YouTube is giving brands something they\u2019ve been asking for. The question is whether getting it makes them want something it can\u2019t yet provide.\u00a0<\/p>\n
The platform\u2019s Creator Partnerships API, announced at the NewFronts earlier this sping, opens up creator performance data to a select group of third-party ad tech companies for the first time \u2013 who watches what, for how long and what that means for an advertiser trying to decide where to put money. It is not, however, an open door. Creators can opt out of being included entirely, and brands must actively opt in. What YouTube is building, in other words, is controlled infrastructure, not a data free-for all.\u00a0<\/p>\n
But better data has a way of raising harder questions. The more precisely advertisers can measure creator audiences, the sooner they will ask what YouTube still cannot answer: can a creator actually sell something? <\/p>\n
TikTok Shop comes closest \u2013 someone watches, taps, buys and never leaves, with attribution following the whole chain. But even that is less solved than it appears. TikTok Shop sits largely disconnected from TikTok\u2019s broader ad stack. Instagram has tried to solve the same problem four times. YouTube Shopping mostly redirects users offsite, which is where the thread snaps. Suffice to say, the full loop from creator content to verified purchase remains unsolved across every major platform.\u00a0<\/p>\n
YouTube\u2019s version is just the most visible, because of how dominant the platform is everywhere else. It commands more U.S. TV watch-time than any other media company \u2014 12.5% of the total, per Nielsen\u2019s most recent data. And yet only 37% of advertisers cite it among their top channels for influencer marketing, against 57% for Instagram and 52% for TikTok, according to influencer Marketing Hub. The audience has always been there. The infrastructure to monetize it hasn\u2019t.<\/p>\n
\u201cThey [YouTube] spent the last five years talking about TV share shift,\u201d said Oli Marlow-Thomas, chief innovation officer at Smartly.\u00a0 \u201cThey missed the real opportunity, which is the consumer now living their whole life in these environments \u2014 shopping, searching, experiencing social and entertainment in one place.\u201d<\/p>\n
It\u2019s fair to say YouTube is intent on making up for lost time. Creator content is now the most effective vehicle for pulling advertising dollars into YouTube\u2019s paid ecosystem, and data is the thing standing between advertisers wanting to spend and advertisers actually spending. Better performance data helps brands identify what\u2019s working; once they know what\u2019s working, the next step is to boost it.<\/p>\n
\u201cWhat they [YouTube] have not done yet is connect the powerhouse that is Google on the outside to the creator ecosystem being built on YouTube,\u201d said Pierre-Lo\u00efc Assayag, co-founder and CEO of\u00a0 Traackr, an AI-powered influencer marketing intelligence platform. They are playing catch-up. But no one can forget that the company playing catch-up is the largest animal in the jungle.\u201d<\/p>\n
Which is a neat way of saying that the gap is more of a sequencing problem than a self-inflicted one. To understand why, it helps to understand what broke the old model. For years, brands selecting a YouTube creator relied on channel-level audience data \u2014 follower demographics, rough geographic breakdowns and average views. It was imprecise but workable. Then platform algorithms changed. Today, more than 80% of people who see a piece of creator content are not a follower or subscriber of that channel. The audience data brands had been using to make decisions bore almost no relation to the audience actually seeing the content.\u00a0<\/p>\n
\u201cIt was almost blind,\u201d said Tim Sovay, chief partnerships officer at CreatorIQ, one of the handful of companies given early API access. \u201cThe data that was being provided on the front end didn\u2019t matter anymore.\u201d<\/p>\n
The API \u2013 or rather the data it facilitates \u2013 changes that. It tells advertisers which creators move audiences. The moment they know that, they\u2019ll want to know which creators move product. The API, in other words, is a precondition for creator commerce on YouTube.<\/p>\n
\u201cYou can\u2019t get data you don\u2019t have,\u201d said Scott Sutton, CEO of Later, a social media management and influencer marketing platform also plugged into the API. \u201cYou first have to develop the rails and the mechanics, and then it enables greater transparency into outcomes.\u201d<\/p>\n
What makes this significant in the near term, though, is less about what it eventually unlocks and more about what it changes right now.\u00a0<\/p>\n
For the first time, creator inventory on YouTube can be evaluated and planned with the same data rigour applied to programmatic media \u2013 audience composition, engagement rates, content performance signals flowing into the same systems brands already use to make media decisions. Creators start to look less like a bespoke sponsorship play and more like a plannable line on a media budget. <\/p>\n
That process has, until now, been surprisingly manual. Each platform, including Instagram and TikTok, has preserved largely human-driven workflows for creator boosting even as the rest of digital advertising automated around them. The API accelerates the move toward programmatic, connecting media spend to creator selection in the same automated, data-driven way brands buy everything else.\u00a0<\/p>\n
That matters because it changes who makes the call. Creator marketing has historically lived in influencer teams, bought on gut feel. On the flip side, programmatic-style data pulls it toward the media desk, where decisions are made on CPMs and measurable return.\u00a0<\/p>\n
\u00a0\u201cThe data from the API allows you to underwrite a creator the same way you\u2019d underwrite any other media placement,\u201d said Christian Dankl, CEO of audience intelligence platform Precisify. \u201cThat changes the conversation entirely.\u201d\u00a0<\/p>\n
Or rather, it changes it \u2013 but it doesn\u2019t end it.\u00a0<\/p>\n
