Beyond Attribution: The Case for Validation and Calibration in Marketing Measurement

Over the next few weeks we’re going to go deeper into the role of validation and calibration in marketing measurement. This is the first post in a series of posts derived from our recent webinar. Catch the full event on demand here.

Accurately measuring the impact of media investments remains a critical challenge. During a recent webinar hosted by Rockerbox, three industry leaders—Will Burghes, Head of Professional Services at Rockerbox; Eli Hile, Senior Director of Data and Analytics at Tombras; and Aoun Jafarey, Senior Vice President of Client Solutions & Data Science at Publicis Groupe—explored how validation and calibration are redefining the way marketers approach attribution and optimize media spend.

Their discussion highlighted practical methodologies, shared real-world case studies, and addressed some of the most pressing questions marketers face today. This thought leadership piece distills the core insights from the conversation, providing a roadmap for marketers seeking to elevate their measurement strategies.

Catch the session on demand here.

The Difference Between Validation and Calibration

To build a foundation for the discussion, we first distinguished between validation and calibration:

Validation is the process of assessing the accuracy of attribution results using external methodologies like MMM, incrementality testing, or surveys.
Calibration involves adjusting these results to create unified KPIs that better reflect true marketing impact.

These concepts are critical as marketers transition from relying on singular attribution models to adopting more holistic measurement approaches.

Why Validation is Essential

At the heart of effective marketing measurement lies a fundamental truth: no single model can capture the full complexity of consumer behavior and media impact. As Will Burghes, Head of Professional Services at Rockerbox, succinctly put it, “No model is a perfect representation of reality. Validation allows marketers to cross-reference multiple measurement techniques, ensuring they make decisions based on the most reliable data available.”

This insight is critical because every measurement model is, by nature, an approximation. Attribution models, while powerful, often reflect inherent biases or structural limitations. For instance, last-click attribution tends to overemphasize lower-funnel channels, failing to capture the nuanced role of mid- and upper-funnel media in influencing consumer decisions. This disconnect can lead to misallocated budgets and underinvestment in channels that drive long-term brand equity.

Eli Hile, Senior Director of Data and Analytics at Tombras, expanded on this point, emphasizing that validation serves two primary purposes:

Proving the Effectiveness of Media: Validation provides marketers with the tools to distinguish genuine performance from inflated metrics. This clarity ensures that the true value of media investments is recognized and rewarded, enabling brands to focus on strategies that deliver meaningful impact.
Enabling Accurate Optimizations: By refining attribution results through validation, marketers can optimize campaigns with confidence, making adjustments that not only improve short-term outcomes but also align with long-term growth objectives.

Hile also pointed out that without validation, marketers run the risk of undervaluing mid- and upper-funnel channels. These channels—such as video, display, and influencer marketing—often contribute indirectly to conversion by building awareness and shaping perceptions. In traditional attribution models, their contributions may be underrepresented or even dismissed.

“For example, mid-funnel channels often face attribution bias due to their lack of direct, last-touch interactions with consumers,” Hile explained. “But these channels play a critical role in creating demand and driving prospects into the purchase funnel.”

Validation, whether through incrementality testing, Marketing Mix Modeling (MMM), or surveys, ensures that these channels receive their fair share of credit. By cross-referencing multiple methodologies, marketers can identify and correct biases, creating a more accurate picture of how media efforts contribute to overall performance.

This multi-layered approach not only builds confidence in decision-making but also supports a balanced investment strategy. It allows brands to avoid over-indexing on lower-funnel tactics while fostering sustainable growth through a more holistic understanding of media performance.

As Burghes concluded, “Validation isn’t just a safeguard; it’s a competitive advantage. It equips marketers with the insights they need to maximize ROI and minimize risk, ensuring every dollar spent drives the greatest possible impact.”

The Importance of Multi-Touch Attribution as the Foundation of Measurement

Multi-Touch Attribution (MTA) serves as the cornerstone of modern marketing measurement, providing granular, real-time insights into user paths and channel contributions. However, while MTA excels at offering detailed attribution data, it is not without limitations—particularly in capturing the broader, long-term impact of media and accounting for external factors like seasonality or competitive dynamics.

To address these gaps and ensure a comprehensive understanding of performance, marketers rely on validation methodologies such as Marketing Mix Modeling (MMM) and incrementality testing. These approaches are designed to validate and enhance the foundational insights provided by MTA, offering complementary perspectives that ensure decisions are based on accurate, reliable data.

MMM and Incrementality Testing: Validation Methodologies That Support MTA

Marketing Mix Modeling (MMM):
- Role: Provides a macro-level view of media effectiveness over time, analyzing historical data to assess how different channels interact and contribute to overall performance.
- Value to MTA: MMM validates long-term trends and helps contextualize MTA’s granular insights by incorporating external factors like economic shifts or competitive activity.
Incrementality Testing:
- Role: Measures the causal impact of individual channels or campaigns, isolating variables to determine what is truly driving performance.
- Value to MTA: Incrementality testing validates the assumptions made by MTA by answering specific questions about channel contributions, ensuring that over-attribution or under-attribution is corrected.

By using MTA as the foundation and MMM and incrementality testing as validation layers, marketers gain a holistic understanding of performance:

MTA provides the detailed, immediate attribution data needed for tactical decision-making.
MMM and incrementality testing act as checks and balances, ensuring MTA results align with broader, long-term business outcomes and real-world causality.

This cross-methodology approach not only reveals discrepancies but also strengthens confidence in decision-making, enabling marketers to refine strategies, optimize investments, and align their efforts with both short-term and long-term goals.

As marketing becomes increasingly complex, leveraging these methodologies in tandem ensures that brands can navigate the intricacies of performance measurement with precision and clarity.

Calibration for Actionable Insights

While validation focuses on accuracy, calibration ensures those insights are actionable. Through calibration, marketers can adjust their attribution models to reflect unified KPIs, creating a consistent framework for evaluating success across channels.

For instance, a calibrated model might apply incrementality multipliers derived from testing to attribution results, ensuring that overvalued or undervalued channels are adjusted to align with real-world performance. This process not only standardizes reporting but also makes it easier for teams to communicate results and align on strategy.

Looking Ahead: Preparing for What’s Next

Validation and calibration are not one-time fixes—they are ongoing practices that should evolve with your marketing strategy and the data landscape. With the rise of new privacy regulations and the decline of third-party cookies, these practices are becoming even more critical.

Over the next few weeks, we’ll delve deeper into specific topics, including: