As C-suites demand greater accountability and cost efficiency, marketers are faced with a critical challenge: tying marketing efforts to business outcomes. With 75% of marketers facing budget scrutiny, proving the incremental value of each marketing investment is no longer optional—it’s expected, and it’s essential.
The proliferation of content through emerging channels like retail media networks and influencer partnerships means brands are battling for customer attention. To break through the noise, brands must be able to test new investments and quickly understand what is most effective in driving engagement and key business outcomes. Artificial intelligence can help.
Marketing measurement today isn’t up to speed
In an Adobe study of over 8,000 marketers and executives, more than 90% of those surveyed think that AI will transform every marketing function, but only about a quarter have developed an AI roadmap aligned with broader business goals. Even fewer have made progress toward implementing AI in their business functions. Marketers also face challenges in being able to produce timely insights that help them effectively plan their marketing budget and campaigns.
Marketing measurement is one way marketers are using AI to evaluate the performance of their spending. By measuring historical data on campaign performance across different channels—such as email, TV and social,—marketers can make better informed decisions about allocating budgets to those channels in the future.
However, timely insights are critical. I once worked with a travel company that received their Q4 marketing results the following spring, meaning they missed the moment to optimize their Q1 marketing efforts. A turnaround gap like that decreases the value of those insights. Marketing measurement needs to be accelerated, and having the right technology in place can deliver valuable insights at speed.
Additionally, while past data is useful, it’s crucial to have a data-informed perspective on which channels will perform well in the future, and thus, where to allocate future marketing dollars. Marketers can’t afford to leave this up to chance.
Plan with precision using AI attribution modeling and marketing mix modeling
As marketing measurement becomes increasingly fragmented, marketers must find better ways to bridge the gaps in customer insights caused by restricted third-party cookies and data limitations within walled gardens. They must also make sure to get a clear picture of onsite, offsite and offline performance across all channels. To avoid having their campaigns lost in the noise or budget misallocated on under-performing channels, marketers need an accurate view of where and when to meet their customers.
Marketers need more than historical marketing measurement; they also need a way to plan future investments effectively. Predictive AI can help by combining the strengths of multi-touch attribution (MTA), which measures the performance of touchpoints across specific online channels, and marketing mix modeling (MMM), which provides channel-level performance and predictive insights. Together, MTA and MMM provide a more complete picture of marketing effectiveness and spend across online and offline activities. By leveraging AI for modeling and measurement, marketers can obtain insights within days rather than months, allowing for more precise and confident budget forecasting and decision making.
Strategically harnessing AI enables marketers to tweak and plan future scenarios by measuring the impact of their campaigns. We’ve seen this work with both customers and our own teams at Adobe. We’ve unified MTA and MMM approaches, which are powered by AI in Adobe Mix Modeler, to deliver more relevant and effective campaigns on the right channels at the right time. By advancing and accelerating how marketing activities are measured, marketers can achieve their goals more quickly and confidently.
An AI-integrated, unified approach that delivers both top-down (MMM) and bottom-up (MTA) insights helps marketers quantify the ROI of their investments and differentiate by being able to rapidly identify which channels and activities will work best in the future.