YouTube\u2019s move is being read less as evidence that it has figured out the creator economy and more as confirmation that it knows it has to. The advertisers closest to the API are under no illusions about what comes next. They\u2019ll take the data, integrate it and come back asking for more \u2014 the metadata, the content signals and, eventually, the commerce attribution.<\/p>\n
\u00a0\u201cThe top three things our biggest customers ask for is more insights, more insights and more insights,\u201d said Sovay. \u201cAnd then there\u2019s everything else.\u201d <\/p>\n
YouTube has answered the first ask. The rest of the list is waiting.<\/p>\n
YouTube reaches 83% of Gen Z and 78% of millennials in the U.S., according to media intelligence firm Precisify. That makes it the rare platform that doesn\u2019t force advertisers to choose between the two. But according to media analyst Evan Shapiro that reach number belies a bigger story. Digiday spoke with Shapiro, who has mapped the media habits of both cohorts extensively, about why the metrics advertisers are still buying on are the wrong ones and what the YouTube on TV shift actually means for how marketers should be spending.\u00a0<\/p>\n
Shapiro on why outcomes matter more than reach<\/strong><\/p>\n \u201cReach is a vanity metric of a past era. Action and outcomes are going to become much more the measurement going forward. Engagement is now a much more important metric than reach. Scale for scale\u2019s sake is the cargo shorts of business models. Affinity, fandom \u2014 those are now truly the measurements that matter.<\/p>\n The good thing about social media, and YouTube being at the centre of that, is that they are much more demonstrable in their outcome-based measurement. Last-touch attribution seems to be much more provable on platforms like YouTube, Meta and TikTok. The measurement on connected television is just not great. When you look at the whole kerfuffle with Nielsen and MRC of late, you can see why that measurement isn\u2019t seen as reliable.\u201d<\/p>\n Shapiro on the platform-as-TV-screen shift<\/strong><\/p>\n \u201cYouTube is the only platform that goes back and forth from phone to television. More and more people are watching YouTube on their television, which is making it \u2014 based on research I\u2019ve seen \u2014 more and more of a shared experience, as opposed to a solitary one.<\/p>\n But the sweet spot for YouTube on television is actually 25 to 55. I don\u2019t think it\u2019s teenagers \u2014 teenagers tend to watch much more content on their phones. Once you hit 25, 26, suddenly people are watching far more on the big screen. I did a study with Common Sense where 88% of kids said they prefer YouTube to any other form of television, so there\u2019s also a co-viewing, digital babysitter dynamic running alongside. The CTV creator narrative is probably a trajectory call more than a current reality.\u201d<\/p>\n Shapiro on why the algorithm is the audience<\/strong><\/p>\n \u201cPeople talk about the algorithm as this nameless, faceless blob that floats in the digital world, unfettered and uncontrolled. It\u2019s not. It\u2019s the behaviour of the people of Earth. That\u2019s actually what the algorithm is.<\/p>\n When you start from that premise \u2014 that all media is now completely controlled by the user base \u2014 the ones who will win are the fans. They now get everything they want, whenever they want it, wherever they want it, and they choose the payment structure on a minute-by-minute basis with swipes of their thumbs. They are in complete control. The platforms and brands who disregard that are the ones who will lose. The ones who agree to that relationship are the ones who win.\u201d<\/p>\n 1 billion<\/a>: The internal target number of weekly active users for ChatGPT which OpenAI missed by the end of last year.<\/p>\n $19.8 billion<\/a>: Total CapEx Meta spent on AI and data centers in Q1 2026.<\/p>\n $180 to $190 billion<\/a>: Total projected AI \/ infrastructure CapEx Alphabet expects to spend this year.<\/p>\n $37 billion<\/a>: Total annual recurring revenue of Microsoft\u2019s AI business, according to its recent company earnings report<\/p>\n The week that Meta employees became training data YouTubers are coming to a movie theater near you<\/a><\/p>\n Movie theaters are seeing a modest comeback, and some YouTubers are capitalizing by releasing films directly in cinemas \u2013 using their built-in audiences to drive ticket sales without traditional marketing, per Scalable.<\/p>\n What is Meta\u2019s China exposure?<\/a><\/p>\n Meta doesn\u2019t operate in China but still earns significant revenue from Chinese advertisers targeting overseas users. That dependence is lucrative but risky, as geopolitical or regulatory shifts could quickly disrupt a revenue stream Meta doesn\u2019t directly control, per Mobile Dev Demo.<\/p>\n OpenAI Misses Key Revenue, User Targets in High-Stakes Sprint Toward IPO<\/a><\/p>\n OpenAI has missed internal targets for both revenue and user growth\u2014failing to hit goals like 1 billion weekly ChatGPT users\u2014raising concerns about whether its business can sustain massive spending on AI infrastructure as it eyes an IPO, according to The Wall Street Journal.<\/p>\n X upgrades its ad platform in long overdue overhaul<\/a><\/p>\n X has launched what it calls the biggest overhaul of its ad platform to date, introducing AI-driven updates to improve ad retrieval, ranking, and contextual targeting, with a full rollout expected later this year.\u00a0<\/p>\n Meta opens its ad ecosystem to third-party AI tools<\/a><\/p>\n Meta is opening its advertising ecosystem to third-party AI tools through new \u201cAI connectors,\u201d allowing advertisers to plug in tools like ChatGPT or Claude to create and manage campaigns without leaving their existing workflows.<\/p>\n Uncertainty is the real cost of the Middle East war for advertisers<\/a><\/p>\n The Middle East conflict isn\u2019t causing an immediate collapse in ad spending, but it is creating sustained uncertainty that\u2019s making it harder for marketers to plan and commit budgets.<\/p>\nNumbers to know<\/strong><\/h2>\n
What we\u2019re reading<\/strong><\/h2>\n
<\/a>Meta is increasingly using employee activity data to train AI systems that can perform knowledge work. Alongside layoffs, this reflects a shift toward a future where humans supervise AI \u2013 raising concerns workers may be training tools that could replace them, according to Platformer.<\/p>\nWhat we\u2019ve covered<\/strong><\/h2>\n