Today's leading companies are implementing AI-backed technology powered by rich first-party data to better understand their campaign’s performance and more accurately predict the impact of future media investments.
CMOs face pressure to link ad spend with business results, but legacy measurement tools lack trust. Leading firms use AI-powered solutions, combining Marketing Mix Models , incrementality testing, and attribution analysis for a comprehensive view.
While adoption of these tools individually is high, concurrent use is low, hindering trust. AI's potential is recognized, but measurement lags in AI maturity. Unified first-party data is crucial for AI effectiveness. An integrated approach with AI and robust data is key for accurate measurement and ROI.Written by Kamal Janardhan, Senior Director, Product Management, Google CMOs and CROs are in a tough position. Not only is there1 increasing pressure to connect ad budgets to business outcomes, but analytics professionals—the people relied upon to make the numbers work— are looking for better performance from their legacy measurement technology. In fact, in a recent study from BCG and Google, we found that only 40% of global organizations completely trust the performance of their current measurement solutions. To address this, leading companies are implementing AI-backed technology powered by rich first-party data to better understand their campaign’s performance, run experiments, and more accurately predict the impact of future media investments. What solution can do all of this? It’s actually a combination of three tools. Marketing Mix Models for a macro view of past and future performance, incrementality testing to identify best-performing channels and tactics through experimentation, and attribution analysis to optimize budget allocation. When used together, these tools provide a comprehensive and trusted understanding of marketing effectiveness, breaking down silos and enabling data-driven growth.To get a clear picture of their media’s performance, marketers must embrace an integrated measurement toolkit with three key parts: MMMs, incrementality testing, and attribution. Each of these approaches are widely used by data teams across the globe on their own — our survey showed 79% adoption for MMMs, 86% for incrementality testing, and 81% for attribution. But the real magic happens, when all three are used together. Today, only 46% of organizations use all three of these tools concurrently. We believe this number plays a major role in low trust levels among analytics professionals. To fully address the top six characteristics of a modern measurement approach, a three-step measurement process is essential.When you overlay the strengths of each measurement approach, you see that each tool provides a critical part of the complete picture of marketing performance. They each offer distinct strengths across critical dimensions like causality, actionability, and recency. And when you integrate different insights in strategic ways — like adding incrementality experiment results to your MMM, you are able to leverage their complementary capabilities, enabling cross-verification of results and building a complete and trustworthy understanding of your marketing's impact.Marketers recognize the potential of AI to address common challenges in measurement. Globally, 72% of analytics professionals “frequently leverage AI” within their measurement efforts, signalling that the industry is beginning to view traditional methods as insufficient on their own. But even amid AI enthusiasm, a concerning reality is taking shape: when we benchmark AI maturity across marketing functions — or how advanced people feel their AI usage is — measurement consistently lags. While media and personalization, creative production, and even operational processes show higher levels of perceived AI acumen, only 9% of global companies consider their AI capabilities “leading” when it comes to measurement. This contrast reveals a significant gap between AI adoption and mastery for measurement related use cases.Companies paving the way for AI-powered measurement are giving us deeper visibility into how these tools can drive sharp, future-forward strategies. According to BCG, leading organizations leverage AI over twice as much as competitors, with 76% of these leaders currently using AI to generate actionable learnings from their campaigns. What’s more, nearly half of leading users are already using AI powered features like predictive modeling and forecasting to shape forward-looking strategies in smart ways.The majority of brands are still working out the best ways to deploy AI across their businesses and a key observation from these industry-wide efforts is that without clean, connected data, even the most advanced AI tools struggle to deliver impactful results. In 2025, 42% of surveyed companies across the globe still lack a CRM, and 57% don't have a CDP—the very technologies required to unify and activate customer data. These deficiencies can lead to fragmented insights, with 29% of marketers reporting limited data availability and only 24% achieving a 360-degree view of their customers.To fully leverage the untapped power of AI measurement, brands must unify first-party data from across their systems. Incorporating data across different sources – spanning offline, online, transactional, and more – into your MMM for example can help to uplevel the model’s performance and provide the comprehensive understanding needed for more effective recommendations. This critical step demands close attention from leadership to align internal teams. As Derek Rodenhausen, Managing Director at BCG, recently stated at a measurement industry event, “30% of the battle is getting the right KPIs and toolkit, the other 70% is getting the right people and processes in place to enable those KPIs and tools to really work.”The future of marketing measurement hinges on brands’ ability to merge three essential solutions — MMM, incrementality testing, and attribution — and, crucially, to support this integrated framework with the power of advanced AI and clean, connected data. Those who are leveraging all three measurement approaches already recognize their transformative potential, with 8 out of 10 intending to increase their usage in the coming years. This signals a growing understanding that true measurement confidence comes from a holistic view, powered by intelligent technologies. Brands can no longer afford to rely on a disjointed, uncertain approach to measurement. As CMOs and executive leaders everywhere continue to call for proof of returns, marketers need confidence and accuracy. Developing a fully-integrated, AI-backed measurement strategy alongside a robust data foundation is the key to driving sustainable business growth during this ROI reckoning.
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