Understanding the Ongoing Challenge of Measuring Brand Marketing Impact

In the dynamic landscape of Digital Marketing, organizations continuously strive to demonstrate the tangible value of their brand-building initiatives. While establishing effective branding strategies is critical, quantifying their direct contribution to sales and revenue remains a complex challenge—often described as the “forever dilemma” within marketing teams.

The Core Issue: The Perception vs. the Reality

Many businesses recognize the effectiveness of their brand marketing efforts through various indicators—brand lift studies, customer surveys, and incremental increases in branded search volumes. These signals suggest that brand activities are resonating with the audience and fostering long-term loyalty.

However, the prevailing measurement frameworks typically rely on last-click attribution models. While straightforward, this approach attributes conversion credit solely to the final touchpoint before purchase, often neglecting the cumulative influence of upper-funnel branding channels such as podcasts, connected TV (CTV), and content marketing. Consequently, the branding teams frequently find themselves at a disadvantage in internal resource allocations, as their contributions are undervalued in the final revenue attribution.

The Internal Dynamics: Brand vs. Performance Teams

This misalignment fosters a persistent internal tug-of-war. The performance marketing team often appears as the “hero,” capturing credit for direct conversions and immediate demands. Meanwhile, branding efforts, which nurture audience awareness and affinity over time, struggle to gain recognition because their impact isn’t directly quantifiable under traditional models. This dynamic hampers holistic understanding and strategic decision-making.

A Path Toward Unified Measurement

Addressing this challenge requires moving beyond last-click attribution toward a more comprehensive, causally sound measurement framework. The goal is to demonstrate—or at least estimate—the “halo effect” of brand marketing: how brand activities influence consumer behavior over the longer term and across multiple touchpoints.

Some effective approaches include:

1. Mixed Attribution Models: Incorporate multi-touch or probabilistic attribution models that better account for the full customer journey.

2. Incrementality Testing: Conduct controlled experiments, such as holdout groups or geo-based tests, to isolate the incremental impact of brand campaigns.

3. Marketing Mix Modeling (MMM): Use statistical models to analyze historical data across various channels, helping quantify the contribution of brand efforts within overall marketing spend.

4. Causal Inference Techniques: Apply advanced methods like regression discontinuity or Bayesian modeling to estimate the causal effects of branding activities on sales.

5. Unified Frameworks: Integrate different measurement methodologies into a cohesive model—combining attribution data,