Unlocking unexpected insights

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.

EEG can be applied to various use cases such as:
- Design of marketing materials optimally adapted to the unconscious perception of customers

- Optimization of control elements to ensure intuitive useImprovement of digital presentations and pitches in order to present content more convincingly and successfullyImprovement of customer communications

- Optimization of sponsorship and advertising placements

- Optimization of information dashboards and user interfaces

- Identification of design and navigation weaknesses in physical and digital products

- E-learning improvements to address users better and to convey content more efficientlyImproved pre-launch predictions about which products or campaigns are particularly promising/motivating to buy 

- Compared to traditional market research, the use of EEG offers significant advantages

- Quantification of motivation to buy/motivation to act, as the brain signal of the perceived attractiveness is measured and quantified directly

- Capturing brain reactions long before a person can consciously make a decision

- Insights into intuitive reactions that the participants themselves are not aware of Quantitative assessment of the motivation and cognitive exhaustion of participants when using a test object

- Derivation of unbiased, objective information based on implicit measurement.

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 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.

Eye tracking can be applied to various use cases such as:Increasing the usability and appeal of desktop and mobile applicationsOptimizing marketing materials to draw and hold attention of target audiences  Optimizing sales pitches and presentations to visually steer focus points and maintain high engagementDesigning easy-to-use and engaging dashboards for managers and executives The use of eye tracking offers significant advantages, especially in combination with EEG:Unbiased insights into both conscious and unconscious perception of visuals and textsUnderstanding which characteristics of visuals and texts attract attention Understanding where navigation paths are disturbed and by what.

"The face is the window to the soul", as the renowned US psychologist and emotion researcher Paul Ekman once put it. A small raise of the eyebrow, an unintended smile or an angry look for a fraction of a second often says more about the reception of investment-heavy artwork than what people tell when they are asked how they feel about it. The method of facial coding relies on technical advancements to detect facial expressions that reveal our emotions. 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.At Deloitte Neuroscience Institute we use facial coding to automatically generate objective interpretations on emotional reactions, e.g. towards film sequences or during media consumptionFacial coding can be applied to various potential application areas such as:Analysis and optimization of sales calls and customer service experiences (queues/routing)Detection of unconscious emotions during media consumption
Facial coding can advance other research methods as EEG and eye tracking byAllowing objective conclusions about emotional statesImproving visual stimuli and storylines based on emotional reactions

The GSR method is based on the correlation between our mental and physiological reactions – transpiration for example. When we experience arousal such as stress or joy, we begin to sweat as our sympathetic nervous system 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 they are 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 to achieve the desired emotional reaction. GSR can be applied to various use cases such as:Design of targeted and emotionally appealing marketing materialsIncreasing the attractiveness and emotional impact of talks, presentations and video contentIdentification of sources of frustration when using physical or digital products Design of intuitive, user-centered business processes GSR can advance other research methods such as EEG and eye tracking byAllowing unbiased, objective conclusions about arousalDeriving information on unconscious, emotional reactions to contentFurther improving user experiences based on emotional reactions and stress reduction.

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.