Did Google Just Kill Independent Attribution?

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Martin Kihn, research vice president at Gartner.

In a muted squib released last week, Google signaled it would no longer include user IDs with log files from its industry-leading ad server.

This move was done in the name of privacy but is part of a multiyear strategy to draw up the bridges between Mountain View and the rest of the world.

Under cover of GDPR and congressional inquests, both Google and Facebook have managed to accelerate their isolationism. At a moment when they seemed under siege, they deepened their moats. Historians of chaos strategy will study their tactics for years.

But now, we have a more immediate problem. What does Google’s announcement mean for marketers?

There’s a growing consensus among practitioners I’ve asked that multitouch attribution (MTA) as we know it will never be the same.

Four Horsemen Of The Adpocalypse

As of May 25th, Google will no longer provide to European Economic Area customers:

  • DoubleClick IDs (DID) in Data Transfer reports from its ad server (DCM) and DSP (DBM)
  • Cookie IDs and user list names in Data Transfer files from its exchange (AdX)

Without these IDs, exported DCM log files can’t be used to determine true reach and frequency or to build MTA models, which are by definition user-level. MTA is not the only way to measure the true impact of ads but is theoretically the most accurate and provides by far the most detailed results.

User-level data is still accessible within Google’s Ads Data Hub (ADH) but cannot be examined at the user level and cannot be exported.

In practice, marketers who want to do accurate MTA are forced to choose one of the following:

  1. Go all-in with Google

This works if you (a) run most of your media on Google properties or networks and (b) trust Google to tell you how it’s doing. The company has access to its own log files, of course, so it can make user-level data available (with appropriate safeguards) to its own products. It is not clear whether Google’s own Attribution 360, part of its analytics suite, will have special access to data, but at the very least, it will be optimized to Google’s workflow. And avoiding non-Google IDs means you don’t have to do messy ID stitching or matching.

Downside: see (a) and (b) above.

  1. Get a Ph.D. in ADH

Google has been pushing advertisers to use Ads Data Hub since its launch last year. It works by storing encrypted user-level campaign data, including DIDs and mobile IDs in the Google cloud. Clients can upload non-Google data into a separate cloud data store. A match table is created, where possible, to map various Google IDs or cookies to client IDs or cookies. And then – after this setup – the client is allowed to perform SQL joins and queries and export aggregate analyses.

For an outside MTA provider, this scenario requires recreating their I.P. within the Google cloud, with Google’s close cooperation. An outside provider with appropriate match tables and data plus MTA experience could possibly weave together magic. But so far, only five third-party vendors are integrated with ADH. Only one of the five, C3 Metrics, is an MTA specialist.

Downside: ADH gives sophisticated marketers valuable data but does not enable fully transparent MTA. It is also an early-stage technology, with all that implies. And it is unlikely Facebook and Amazon will ever make data available there.

  1. Use a different ad server

Alternatives to DCM exist, although many marketers haven’t seen a reason to care. Sizmek and Adform offer “mini-Google” alternative ad stacks and are among ADH integration partners. Providers like Flashtalking, Smart AdServer and TruEffect offer buy-side ad servers. These competitors may see renewed interest, and smart alternates will offer incentives to switch (rumor has it, they already are).

Downside: Google’s long dominance in ad serving means its market power, talent, investment and – in some cases – its capabilities outstrip rivals. Switching ad servers is disruptive, and DCM’s smooth integrations with the rest of Google’s suite will dial up distress.

  1. Build a redundant data set using tags and pixels

In the past, enterprise MTA solutions such as Visual IQ (now part of Nielsen) gave clients an alternative: use the ad server log file (usually DCM) or implement the MTA solution’s pixel-based ID. The latter works by putting a beacon into ads and landing pages so that each impression is recorded, along with a unique ID based on a cookie. Of course, this is the same data that sits in the ad server log files, but it is accessible at the user level (via the MTA ID) and so can be used for analyses.

Large MTA vendors have been trying to wean clients off DCM log files and onto their own IDs for some time. However, many clients still rely on log-file data. As of May 25th, that option disappears. These clients will have to decide now between two different options: start over using the MTA vendor’s ID or … see choice 1., above.

Either way, they’re starting over.

Downside: Building a campaign-wide data set is complex and wearisome. Some ads can’t be pixeled, including (coincidentally) Google’s YouTube inventory and Facebook ads (which are not accessible to DCM either). In-app and offline ads also can’t be tagged. And collecting impression-level data does not solve the cross-device challenge, which is necessary for accurate MTA.

Winners And Losers

So, who wins and who loses?

Obviously, the hardest hit are non-Google MTA providers, including solution vendors and consultants.

Not all MTA vendors have a tag they deploy to create their own ID. Those that do are the larger and longer-established platforms such as Nielsen (Visual IQ), Neustar (MarketShare) and Flashtalking (Encore). Others that relied on log files face a difficult path. And still others, such as Oath’s Convertro, just gave up the stand-alone battle.

To survive, independent MTA vendors will have to focus on their omnichannel models, pairing MTA and MMM for a holistic view of online and offline media. They will need wide reach through their own data collection. And they will in effect need a unique user ID that is able to deduplicate across many data sources and devices. This requires a roster of partnerships, including cross-device data vendors, that themselves face challenges.

