Over the next few weeks we’re going to go deeper into the role of validation and calibration in marketing measurement. This is the third post in a series of posts derived from our recent webinar. Catch the full event on demand here, also read the first and second posts in the series.
Case studies shared during the webinar by Will Burghes, Head of Professional Services at Rockerbox, and Eli Hile, Senior Director of Data and Analytics at Tombras, highlighted how validation can uncover inefficiencies, refine strategies, and drive measurable impact. These real-world examples emphasized the importance of moving beyond attribution assumptions to gain a clearer picture of what’s truly driving performance.
Case Study: Revisiting Brand vs. Non-Brand Search
Burghes recounted a striking example involving a major advertiser investing heavily in both brand and non-brand search campaigns. While attribution models painted a rosy picture of performance across the board, validation testing told a different story.
- The Test: Incrementality testing was employed to evaluate whether conversions attributed to brand search were truly incremental or if they would have occurred regardless of paid search ads.
- The Findings:
- Only 20% of brand search conversions were incremental, meaning 80% of the attributed conversions would have happened without the ads. For this advertiser, a household name with significant organic visibility, many consumers searching for the brand were already predisposed to purchase and would have navigated via organic search results.
- In contrast, non-brand search campaigns demonstrated nearly 100% incrementality, proving their ability to drive new customer acquisition.
The Impact:
These insights allowed the advertiser to reallocate budgets, reducing overspend on brand search and doubling down on the high-performing non-brand campaigns. “This differentiation helped maximize the effectiveness of their search strategy,” explained Burghes. “Instead of treating all search campaigns the same, they prioritized investments where they could generate genuine incremental results.”
Case Study: Surprising Incrementality in Brand Search
Hile offered a counterpoint with a case study showcasing how brand search can yield unexpected results depending on competitive dynamics and brand recognition.
- The Scenario: An e-commerce client in the clothing space was similarly testing the incrementality of their brand search campaigns.
- The Findings: Unlike the previous example, brand search showed incrementality rates of 40-45%, significantly higher than anticipated. The reason? A unique combination of factors:
- The brand’s name was distinct, making it unlikely that consumers would accidentally find them via organic search.
- The competitive environment was particularly fierce, with competitors aggressively bidding on the client’s branded keywords. Paid ads ensured the brand’s presence at the top of the results page, effectively countering this competition.
The Impact:
The insights validated the client’s continued investment in brand search but with a more balanced approach. “While the incrementality wasn’t as high as non-brand search, it was still significant enough to justify a calibrated budget allocation,” Hile explained. “This example underscores the importance of testing—assumptions about what works and what doesn’t can vary dramatically across industries and competitors.”
Key Lessons for Marketers
- The Importance of Context:
These case studies illustrate that the performance of brand search—or any channel—cannot be assessed in isolation. Contextual factors like brand recognition, competitive dynamics, and organic search strength play a critical role in shaping incrementality. - Data-Driven Adjustments:
Testing and validation allow marketers to shift resources away from inefficiencies and toward high-impact strategies. Burghes and Hile agreed that these findings empower brands to “squeeze every dollar of value from their campaigns.” - The Value of Nuance:
Broad assumptions about channel performance can lead to waste or missed opportunities. Incrementality testing reveals nuances that attribution models might miss, ensuring more accurate and effective decision-making.
By leveraging validation methodologies, marketers can gain the clarity needed to optimize their spend and align strategies with true performance drivers. These examples are a powerful reminder of the potential hidden in the data—waiting to be uncovered with the right approach.