Consumers today navigate a dynamic journey — streaming, scrolling, searching, and shopping — across channels and devices, sometimes all at once. It’s no surprise then that 8 in 10 online purchases involve multiple touchpoints.1 For marketers, this complex journey requires a new measurement strategy: one that shows a full picture of all customer interactions, enables smarter budget allocation, and drives significantly higher ROI.
AI is at the center of this approach. It’s the force accelerating new consumer behaviors, and powering the measurement solutions that help you keep pace. In this article, we’ll explore four ways you can use AI-powered measurement to your advantage.
1. Own your performance with a strong data strategy
AI can be a powerful growth driver, but it needs the right data. Your first-party data is your key competitive edge, serving as the fuel to optimize your campaigns, reach the right audience at the right time, and boost performance. It’s foundational to any advertising platform, including Google and third-party providers. In fact, marketers who perceive using first-party customer data as enabling AI report seeing a 30% lift in performance compared to those who don’t.2
Google’s tools were built to put all of your first-party data to work seamlessly. For example, Google Ads Data Manager allows you to easily connect data from disparate sources in one place, enabling deeper customer insights and more relevant ads. It also helps streamline the process of using other features, like enhanced conversions for leads. Enhanced conversions for leads improves the accuracy of your conversion measurement by allowing you to link your first-party data to match offline conversions back to your Google Ads campaigns. Advertisers using the feature achieved 8% more conversions than measured with standard offline conversion import on Search.3
In other words, by using the right solutions you can measure online and offline conversions that would have otherwise not been captured.
2. Make smarter budget decisions with advanced MMMs
To truly understand your media effectiveness, you will need a multistep measurement setup that includes marketing mix modeling (MMM), incrementality testing, and attribution. This combination unlocks the highest ROI for your marketing dollars.
MMMs have long been a valuable tool to understand the long-term impact of marketing investment across channels and inform budget allocation decisions. Research shows that C-level leaders who placed high importance on MMMs were over 2X more likely to exceed revenue goals by 10% or more.4
Understanding how much spend should go to specific formats is best for actionable decision-making.
But traditional MMMs, largely built to measure the brand impact of offline media, have struggled to accurately measure online media. Here’s an example. Advertisers are more likely to say Google Search provides a good return on ad spend (ROAS), more than any other paid advertising platform.5 However, if your MMM doesn’t account for the various auction dynamics of Search, like a sudden increase in organic queries for your product category, you may be underestimating the impact of your Search campaigns. This could lead to inefficient budget allocation and lower market share that your competitors will otherwise capture.
That’s why leading marketers are increasingly turning to advanced MMMs to more accurately capture the nuances of online channels and gain more actionable insights. For example, Meridian, Google’s open-source MMM, incorporates more granular data, like Google query volume or reach and frequency, empowering marketers to better allocate budgets at greater levels of detail, while respecting user privacy. Knowing how much budget to allocate to digital marketing is good; knowing the exact dollar amount that should go to Search, Display, or YouTube is better; and understanding how much spend should go to specific formats is best for actionable decision-making.
3. Validate and refine tactics with incrementality testing
While MMMs help you better plan your budget allocation, incrementality experiments like Brand Lift and Conversion Lift help you evaluate which tactics or channels drive outcomes that would not have happened organically. They allow you to say with certainty that your campaign drove a customer action.
Thanks to experiments, you can identify where your modeled predictions differ from actual results, so you can take action.
Incrementality experiments split your audience into two groups: one that is exposed to your ads and one that isn’t. Then they compare metrics such as brand awareness, search volume, or conversions across the two groups, giving you a deeper understanding of your ads’ true effectiveness. For example, you might run an incrementality experiment to help you understand whether your app-install campaigns are driving incremental downloads.
Beyond validating individual tactics, incrementality testing also provides you with insights to refine your MMMs and attribution models. Thanks to these experiments, you can identify where your modeled predictions differ from your actual results, so you can take action and optimize your models for greater accuracy.
4. Unlock the full value of your investments with data-driven attribution
Every day, people engage with your brand repeatedly across countless channels, platforms, and devices. This complex web of interactions makes last-click attribution models obsolete, because they give all the credit to the last touchpoint instead of calculating the contribution of every interaction that led to a purchase. If you’re still using last-click attribution, you may be misallocating budgets and missing revenue opportunities.
By embracing a multifaceted measurement strategy, marketers can confidently navigate the evolving media landscape and drive ROI.
Data-driven attribution, powered by Google AI, accurately assigns credit to each interaction in real time and is always on. By considering a vast number of insights and dynamically adjusting to each of them, it helps you optimize campaigns in real time and get the best return for your marketing dollars. That’s why data-driven attribution is the default for all Google Ads campaigns.
Rethink your measurement today
In a world where every marketing dollar counts, the ability to clearly demonstrate ROI is paramount. By embracing a multifaceted measurement strategy that integrates AI-powered attribution, MMMs, and incrementality experiments — built on a foundation of first-party data — marketers can confidently navigate the evolving media landscape and drive ROI.
