EEG

Electroencephalography (EEG) measures brain activity that allows for unique insights into brain reactions. We use the EEG to measure how motivated people are in terms of both extrinsic and intrinsic motivation. From this, we derive how attractive content is rated and, in combination with eye tracking, how well the usability of a website or product is. Next to motivation and perception, the cognitive load of a user can be effectively evaluated using EEG. This provides insights on how content should be structured to avoid frustration and exhaustion.

Nudging & Behavioral Economics

Debiasing and Nudging are two behavioral economic methods that can be used to assist decision-making. Debiasing is a way to proactively make people aware of irrational distortions in their behavior (e.g. prejudices or biases) and helping them to make more rational, objective decisions. Nudging, on the other hand, is the targeted change of habits, internalized processes, representations or formulations with the aim of discretely influencing micro-decisions such as eating healthier or favoring the less expensive hotel accommodation.

Eye Tracking

Eye tracking is a very established methodology that is used alone or in combination with other neuroscientific approaches. One main application area of the eye tracker is the improvement of user interfaces (UI) or user experiences (UX) which is particularly powerful in combination with EEG. Using eye tracking we can, for example, shed light on where users and consumers actually look at when interacting with a website, store shelves, or a product and what aspects of a message or user interface they actually focus on. The method allows to reconstruct gaze paths and helps to identify focus points and eye movements that study participants are not even aware of. We can measure when, in which order and with which focus specific elements are perceived. Thus, we can quantify and analyze consciously and unconsciously perceived perspectives that cannot be identified with explicit methods.

Facial Coding

A small raise of the eyebrow, an unintended smile or an angry look for a fraction of seconds say often more about the reception of investment-heavy artwork than what people tell when they are asked how they feel about it. Hence, the method of facial coding relies on technical advancements to detect emotion revealing facial expressions. Technically, it is based on a combination of image recognition, machine learning and deep learning algorithms where the self-learning algorithm for pattern recognition detects key facial characteristics such as the mouth, eyes and eyebrows. Changes in these features are used to classify distinct emotional states. This way, small changes in facial expressions can be detected and interpreted. Thus, we use facial coding to automatically generate objective interpretations on emotional reactions, e.g. towards film sequences or customer experiences.

GSR

The GSR method is based on the correlation between our mental and physiological reactions – transpiration is such an example. When we experience arousal such as stress or joy, we begin to sweat as our sympathetic nerve increases its activity. This is also the case when experiencing emotions such as anger or frustration. The intensity of our emotional arousal but not the type of emotion can be derived from transpiration. Conversely, during boredom or relaxation transpiration decreases. We use GSR to measure changes of transpiration with high sensitivity. For this purpose, two electrodes are attached to the hands of study participants while interacting with an object or a person. Then, the voltage difference across the electrodes is used to calculate the skin conductivity which allows conclusions on their emotional state (e.g. bored, relaxed, engaged) during that experience.

These insights are used amongst others to test and improve communications, marketing messages, advertisements, and product/service experiences in order to achieve the desired emotional reaction.

Forced Choice Testing

The Forced Choice Online Test, also called the Implicit Association Test (IAT), is a method that forces participants to consecutively decide in between two options within a very short time frame. Therefore, they must decide often and intuitively about their preference when confronted with two options over and over again. This approach provides a more realistic and pure insight into preferences and associations of participants towards brands, services, products or even features. We also use this method to identify and visualize implicit attitudes towards presented contents, attributions or characteristics. With this method we cannot only derive which option is unconsciously preferred by customers but also what they implicitly relate with e.g., a brand. As a result of the Forced Choice Online Test, preferences are often ranked and compared among each other to show what really is important to customers. Therefore, the approach can be supportive in prioritizing product/feature development and budget allocations, too.