There is growing interest in using triangulation to improve marketing measurement. Yet, there is still no shared understanding — or consensus — on how to combine attribution, marketing mix modeling (MMM), and incrementality tests effectively.
Dr. Isabelle Kes will use practical examples and insights into the scientific discourse to shed light on these approaches. She will show how triangulation can address the challenges of marketing measurement — but also where its limits remain.
Further, she will give an overview how marketing measurement should be anchored in a company to ensure sustainable usage.
Ad-blockers, tracking prevention, and incomplete consent make accurate measurement harder, especially under strict privacy rules. These data gaps disrupt attribution and weaken campaign performance.
Pixum and Giesswein tackled this challenge with server-side tracking and AI-powered Synthetic Users—recovering lost conversion data and boosting ROAS by 10–25%, even in privacy-restrictive environments like Safari.
In this session, Thomas Tauchner shares insights from these real-world projects and shows how to close data gaps and improve measurement quality while staying compliant.
Attribution and marketing mix models alone can’t capture the full picture of marketing effectiveness. Experiments and incrementality testing offer a clearer view of true causal impact — not just correlations.
In this session, we’ll explore how experimental design fits into a broader strategy of measurement triangulation. We’ll discuss the strengths and limitations of different testing approaches and share solutions to common challenges.
Discover why incrementality testing is not just a method, but a mindset – and why it should be at the heart of modern marketing measurement strategies.
