Here’s why your brand marketing campaigns’ metrics are misleading!

Picture this. Mark, an innovative marketer, has just concluded an extensive multi-publisher digital campaign. It was a grand effort pushing the brand campaign, reaching audiences across three different major publishers. As the dust settles, he’s presented with separate brand lift studies, run by each of these publishers themselves. Each report is a testament to the campaign’s success, with impressive results that would make any marketer smile.

However, as Mark dives deeper into the data, a niggle of doubt starts to surface. Each study tells a tale of triumphant engagement, conversion and brand impact. But each tale is told in isolation, unlinked to the others. He realises that these results, while individually impressive, don’t tell the whole campaign story. In fact, he worries that they might even distort it.

The compounding complexity: data overlap and group contamination

Mark recognises that in each brand lift study, some of the same audience interactions are likely counted multiple times. After all, a significant portion of his audience likely encountered the campaign through more than one publisher.

Additionally, he realises there is a risk of over-attribution. If a customer saw the campaign on all three publishers before endorsing the brand, then to which publisher does the credit belong? Each brand lift study, in its isolation, seems to claim the victory.

Compounding his concern, Mark identifies another issue: the potential contamination of control groups. A brand lift study typically classifies audiences into two groups: those exposed to the campaign and a control group that remains unexposed. However, in a multi-publisher scenario, an individual assigned to the control group for one publisher might be included in the exposed group for another. This cross-contamination muddies the efficacy of the brand lift study, further obscuring the campaign’s true impact.

Mark sits back to reflect, and resolves to himself, the value of using publisher-specific Brand Lift Insights (BLI) in certain scenarios. He now knows that if he is running a campaign exclusively with one publisher, the insights from a publisher specific BLI would be both sufficient and insightful. Similarly, if he’s looking to evaluate a platform’s specific creatives or audience strategy’s contribution to his campaign, a publisher specific BLI would be his instrument of choice. However, with a cross-publisher campaign, an overall read is only possible with a cross-publisher brand lift.

The (un)known obstacle: cookie deprecation

Just as Mark grapples with these issues, he faces another curveball – that deprecation of third-party cookies might affect the credibility of the results he is seeing. This change throws a wrench into the mechanics of digital advertising. It’s like being asked to play a symphony while being gradually stripped of your instruments.

Third-party cookies have been instrumental in tracking user behaviour across websites, crucial for brand lift studies. With their demise, tracking users across multiple publishers and some device environments become significantly more challenging. The potential for data misinterpretation intensifies, and accurately assigning users to control and exposed groups turns into an uphill task.

The path forward: holistic brand impact measurement

Mark’s predicament underscores the need for a paradigm shift – a move toward holistic brand impact measurement. This approach for digital campaigns would consolidate data from all publishers and across all devices, reflecting the consumer’s journey in its entirety rather than as disconnected interactions.

A holistic measurement method also addresses the issue of control and exposed group cross-contamination. With a unified view of audience interactions across all publishers, it becomes possible to accurately delineate between those who were exposed to the campaign and those who were not; thereby maintaining the integrity of the control and exposed groups.

The solution in practice

Holistic brand impact measurement may feel like a utopian concept – an idealistic world where campaign data from various publishers and devices integrate seamlessly, telling a complete and accurate story of consumer journeys. However, this idealistic world doesn’t have to remain a distant dream.

The challenges are real, but so are the solutions. One of them is , an innovative tool designed to bridge these gaps and bring the concept of holistic brand impact measurement for digital campaigns to life.

Kantar’s Brand Lift Insights unifies data from all publishers, ensuring that the unique contribution of each channel to your campaign’s success is accurately tracked. It presents a panoramic view of your campaign, drastically reducing data overlap and control group contamination.

As we navigate the impending phase-out of third-party cookies, Kantar’s measurement stands its ground. It’s built to adapt to the challenges of a privacy-focused era of digital marketing. Effectively leveraging first-party data, consent-based user tracking and heavily validated (Opportunity-to-see) models, it continues to provide precise brand impact measurements even in the absence of third-party cookies.

At Kantar in Australia, we have been the trusted campaign effectiveness partner for top-tier advertisers and publishers for over a decade. We have measured more than 500+ multi-media and digital campaigns and use our extensive campaign effectiveness data to benchmark performances of every campaign measured.

Kantar’s Brand Lift Insights is the compass that can guide you through the complex landscape of cross-publisher campaigns. It’s the key to turning the ideal of holistic brand impact measurement into a practical reality.



Meheer Thakare
Lead, Media Effectiveness (Melbourne) / Director,
Kantar Australia