What Google’s Removal Of Third-Party Pixels On YouTube Means For Marketers

pixelAs the United States ushered in its 45th president on Friday, Google quietly ushered in a number of updates to its ad platforms.

But it was Google’s reduction of third-party cookies and pixels on YouTube, as well as the release of a cloud-based YouTube measurement system called Google Ads Data Hub, that had industry insiders scratching their heads.

To be clear, marketers can still upload their site lists/segments and target those viewers on YouTube. They just have to use Google’s identity-based, not cookie-based, tools, including Google’s Customer Match, to make an audience match via a hashed ID, or the Ads Data Hub to measure. (Google noted it would continue to work with third-party, MRC accredited measurement vendors as it builds out the new solution).

At the same time, marketers aren’t allowed to retarget YouTube user lists on third-party sites using AdWords.

In other words, data in – not out.

Google claims the elimination of third-party cookies and pixels will improve cross-screen measurement on YouTube.

Some complaints from early testers are minor. Customer Match lists are restricted to email, one source claimed, and with so much YouTube consumption happening on mobile, “then why not allow buyers/DSPs to upload mobile ad IDs the way Facebook does?”

Others, like Jenna Sheeran, SVP of search marketing for DigitasLBi, say an identity-based system will advance cross-screen measurement, but noted an issue she foresees for buyers: “It will inhibit our ability to connect data outside of Google.”

Gerry Bavaro, SVP of enterprise solutions and digital strategy for Merkle, acknowledged the same challenge: “We predict there will be [loss in] identity, measurement and targeting [compared to] what Google offers within their environment.”

Ad buyers who want a holistic view of their campaigns will need to figure out how to connect data both within and without Google’s walls.

Although YouTube’s pixel policy change will, theoretically, allow advertisers to target users across devices using Google logged-in data (and now leverage Google search data to fine-tune that targeting), some say it will come at the expense of efficiency and transparency.

It might also fragment marketers’ horizontal attribution models.

Marketers and agencies that rely only on cookie-based DSPs and ad servers to target and measure on YouTube will lose out, said Venkat Achanta, chief data and analytics officer for Neustar and the former chief data officer of Walmart.

“To regain some of these efficiencies, marketers will need to work with independent identity providers to help them bridge and measure online and offline channels,” Achanta said.

Ric Elert, president of Conversant, shared some of Achanta’s concerns.

“Most of Google’s marketing platforms prevent independent measurement of the individual at scale,” Elert said.

“There are inherent flaws in limited measurement,” he added, “but when you are an obstacle to independent measurement entirely, you end up preventing the innovation that’s necessary to make advancements that benefit everyone in the industry, and most importantly create efficiencies for marketers.”

The Benefit

But many say the upside of Google’s people-based system outweigh the concerns.

By weaning itself from cookies, some predict Google will be able to better activate on YouTube intent data from search, behavioral data from DoubleClick, site data from Google Analytics and CRM data from Customer Match.

These developments could let Google offer better demo targeting on YouTube, “which is critical to accelerate shifts in TV budgets,” said Paul Boruta, head of ad products at YouTube branding platform, ZEFR.

A significant portion of YouTube’s audience is still anonymous. This problem, which stems from Google’s lack of a user-authenticated network like Facebook, may ease if it can infer more about an end user’s age or gender based on their intent signals (a major advantage for Facebook), Boruta predicted.

“The advertising industry is really struggling to move audience-based media strategies beyond the comfort zone of cookies, so there is clearly a market need and appetite,” noted Mike Baker, the CEO of DataXu.

These new developments with YouTube and Ads Data Hub indicate Google is “aiming to align with a limited number of tracking partners that provide value in a targeting and measurement ecosystem they’re increasingly tying back to a more deterministic identity of Google users,” Merkle’s Bavaro reiterated.

Google declined a formal interview for this report.

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  1. Google is not the only animal in the forrest with people-based marketing ambitions. Smarter marketers are realizing the movement away from cookies and towards user IDs/identity. Still, Google’s latest moves mean the ecosystem’s walls have grown in height. No user authentication today because Google is still fragmented as a platform, with no real social piece, so it will have to infer age and gender from the few partners it lets in to the new normal of Google advertising- Google Ads Data Hub.

  2. This is a massively positive step forward by Google bringing people out of the dark ages of relying on cookies. Too many companies were built during the web er, and haven’t adapted to today’s realities where IDs are more persistent and data can be transmitted S2S. The unrest here is a tell tale sign of companies that are privately struggling to keep pace with a rapidly evolving ecosystem.

  3. Yes, the cookie crumbles.

    Facebook Audience targeting has been leading the way and this a good step from Google for a combined IDGraph for identity matching – at least on Google. The major consumer shift to mobile usage has left old school data companies and platforms in the dust. Snapchat, Twitter and Facebook will continue to dominate based on their core strengths of usage and deterministic user targeting on mobile.

    Targeting users based on desktop cookies with a cross-device match is a short term measure because its not really mobile usage data. The biggest issue facing advertisers is that some identity providers use “very probabilistic” matching techniques.

    Deterministic ad targeting on mobile will win as scale increases.