Measuring the impact of brand investments in B2B settings is often dismissed as challenging. While traditional metrics like first-touch and last-touch attribution fail to capture the true influence of brand efforts, a new approach called incrementality offers a more accurate assessment. This method focuses on understanding what would happen if a brand investment were absent, rather than just tracking clicks or conversions. It emphasizes the importance of mental availability, where consumers recognize and trust a brand before they even engage with it. To effectively measure brand impact, the article outlines a four-step framework. First, define success metrics that go beyond immediate revenue, such as pipeline growth or behavioral indicators like search query volumes. Second, form a testable hypothesis centered on incrementality. For example, hypothesizing that increased brand spending will lead to higher traffic and sales-qualified opportunities sets a clear foundation for measurement. The third step is to conduct incrementality tests through geo-tests, control groups, or time-based comparisons to establish causal relationships. Finally, combining incrementality results with Marketing Mix Modeling (MMM) provides a broader view of how different channels contribute over time. The article also highlights that while significant brand investments can yield measurable uplifts—like a 2% revenue increase or a 6% boost in funnel conversion—this method is typically effective for companies with substantial marketing budgets, usually exceeding a few million dollars annually. Tools like Paramark leverage AI to streamline data analysis, making it easier for B2B teams to assess brand impact without needing extensive data science resources.