Also affected are agency analytics teams and MTA consultants. Without log files to analyze, they’re reduced to the less lucrative role of report jockeys. Being smart, some will refine their expertise to focus on ADH, and some will switch to different problems. But some jobs will change.

Beyond MTA, any provider that used DIDs somewhere in their workflow is affected. These include onboarders, marketing analytics and location data providers, and others.

And what about Alphabet/Google? It’s a massive media company that earns $1 in every $3 spent around the world on digital ads. Ad serving is a minuscule part of its business. Losing a few clients, even large ones, won’t have any impact on Alphabet’s life so long as they continue buying paid search and video ads. Which they will.

And what about consumers? Privacy is important and GDPR is real. Many Google partners publicly applaud this move while privately asking questions. For example:

  • Since the DID is anonymous and can’t be used for ad targeting, how does stripping it out protect privacy?
  • How does more accurate campaign measurement hurt consumers?
  • Why does every move Google makes in the name of privacy — such as removing keywords from referring URLs — help its business?

I’m not a lawyer and can’t comment, but I appreciate the questions.

Google is challenging marketers to scramble around it or accept its terms. In the end, most marketers will write down pros/cons, take a deep breath, and say, “OK, Google.”

Editor’s note: This column has been updated with more detail on Google’s policy change. 


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  1. The value of independent and unique supply pools (like adexchanges) just went up dramatically with this move. Strategically, every move Google makes shows that to win in this game you need to own supply at scale. Then you can change the rules. The not so big secret is that ad inventory is basicLg spread out between the walled gardens and “everyone else” (com score 1000 publishers = adechange inventory). The long tails is an afterthought.

    In a world where every large company is snapping up proprietary data sets (e.g. IBM and the Weather channel or MICROSOFT with LinkedIn) the same thing will happen in advertising. If you can’t snap up the walled gardens you are left with adechanges and SSPs.

    There are only a few supply pools that matter: OpenX, Index, Rubicon and Pubmatic and maybe Appnexus (though buyers would need to swollow the buy side biz as well). To see who is winning on the supply side just look at ads.txt.

    FYI: I believe OpenX has the largest adoption of ads.txt among top publishers.


  2. Random Guy 42

    DID could be used for ad targeting. I believe the service was called PLU.

  3. Interesting. Digital advertisers relying on those IDs for MTA sacrificed quality for expedience a long time ago. That cookie and anything relying on its stability is the poster-child for unreliable 3rd party tracking, i.e. bogus measurement and imprecise targeting.

    #1: I’m glad you brought up trust which hopefully advertisers are paying attention to now in the post-ANA world. Best approach is also “to verify”.

    #2: It is hard to believe that advertisers willingly uploading their data to ADS.

    #3: Well-said. Some media agencies may be conflicted about this, while others are moving their clients away from the expedient choice.

    #4: It should now become more clear: digital advertisers that chose expedience have lost the competitive advantage. Worse, they have been measuring and targeting with garbage data for years.

    My recommendation to clients is to run from reliance on this dirty bird and find point solutions where they can leverage 1st party methods/do quality control and own their own destiny.

  4. Certainly the changes Google and Facebook have been making will deeply impact those attribution techniques that rely on data capture from these systems. However as you point out, many high-end independent MTA vendors (LeadsRx, Bizible – now Marketo, VisualIQ, etc.) all have their own native pixels to do the data capture instead. This approach remains the best option for enterprise brands looking to benefit from un-biased multi-touch attribution and that need a long-term solution for optimizing ad spend.

  5. Confirming Random Guy 42’s comment. DIDs can and are used for audience/ad targeting via PLUs (Provided Lists) for many advertisers. Segments comprised of DIDs are queried/clubbed, then exported to a buying platform for deployment.

  6. Great POV Marty! So glad to see someone bring these issues to light. It definitely feels like there’s a groundswell of support for open, independent measurement (completely separate from media). As Dominic pointed out above, what’s been historically easy has not be effective. As the Duopoly (+ Amazon) continue to consolidate power, the need for an independent source of truth will become even greater.

  7. Nico Neumann

    Attribution modelling was a great concept years ago, but it always lacked sufficient data (TV, radio, OOH) and key variables got lost even for digital long before Google’s move (in particular when Facebook removed cookie data).
    Fortunately, there is a solution that always works – the most accurate way to measure at least short-term effects: AB tests aka the good old experiment, foundation of science.

  8. The removal of DoubleClick IDs represents a major problem for companies who are reliant on Google DCM. The inability for marketers to link up their offline and other customer data means they will get, at best, a very partial view of the customer journey, which is a backwards step in terms of today’s marketing.

    But multi channel attribution is still alive and well, through the use of other tools. There are solutions that track the complete customer journey, allowing users to match their digital activity at an individual data with data from their own first party databases, including offline transactions. The best are simple to use, transparent, and GDPR compliant.

    GDPR represents a number of challenges, but it should also be treated as an opportunity to do things differently – and even better.