Using neuroscience to conduct consumer research is a relatively new approach to the field of market research. The application of neuroscience technologies and methodologies to better understand the consumer experience is a very exciting idea. However, “With great power comes great responsibility,” as the character Ben Parker of Spider-Man fame once said.
In fact, you may have read about neuromarketing in the news. With headlines such as “How to make the most memorable TV ad, according to neuroscience” , “Advertisers are looking inside your brain: Neuromarketing is here and it knows what you want”,and “Making Ads That Whisper to the Brain” you may start to think that we’ve finally arrived in the future; and that we are living in the movie Minority Report. In the case of neuromarketing, the future is now!
A pattern that emerges from the news headlines is the application of neuroscience to advertising. This is the most common application of neuromarketing – the practice of using neuro-tools like fMRI, EEG or other biometrics to measure response to commercial advertising in hopes of being able to more accurately design TV commercials that have greater appeal. They’ve found some success, however, this application can be limiting. Many of the neuro-tools being used have been questionable. For example, the use of low cost EEG headsets or high cost fMRI with small sample sizes.
So what can neuroscience do and why should you use it in your market research?
As your friendly neighborhood neuroscientist, I’d like to help answer your questions.
What is Applied Consumer Neuroscience?
We at HCD prefer to use the term Applied Consumer Neuroscience as opposed to Neuromarketing. Why? Neuromarketing is obviously the more recognizable term. However, it also carries with it some negative connotations associated with junk science and snake-oil salesmenship. In fact, many in the neuromarketing field are switching to using the more academic sounding term – Consumer Neuroscience. We chose some years ago to separate ourselves from the neuromarketing term because what we do at HCD is offer a combination of traditional quantitative and consumer research methodology with neuroscience or psychological methodology, which together work as Applied Consumer Neuroscience or the application of all these methodologies to market research.
What impact have you seen neuro measures make on business decisions?
Often, neuro measures have been used in advertising to test the effectiveness of an ad that has already been created, or to help diagnose problems in ads. This is the case with consumer products too. Neuro measures can be used in early, middle and late stages of product development. Neuro methodologies can be great in early stage research in order to gauge the feasibility or interest of innovative concepts or as an aid to exploratory research. It can also be used in mid stages of development to assess and differentiate product attributes such as colors, fragrances, flavors, spokes-people for ads, etc., for optimization. It can be used in later stages of development for final product testing, benchmark comparisons, or in-use/in-home testing. We have helped our clients optimize products across all of these stages to make more impactful products that connect better to their consumers’ needs, both for emotional needs and practical needs.
What are the limitations?
This is a very important question that is perhaps not asked enough. There are limitations to what could and/or should be studied using neuro measures. The purpose of using neuro measures is to uncover consumer understanding that cannot be assessed by traditional measures alone, the things you cannot easily ask or that consumers cannot easily answer or articulate.
First and foremost, it depends on the research question. Not all research questions require neuro measures, and not all neuro measures are appropriate for all research questions or situations. For example, if the situation involves putting cosmetics on the face, using fEMG is not appropriate. If the consumer will be wet during the measure, then electrophysiology may not be appropriate. What is appropriate is making sure to use the right tool for the right question and having a variety of tools to access is very helpful when designing appropriate consumer research.
Understanding the limits of the measures themselves is important as well. It is not currently possible to read the mind using neuro tools, at least not in the way that is typically suggested. We can recognize patterns in physiological reactions that may help us predict what the consumer has experienced; however, this is not the same thing as reading the consumer’s thoughts. Further, there is no “buy button.” Neuro measures cannot help clients ensure that consumers will purchase products. They can measure experiences and reactions in a way that can help guide optimization, but again, this is not the same thing as being able to direct the consumer’s mind.
Neuro measures should for the most part, not be performed in group settings like focus groups. While it can seem appealing to measure multiple people sitting together, it is nearly impossible to determine what the consumer is reacting to – the product or the shoes that the person next to them is wearing or a cough that happens during the session.
It is difficult to use neuro measures in a real life emulating way. By design, the use of neuroscience requires a more controlled experimental environment. Measuring consumers in a noisy, real life environment will make it difficult to determine what is causing the consumer to react. More importantly, the natural environment makes the results less generalizable and more qualitative in nature (each individual would inherently have a different experience if being measured walking through a store, and so it would not be possible to aggregate the data in any statistically meaningful way). However, this can be fine if the client is okay with qualitative results.
