01 July 2025

If Google’s ad tech empire breaks up, what happens next?

In summary

• In April, Google avoided a jury trial by reaching a settlement on monetary relief, a tactical move that curtailed the risk of a potentially damaging public courtroom process.
• Proposed remedies include divesting AdX and DFP, putting pressure on Google’s end-to-end advantage.
• Whether or not the breakup happens, the shift towards fragmentation and privacy-first measurement is already here.

US Department of Justice puts pressure on Google

In April 2025, the US Department of Justice landed a major win, convincing a US federal court that Google had been illegally dominating the digital advertising market. The fix on the table? A forced breakup, splitting Google’s ad exchange - Authorised Buyers (Formerly AdX) and publisher tech - Google Ad Manager (GAM formerly known as Doubleclick For Publishers) from its buy-side tools to reduce its end-to-end control. While the case is unfolding in the US, the impact is anything but local.

Australia’s media infrastructure is deeply tied to Google’s ad ecosystem, with few real alternatives currently in play. So, if the breakup goes ahead, or even if the pressure continues, sellers and marketers here will be facing a more open, but also more complex, ad landscape. Layer that with recent unpredictability in US politics and growing calls to rein in big tech, and it’s clear we’re heading into uncertain but important territory.

Measurement just got more complicated

The biggest shift? A potential loss of full-funnel visibility. Right now, advertisers using Google can track from the first impression, say, a user on a News Limited property, all the way to conversion on site, in store, or in-app.

Split the stack, and that connection weakens. Expect sparse conversion paths, attribution blind spots, and platform-specific discrepancies. As a response, some marketers turn to third-party or open-source tools, but these often apply different measurement logic and lack seamless integration. We’ve observed these limitations in platforms like Adobe Analytics, where building a unified view can be complex and resource-heavy. That’s why we continue to favour Google Analytics, which still offers one of the most integrated perspectives across channels.

Google’s Ads Data Hub (ADH) would also take a hit, and click-based identifiers like GCLID, which are already impacted by Apple’s Intelligent Tracking Prevention (ITP), may lose further effectiveness. Marketers will lean harder on UTM parameters, alternate solutions like WBRAID and GBRAID and aggregate identifiers, which offer less precision.

Google’s performance edge may weaken

One of Google’s biggest advantages has been how its products and user identifiers work seamlessly together, especially when it comes to campaign performance. Tools like Smart Bidding rely heavily on rich, cross-platform data shared between Google Ads, GAM, YouTube, and Google Analytics.

If the ecosystem is split, that tight feedback loop starts to unravel. Without unified signals from across Google properties, automated campaigns like Performance Max may lose their optimisation edge. That could translate to higher acquisition costs, weaker targeting, and diminished returns.

Google Ads would also feel the impact. Its deep integration with Google Ad Manager (GAM) has given marketers real-time visibility into campaign performance and conversion behaviour, as well as access to lower-cost inventory via AdSense, the Google Display Network, and now Performance Max. If GAM and related platforms are spun off, Google Ads could lose this ‘fast lane’ to campaign data and preferred inventory. That would likely mean slower insights, less precise attribution, and increased costs for advertisers, but potentially higher yields for publishers.

In a more fragmented ecosystem, marketers may find themselves juggling multiple analytics tools, or settling for less granular data, all while measured performance suffers.

AI-powered campaigns lose their secret weapon

Compounding matters further, the DOJ’s proposed remedies explicitly state that:

Google should be prohibited from utilising first-party data, i.e., data on users generated from any Google property (including but not limited to YouTube, Gmail, Google Search, Chrome, and Android), to inform AdWords’ or DV360’s bidding on, buying, or evaluation of digital advertising inventory on third-party tools and/or websites, or to preference any Google product over any competing product. Google should also be required to allow publishers to access data generated in DFP or AdX from their inventory in the same format as Google can access said data.

This would directly impact campaigns like Performance Max and Demand Gen, which rely heavily on cross-property signal sharing. Audiences targeting such as in-market segments, and affinity audiences, same. If these signals are cut off, Smart Bidding loses its edge. Campaign performance could decline, leading brands to rethink their reliance on Google’s automation.

Also on the table: competitors gaining access to years of Google’s auction logic. If that happens, the edge Google built through optimisation could be eroded overnight.

Data silos and fragmentation intensify

The digital ad ecosystem already contends with data silos and walled gardens. A Google breakup could deepen that fragmentation. As platforms diverge, marketers may face greater challenges in executing cross-channel attribution.

Google’s Ads Data Hub (ADH) could become less useful, as advertisers lose access to unified impression-to-conversion data. Meanwhile, click identifiers like GCLID replacements such as WBRIAD and GBRAID, already impacted by Apple’s ITP updates, could see further erosion.

Marketers may need to rely more heavily on aggregate identifiers like UTM parameters or analytics platform equivalents, which offer less precision and consistency across platforms. The result? More patchwork reporting and less confidence in performance comparisons.

Adopting to a reliance on alternative identity solutions such as Open ID2.0 and LiveRamp’s RampID’s will unlikely bridge the identity graph gaps with privacy and consent management impinging these solutions to the same or greater degree even before the OAIC data collection minimisation and consent guidance is widely adopted.

Programmatic opens up… but not without disruption

Google’s programmatic dominance has long hinged on the integration between DV360 (its demand-side platform), Google Ad Manager (GAM, formerly DFP) and Authorised Buyers (formerly AdX). This tight coupling allowed for dynamic allocation, improved yield for publishers, and efficient buying tools like programmatic guaranteed, all to Google’s advantage across its ads and display products, including within Google Ads features and products.

A forced divestiture would likely move AdX into open-source header bidding. While this would foster greater transparency and competition in the long term, the short-term impact could be turbulent. Publishers may need to reconfigure their tech stacks, deal with latency issues, and weather temporary drops in revenue and new challenges such as increases in fraudulent arbitrage in the media supply to buyers.

Despite the shake-up, DV360 will undoubtedly remain a major DSP, especially if it adapts quickly to support more flexible buying pathways. What’s less certain is YouTube’s future in this mix. If its inventory is ever opened up to non-Google buying platforms, it would dramatically reshape video ad buying and create a different playing field for competitors.

Louder’s recommendation

• Ensure that your data collection, consent and measurement approach is resilient to privacy, signal and technology shift.
• Utilise Post Impression and Post Click solutions (CM360, GA360 and Big Query) appropriately to measure omni-channel performance and to activate data appropriately
• Utilise DV360 and SA360 products tactically to avoid competing for the same media through multiple channels such as Google Ads Demand Gen, YouTube, Display or Video buys
• Invest in MMM readiness: Clean data and modelling fluency are becoming must-haves.
• Prioritise media quality by optimising supply paths and improving inventory quality to maximise efficiency while minimising wastage.
• Build strong data engineering foundations to integrate and unify platform, media and first-party data in a privacy-compliant, future-ready way.

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