With the upsurge of neuromarketing research, it’s more and more common for marketers to let brain waves optimize their ads, stores, products and websites. In order to do so, the research method used most often is Electroencephalography (EEG). This is a method that captures brain activity by isolating electrical activity through electrodes on the scalp.
Over the years, EEG technology has branched into many shapes and forms. From medically engineered caps consisting of over 100 electrodes, to single electrode headsets that appeal to the consumer market.
When embarking onto EEG research, chances are you will cooperate with a specialized neuromarketing research agency. You want them to address your research question with technology and metrics that are appropriate for the job. In this article, we list three important considerations any company should take into account when selecting a neuromarketing research vendor.
Question 1. Dry versus Wet EEG electrodes
Traditionally, EEG electrodes make contact with the scalp through a dab of conductive gel or cream. However, the number of dry EEG systems is vastly rising the last couple of years. These systems can used more swiftly and easily, but could potentially hinder signal quality.
Recent research into this issue has compared dry and wet EEG electrodes (Mathewson, Harrison & Kizuk, 2017). The researchers have established a clear trade-off between ease of use and amount of data noise. While dry systems are certainly less time consuming to work with, they result in stronger data contamination by other sources of electricity, such as muscle movements and external sources.
In practice, this means that dry EEG will result in fewer insights and more false positives. It’s very much like a kitchen strainer with relatively wide holes: many data slips through the openings and only the biggest chunks remain. That’s not to say dry EEG offers no value – it does – but its accuracy still pales in comparison to wet electrodes. Many researchers consider dry electrodes suboptimal for studies in which participants interact with a piece of marketing communication only once (e.g., advertising, retail and online usability research). However, the noise can be trimmed when averaging the signal across multiple trials (e.g., viewing a product image multiple times).
Ask your neuromarketing research vendor whether they employ dry or wet EEG. In the case of dry EEG, ask which precautions they make to iron out the added data noise.
Mathewson, K. E., Harrison, T. J., & Kizuk, S. A. (2017). High and dry? Comparing active dry EEG electrodes to active and passive wet electrodes. Psychophysiology, 54(1), 74-82.
Question 2. EEG Headset Comfort
An important downside of EEG research is that it can be quite stressful and uncomfortable for your respondents to be part of, compared to your everyday interview or survey. For many people, it’s the first time in their lives they allow a futuristic apparatus to record their brain activity. This increased stress or physical discomfort isn’t much of an issue for the medical purposes for which EEG was traditionally developed, but it can be detrimental to marketing research.
Nowadays, commercially oriented EEG headsets vary greatly in their designs and materials. This can make quite a difference in the respondent’s experience, and therefore in the subsequent data. Ideally, you’d want respondents to feel like home. First of all, it helps to create a living room like research environment that brings them at ease. Secondly, the lesser people are aware of the EEG headset itself, the better. It’s therefore important to be mindful of how respondents experience the EEG headset.
In a comparative study, a team of researchers led by Hairston (2014) tested three EEG systems that are popular among neuromarketing researchers: B-Alert X10, EMOTIV EPOC and QUASAR HMS. They compared the headset to the BioSemi ActiveTwo, a laboratory grade gold standard.
The researchers found that two out of three commercial headsets were actually less comfortable than the lab standard. Both the EMOTIVE and QUASAR headsets were rated less comfortable than the standard ActiveTwo. After a while, some respondents reported headaches or neck pain due to weight or uneven pressure from the headset. Only the B-Alert X10 fared better than the ActiveTwo. Its flexible strip-based design contains no hard plastics, which makes it appropriate for a higher diversity of head shapes.
This study shows that, overall, commercial EEG systems still have a long way to go before they become truly unnoticeable. Be sure to inquire which system a neuromarketing vendor uses and which precautions they take to maximize respondents’ comfort.
Question 3. EEG Metrics
The third and final question concerns the actual metrics your neuromarketing vendor promises to derive from EEG. Which emotional and motivational states do they calculate? And on what scientific underpinnings do their metrics lean?
EEG metrics belong to one of these two types:
Openly validated metrics- These metrics are validated in published academic articles (e.g., attention). Researchers have clarified what pattern of brain activity underlies the metric, so it can be replicated and put to further empirical scrutiny.
Proprietary metrics- These metrics are said to measure a specific psychological state (e.g., anger) but the underlying brain activity and algorithm are kept secret. This highlights the problem of the ‘black box’: the metric could very well measure what it pretends to measure, but there’s no way to know for certain.
Stephen Genco, Andrew Pohlmann, Peter Steidl (authors of Neuromarketing for Dummies) argue strongly in favor of validated metrics. A client should know what research they are paying for. In addition, sharing of research knowledge accelerates development and finetuning of EEG metrics.
Before conducting a study, ask which metrics will be measured. On what empirical studies are they based? And what will these metrics unearth that help you make your marketing better?
Genco, S. J., Pohlmann, A. P., & Steidl, P. (2013). Neuromarketing for dummies. John Wiley & Sons.
Hairston, W. D., Whitaker, K. W., Ries, A. J., Vettel, J. M., Bradford, J. C., Kerick, S. E., & McDowell, K. (2014). Usability of four commercially-oriented EEG systems. Journal of neural engineering, 11(4), 046018.
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