Finally, there is a degree of error in every measure. However, this can be adjusted for by having a tightly controlled experimental design and strong statistics with relevant sample size to ensure valid results.
As I like to say, if your research provider cannot tell you the limitations of their measure, then you shouldn’t trust your research provider.
When is the “right time” to use these measures in the product development process?
The right time to use a neuro measure is when you have a question that is difficult to ask in a survey or difficult for consumers to articulate. Also, neuro measures can be best used to provide additional insight beyond traditional measures for addressing pain points or typical problems in the product development process.
How do I know which projects would be a good fit?
As a research provider that uses a wide array of methodologies and technologies, we are keen on using the right measure for the right question. Not all questions can or should be answered using neuroscience. Applied consumer neuroscience is not meant to replace traditional research. Rather, it is meant to supplement and complement it.
A few questions to ask yourself when contemplating using neuroscience:
- Can I just ask the consumer?
If the answer to your research question is something that can be articulated by consumers, then by all means, save yourself time and money and simply ask your consumer. When your question isn’t easily asked or easily answered, then you should add neuro measures. For example, it is easy to ask and answer “Do you like it?” However, it can be difficult to compare similar products and ask the question again hoping to get a differentiating answer. Another example of a difficult to ask and answer question is “Is it appropriate?” This can be a difficult concept for consumers to verbalize or understand when judging a product. In this case, it can be helpful to use implicit or non-verbal measures.
- What is my sample?
If you are looking for a large sample size for a broad and general population, this may dictate the type of measure you use. For example, it may be prohibitive to use costly or time consuming measures like EEG, fMRI or other physiological measures where homogeneity of the sample is necessary and sample sizes are small. However, if you still need non-conscious or implicit measures, other methods like Implicit Response may be appropriate.
- What is my timeline and budget?
As there are many different methodologies that can be used, important factors that can help you to determine which methods are best for you may also include how quickly you’d like results and what the total budget is. Methodologies like fMRI are very expensive and require more time to run, while online implicit tests like IATs can be run rather inexpensively and quickly. Taking into account both your specific research question and business needs, we at HCD like to offer a range of options to our clients so they can make the choice that fits their needs best.
What is the difference between facial coding, fEMG and EEG? How do I know what the best method to use is?
Facial coding relies on recorded video of the face and then categorizes different facial expressions into coded emotions (happy, sad, surprised, etc.). You can read more on facial coding on our previous blog post (http://www.hcdi.net/is-facial-coding-a-valid-means-of-collecting-emotional-state/ & http://www.hcdi.net/face-value-theories-of-emotion-and-their-application-to-neuromarketing/ ).
fEMG, facial electromyography, relies on electrodes placed on muscle groups on the face in order to record positive and negative emotional valence. There are sets of muscle groups associated with positive or negative emotions and the electrodes measure the changes in electrical activity of these muscles, their movement. This measure is similar to facial coding, but more sensitive. Instead of being categorical (fitting reactions into boxes), fEMG is linear, meaning it rates the amount of activity on a scale of more positive to less positive emotional reaction. Combining this method with other physiological measures for arousal (GSR) and motivation (HRV) provides a means to get a very sensitive measure of emotional state.
EEG, electroencephalography, relies on electrodes placed across the skull to measure changes in electrical activity in the brain. This can be a very sensitive measure of motivation, or as some people theorize, emotional valence (though this is in debate). There is a range of quality of EEG. There are cheaper headsets using “dry electrodes” as opposed to the more reliable and sensitive “wet electrodes”. The difference is that wet electrodes use a gel to help conductance, making for a clearer signal being measured while dry electrodes may record a significant amount of noise or unwanted activity. This difference is very important to remember when interpreting data, especially for the reason these cheaper EEG headsets tend to use fewer electrodes, making it more debatable as to what is really being measured or where that measure is coming from. It is also important to remember that research using EEG needs to be very clean, as electrical pulses are generated for every eye blink and breath that a person takes. Therefore it requires careful research design to ensure it is a valid measure and that you are measuring what you think you are measuring.