DSP but is your data cookie based or people-based?

@chenkoposts @EricTilbury_RTB He actually has some of the best bot detection in the industry… social posts are irrelevant to the data. I like to know the truth but a lot of AdTech likes to pay people to lie to them. I like to pay to *actually* know what was real.

@EricTilbury_RTB @chenkoposts We’re not a data provider. But I would love to run head-to-head tests of Viant vs TTD if you’ll publish the results on X and LI? If we lose, I’ll pay your bill on our side. TTD Customers = FOFO

@chenkoposts @TimVHook I would love to work with viant actually. Possibly a data provider?

@EricTilbury_RTB To be slightly more specific…. The NFL on CTV is the Ferrari! There are a lot of minivans in CTV too.

CTV is the Ferrari of advertising channels.

@AdtechGod @BradAT Ha!!

@BradAT Now you know my real identity.

Things I'm thankful for on this Thanksgiving holiday.

@BradAT Let’s go!!!

@antoniogm Brad Parscale is just another snake oil salesman in AdTech like so many others. Anyone with experience knew it was vaporware immediately…

Cambridge Analytica, and I say this as someone who helped build the ads targeting system in question and was deposed in the resulting lawsuit, was an immense mountain of bullshit that was duly exploited by everyone, from journalists to politicians, for their own ignoble ends.

CTV drives organic brand search like no other channel—and it’s both measurable and attributable. By matching CTV exposure data with site visitor signals, you can pinpoint users who arrived via organic search post-CTV. Yet, many advertisers stick with Google products. They get what they deserve.

@Ivan778899000 Google almost always gets in the way. Same as the App Store for apps. Which is an issue in the click attribution system as it zeroes any value of coming from CTV. You can verify it by seeing the bumps in branded search traffic.

CTV’s biggest challenge isn’t measurement it’s attribution. Existing attribution methods are hostile to CTV’s exposition based performance. QR Codes aren’t and will never be the answer. The answer likely is in assessing incrementality. Which very few marketers accurately assess and where there is no existing standard methodology. Standard as is commonly accepted. But it will happen. And it will shake the advertising industry far beyond CTV. Bad players (and/or the bad operators) won’t be able to hide behind last click attribution.