U.S. digital advertising revenue reached $294.6 billion in 2025, a 13.9% increase on the prior year, according to the IAB/PwC Internet Advertising Revenue Report. Measurement has not kept pace. In its October 2026 release on cross-channel measurement, the IAB cites research showing that 60% to 75% of marketers say advanced measurement falls short on dimensions such as rigor, timeliness, trust and efficiency. This article covers where spend is moving, what budget and AI data say about readiness, and how measurement methods are changing.
Spend is concentrating in channels that report their own results
The IAB/PwC report puts social advertising at $117.7 billion in 2025, up 32.6% and equal to 40% of U.S. digital ad revenue. Search reached $114.2 billion (IAB’s category definitions overlap), but it grew only 11%, down from 15.9% in 2024. Commerce media rose 18.0% to $63.4 billion, programmatic rose 20.5% to $162.4 billion, and creator advertising reached $37 billion, with a projected $44 billion in 2026.
IAB chief executive David Cohen attributes part of the shift to marketers placing money where spend can be tied to business outcomes. The report adds that the ten largest global media companies hold most internet ad revenue, helped by proprietary measurement infrastructure. For analytics teams, the consequence is direct: the biggest and fastest-growing budgets sit in environments that supply their own attribution. One caveat on the source itself: PwC compiles the figures from company-reported data and does not audit them.
Flat budgets and an AI readiness gap
Gartner’s 2026 CMO Spend Survey was fielded from January to March 2026 among 401 marketing leaders, most at companies with more than $1 billion in revenue. Budgets averaged 7.8% of revenue, up from 7.7% in 2025, and 56% of CMOs said they lack the budget to deliver their 2026 strategy.
CMOs allocate an average of 15.3% of marketing budgets to AI, and 70% call becoming an AI leader a critical 2026 goal. Only 30% report mature AI readiness. Those mature organisations put 21.3% of budget into AI and average budgets of 8.9% of revenue. Gartner’s Ewan McIntyre warns that CMOs risk buying AI tools faster than they build the data foundations, processes, governance and talent needed to scale them. Measurement pipelines are part of that foundation, so one reading of the data is that analytics maturity is a precondition for AI returns, not a parallel project.
What market-size estimates show
NextMSC’s Marketing Analytics Market report values the market at USD 8.6 billion in 2025 and USD 9.8 billion in 2026, and projects USD 34.2 billion by 2035, a 14.8% CAGR over 2026 to 2035. Campaign and attribution analytics is the largest solution family at USD 1.72 billion in 2025, while web and app analytics grows fastest at 16.6% a year. Cloud accounts for about 68% of 2025 revenue (USD 5.85 billion), yet hybrid deployment grows fastest at 17.0%, which the report ties to regulated industries keeping sensitive customer data on-premises while using cloud tools for activation.
Scope matters when comparing figures like these. The estimate covers software, data services and managed measurement worldwide, so it is not a like-for-like comparison with the U.S. ad revenue numbers above. Within that scope, attribution is the largest single solution family, ahead of web and app analytics at USD 1.38 billion in 2025.
What happened to the cookie deadline
Many measurement roadmaps were built around Chrome removing third-party cookies. That did not happen. In April 2025, Google said it would keep its current approach to cookie choice in Chrome and not introduce a standalone prompt. On October 17, 2025, it went further and retired most Privacy Sandbox technologies, citing low adoption, including the Attribution Reporting API.
The pressure on measurement now comes from other directions: privacy regulation, consent requirements, data held inside large platforms, and AI search surfaces where click-based attribution is hard to apply. Teams that deferred first-party data work while waiting for a Chrome deadline have lost their reference date, but not the underlying problem.
Marketing mix modeling moves into the default stack
Google opened its Meridian marketing mix model globally in January 2025 and added a no-code Scenario Planner in February 2026. On May 20, 2026, at Google Marketing Live, it announced that Meridian is being integrated into Google Analytics 360, alongside Qualified Future Conversions, a Gemini-based metric now in restricted pilot. PPC Land reports that Google has not published how those predictive signals would feed back into Meridian, which raises circularity questions because both draw on Google Ads data. It also relays Google’s figure that AI Mode has passed 1 billion monthly users, a surface where last-click attribution does not work as it does on a standard results page.
Adoption inside organisations trails availability. An EMARKETER and Rakuten survey found that only 11.8% of U.S. marketers feed MMM insights into live campaigns weekly and 17.3% monthly. The largest group, 26.4%, updates quarterly, 20% do so ad hoc, and 20.9% do not use MMM at all.
MMM also has channel limits. In an April 2026 IAB and Instacart white paper, the authors argued that MMM is structurally ill-suited to retail media because spend is always on and commerce data is fragmented. They pointed to closed-loop, transaction-level measurement as the better fit, and noted IAB’s forecast of 12.1% commerce media growth in 2026.
When methods disagree
On October 20, 2026, IAB opened public comment, running through November 4, on a Cross-Channel Measurement Decision Guide developed under Project Eidos. The guide starts with the business decision and works back to the method, instead of starting from whatever metrics are available. It addresses cases where MMM, incrementality testing and attribution produce conflicting results for the same campaign. IAB’s own example is a channel that reports a strong attributed ROAS which an incrementality test does not support.
The guide is still a draft, so its sequence may change. The framing is usable now: when methods disagree, the disagreement is a finding to investigate, not noise to average away.
Implications for B2B teams
Four points follow from the data above. First, match model refresh to the decision cycle. If quarterly is the most common update rhythm, a weekly MMM output has nothing to inform until the next planning window. Second, treat platform-reported ROAS in the fastest-growing channels, social, video and commerce media, as a claim to test with incrementality designs, because those platforms also supply the measurement. Third, fund data foundations before AI tooling, since Gartner’s readiness gap shows spend running ahead of governance and process. Fourth, retire any roadmap whose critical path runs through a Chrome cookie cutoff.
Two dates will show how this settles: IAB’s comment window closes on November 4, 2026, and Google’s Qualified Future Conversions beta is planned for later in 2026. Both bear on whether the industry converges on a shared way to resolve conflicting results.