Leveraging Implicit Data Using Causal Machine Learning
Implicit measurement methods successfully quantify aspects of unconscious decision making. Mostly unsolved is the question how those aspects, such as stimulation, balance or dominance emotions, drive decision making and particularly how this differs between products, contexts and target groups. By connecting implicit with explicit data and success measures and applying causal machine learning techniques we discovered new, unexpected and highly relevant insights: stimulation not balance emotions are driving milk sales, relaxation not excitement emotions drive audio equipment sales, hedonistic emotions not association with quality or tradition drive beer sales.
Friday October 21, 14:15
- Fiding relationships of implicit data and success metrics
- Three examples of the implicit methods applied in practice
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Speakers: Dr. Frank Buckler, SUCCESS DRIVERS GmbH & Dr. Steffen Schmidt, University of Hannover