Consolidation vs. Transparency: Two Tensions Shaping Major Ad Platforms & How Brands are Responding

An abbreviated version of this article originally ran in MarTech, Oct 2024, read here.

In recent years, Big Tech has dominated the news, with Meta, Google, and Amazon asserting control over the digital media landscape and facing broader scrutiny from consumers and regulators alike. Underneath the headlines that break-through for the general public, a subtle but significant shift has taken place—one that is profoundly reshaping the way brands engage with advertising platforms: the tension between consolidation and transparency.

Several factors have driven the rise in consolidation. Machine learning and artificial intelligence (AI) optimization have significantly improved, enabling platforms to automate ad placements and deliver performance at scale with minimal input from marketers. Simultaneously, these platforms are working to safeguard their first-party data, especially as consumer privacy concerns rise and regulatory pressures mount. With growing restrictions on third-party data and tracking, tech giants have responded by centralizing control over their ad ecosystems.

At the same time, demands for transparency have escalated, fueled by a number of converging market dynamics. First, overall digital user growth has plateaued, increasing ‌competition for every media dollar spent. Second, rising challengers in digital media, such as retail media networks and connected TV (CTV), have added scale and introduced more alternatives for brands to diversify their spend. Finally, performance media dollars have become fiercely contested as brands look to optimize their returns across a growing array of channels, which includes emerging platforms beyond the traditional big players. All these factors are pushing ad giants to demonstrate clear value and offer advertisers additional brand controls. 

These opposing forces—consolidation for control and efficiency, and rising demands for transparency in a competitive, crowded digital market—are reshaping the relationships between advertisers and platforms. Campaign structures like Google's Performance Max (PMax), Meta's Advantage+ Shopping, Amazon’s Performance+, and TikTok’s Smart Performance Campaigns promise efficiency through automation and AI. However, the accompanying lack of transparency leaves brands questioning the effectiveness of these tools and their ability to make informed decisions.

Google’s Performance Max (PMax), launched in late 2021, epitomizes the consolidation trend. Advertisers launch a campaign with little control over where ads will appear, what message will be delivered, and who will see it. AI optimizes for goals set by the advertiser but obscures many of the levers marketers traditionally controlled, such as audience targeting or channel selection.

For many brands, this shift to "black box" advertising feels restrictive. Performance Max, for instance, optimizes across all Google-owned media, including unexpected placements like Gmail inboxes—hardly the personal, curated touch marketers often strive to achieve. In addition, Google has removed some access to auction insights, complicating advertiser visibility into competitive ad buying dynamics. Despite these challenges, Performance Max has been a necessary tool for those looking to tap into Google's unmatched reach.

Meta followed suit in 2022 with its Advantage+ Shopping Campaigns. Faced with increasing privacy constraints, particularly from Apple’s mobile changes, Meta overhauled its ad algorithm. Marketers provide inputs like goals, budgets, and product feeds, and Advantage+ takes over from there. While brands appreciated improvements in performance, the lack of transparency mirrored the struggles seen with Google’s PMax campaigns.

Amazon's Performance+ —encompassing Sponsored Products, Sponsored Brands, and Sponsored Display— launched in 2024 offers a similar level of consolidation. These campaigns leverage Amazon's massive shopper data and AI to optimize placements across its platform with minimal direct control from advertisers. Revealing this industry tension between consolidation and transparency, Amazon Ads attempted to distance itself from other consolidated campaign types by launching these machine learning-driven upgrades within its existing DSP and touting no changes to reporting or attribution.

TikTok, with its Smart Performance Campaigns, also entered this space by automating optimization across its short-form video platform, offering advertisers rapid scale with limited input.

With the rising trend of consolidation, many brands have reacted with three key strategies.

Brands have repeatedly called for more visibility into campaign drivers and performance metrics. The lack of data makes it difficult to analyze what is driving success or failure, leaving many feeling that their investments are being managed by inscrutable algorithms. Direct feedback to platforms has been an ongoing effort as brands push for more detailed reporting and greater control.

Rather than remain fully dependent on the perceived "black box" of Google, Meta, Amazon, and TikTok, many brands have diversified their media spend. This trend has been accelerated by the rise of alternative platforms, such as streaming video and CTV, which offer both brand reach and media that's increasingly accountable to business outcomes. Much has been written about the flow of ad dollars from Linear to CTV, but at PMG, we’ve also seen digital performance budgets diversifying to include CTV. Additionally, Amazon’s growth as an advertising giant has helped expand options beyond the historical digital duopoly of Google and Meta.

Expanding platforms and formats in retail media and digital out-of-home (DOOH) also provide more avenues for advertisers to explore—with uniquely accountable placements. These options have allowed brands to shift away from pure dependence on consolidated ad platforms and instead build more varied media strategies.

With less transparency coming from ad platforms, brands have had to strengthen their own measurement capabilities. The adoption of sophisticated media mix modeling (MMM), always-on experimentation, and incremental testing has become critical. Brands are building their own "source of truth" to measure the effectiveness of their media investments independently, creating a counterbalance to the performance metrics reported by the platforms.

By developing robust internal measurement capabilities, brands are able to drive accountability, ensuring that platforms are delivering on the business outcomes they claim to influence.