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Which EEG-metrics do we use when analyzing brain activity in neuromarketing research?

The most exciting part of our neuromarketing research is the analysis of the EEG-data. Finally, we can take a peak in the unconscious brain. For the data analysis, we use four metrics: Desire, Confusion, Attention, and Workload.

Principles of EEG 

An EEG-test is able to measure emotions and motivations. However, we’ll first take a dive into the workings of an EEG. What does EEG measure precisely? It registers electrical, neural activity as brain waves of maximum 80 Hertz (Hz).

The wavelengths in this range can be classified as delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-25 HZ) and gamma activity (>25 Hz). These frequencies can be observed during altered attention (delta activity), sleepiness (theta activity), relaxation (alpha), and concentration (beta).

The metrics are then calculated, using the wavelengths and an algorithm.

After reading this theory, that is likely to have altered your theta activity, we’ll continue the explanation of the four different metrics we use for our research: Desire, Confusion, Attention, and Workload.


What show will I watch tonight? Is this the man of my dreams? What kind of apples should I buy? This is just a grasp of the questions that can be answered using the desire metric. Research has shown that desire highly correlates with, for example, billboard charts, high-grossing movies, and even partner choice.

For the calculation of this metric, we use the alpha activity from the electrodes that are placed on the left and right side of the head. When activity in the left side of this so-called frontal region is higher than right-sided activity, this means we are attracted to whatever we observe. Is there more activity on the right side? Then we’re being repelled by whatever is in our sensory fields.

This is reflected in our data as negative activity (-1 to 0) for repulsion and positivity activity (0 to 1) for attraction. This metric is used in all of our research, because of its predictive qualities of actual buying behavior.

Some characteristic research questions for which desire is important:

  • Is your advertisement perceived as desirable or repulsive?
  • Will consumers actually buy your product?
  • Will consumers return to your shop?
    Neuromarketing EEG Example: Desire Metric


Sometimes, marketing communication can take an unexpected turn. An advertisement can be perceived as boring, or a non-intended web page is loaded. On moments like these, we’ll observe altered confusion in the brain activity.

Confusion means that you are involved in something else than the relevant cognitive task. This could be brought about by frustration, boredom, or actual confusion. This is reflected in our data as a score varying from 0 to 1, in which 1 implicates high confusion.
Confusion is undesirable in marketing communication. Therefore, this metric is used in, among other things, usability research to provide practical recommendations on websites.

Some characteristic research questions for which confusion is important:

  • Does a webpage contain the right amount of information?
  • How are the transitions between pages on your web site?
  • Has your store a sensible floor plan?

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Have you ever been so focused when reading a book or watching a movie, you forgot the time? In this case, your brain shows a high amount of attention. The attention metric is a reflection of involvement with a task: For example, of the focus one has when gathering information and visually scanning a store.

This metric is related to personal relevance and is a predictor for the consolidation of memory. This is important for the memorability of a certain stimulus or event. 

Levels of attentions are shown in a continuous scale from 0 to 1. At 0, the stimulus is not successful in capturing our attention. A score of 1 shows that the brain is extremely focused on processing information.

Some characteristic research questions for which attention is important:

  • To what extent does the campaign grasp the attention of consumers?
  • Is the brand proposition relevant?
  • Do consumers find your store interesting?


Workload increases when the working memory in the brain gets overloaded. For example, when you’re being asked to count from 100 to 0 in steps of 7. Workload increases when solving problems, integrating information, and arguing analytically.

Workload helps us to focus on the activities that are important at that moment. It fluctuates between 0 and 1, wherein a workload between 0.4 and 0.8 is seen as ‘sweet spot’. The sweet spot indicates the ideal amount of effort that the brain has to process the information. The brain is actively processing the content but does not show too big of an effort to process it.

A dip in the workload (below 0.4) indicates that the brain is bored. This often occurs when a boring advertisement or website is being processed.

On the other side, a peak in workload (above 0.8) means that the content is perceived as too complicated. A nice example is Times Square: the brain is overloaded with visual, auditory, and olfactory sensations.

Some characteristic research questions for which workload is important:

  • Is the advertisement too boring for consumers?
  • Are the product categories on the website too complicated for consumers?
  • Are there too many sensations in your store?

Concluding Remarks

These four metrics are being used by Unravel Research for our qualitative and quantitative analyses of retail research, advertisement research, and usability research.

For each type of research and analysis, we use a different combination of the metrics that are relevant for the research question. Read more in our blog Data-analysis of EEG in neuromarketing research.

EEG, Neuromarketing, Commercial, Neuro