All posts by Michelle Niedziela, PhD

Neuromarketing: Identifying The Fact From the Fiction

One of the striking narratives that plagued 2016 was the emergence of fake news. With the decline of the newspaper and growth of viral news, more people are getting their information from social media rather than the older, reliable news sources. Many are quick to accept what they read online as fact, and even more don’t even read past the headlines or check the news source before accepting the message. The growth in fake news has been so large that it may have even influenced the 2016 presidential election.

Fake news, however, is not the only problem. There has also been an emergence in the spread of pseudoscience. Pseudoscientific news ranges from the hilariously ridiculous (Big Foot sightings) to the dangerous (homeopathic cures for cancer).

Unfortunately, the persistence of fake news and pseudoscience affects not only our entertainment, but can also have legal ramifications (http://www.telegraph.co.uk/technology/11834670/Woman-who-claimed-she-was-allergic-to-Wi-Fi-gets-disability-allowance-from-French-court.html).

Neuromarketing has seen its fair share of pseudoscience. There are no easy to use gadgets that can “read consumers’ minds.” The human brain is far too complicated to be reduced to a simple piece of plastic sitting on top of your head (that’s not to say that physiological measures can’t tell us something about consumers’ reactions to products and communications, but that’s not the same as mind reading).

If you are looking for a simple solution like that and are not interested in its legitimacy, let me redirect you to here: https://www.google.com/search?q=mood+ring

Perhaps a great New Year’s resolution for 2019 is to be sure to think critically and dismiss fake news and pseudoscience.

But how can you identify neuro-fact from neuro-fiction?

My first piece of advice is to know that there is no ONE perfect tool for studying human response. Different research questions and settings require different methodologies and technologies. So if your research provider is suggesting that their widget can do everything anywhere, you are dealing with a widget salesperson that will only ever sell you a widget, not a scientist helping you to understand your consumer. And to that point, if your research provider cannot tell you the limitations of their widget, then they are not being honest with you.

But when seeing “scientific” news about neuromarketing, here are a few steps to help you to sort through the muck:

  1. The use of Psychobabble Psychobabble is the use of words that sound scientific, but are not. Neuromarketers have ahabit of tagging the word “neuro” in front of anything to make it sound like real neuroscience. The use of these neuro-words or neuro-brands is really no more than “neuro-hype.” Often these words are really just a marketing scheme to get you to believe in a product or company.And while it’s just a name, this is why we at HCD prefer to use the term “Applied Consumer Neuroscience.” We believe this better describes the process of using a combination of neuroscience, psychology and traditional consumer research methods to better understand the consumer experience. Sure it’s just a name, but we don’t believe that neuro- measures are meant to replace traditional research and instead suggest that the addition of neuro- measures is an evolution and advancement to the already existing field of market research.
  2. Reliance on anecdotal evidence In place of published studies, many neuromarketing companies offer case studies and most do not validate their tools or methods with any scientific research. If you are not paying for a validated tool, then what exactly are you paying for?Many people become interested in using physiological or neuropsychological measures because they believe it will be more accurate than traditional measures. They believe that participants won’t be able to lie as they might on a survey or that difficult to articulate emotional reactions may be revealed through neuropsychological measures. And while that may be true, anecdotal evidence is not evidence. Any new measure or new application of a neurological tool must be validated before being used (and sold).While case studies can be very informative and lead to great research ideas, thoughtful research must still be done to validate a methodology. For example, in the world of pharmaceuticals this is very important. Just because one participant given a drug may have improved more than when given a placebo does not mean that the drug should be approved. It still needs to be thoroughly tested; otherwise you risk relying on a false positive result.Many neuromarketers provide anecdotal evidence as proof that their tool works. However, I suggest that if your research provider cannot provide you with real evidence (published peer-reviewed papers, or at least blinded case studies with real statistical analyses), then you may best be cautious. Buyer beware.
  3. Extraordinary claims in absence of extraordinary evidence The human brain is a complicated organ, so complicated that it can’t be duplicated and many aspects of it are still not understood. Academic neuroscience, for example, is still trying to explain even simple, vital, everyday things we do such as eating (see recent publications here: https://www.ncbi.nlm.nih.gov/pubmed/?term=food+intake, at time of writing, 187,055 recent publications still can’t tell us why we eat or stop eating).So when I see a claim that says that this or that tool or approach can “read the subconscious” or predict a complicated behavior like consumer behavior, I raise an eyebrow. Unless they can show you the evidence that the measure is linked to a behavior, then this is not predictive. It is imperative that neuromarketers do the background research in order to prove that their tools can be used in the specific ways that they claim, rather than just what sounds interesting.
  4. Claims which cannot be proven false When making claims about neuro- methodologies, researchers often fall into the trap of hindsight bias.  Hindsight bias (https://en.wikipedia.org/wiki/Hindsight_bias) is the research mistake of asserting that your finding is true and predictive after the event has occurred. It’s the act of seeing the final score of the Super Bowl and then telling everyone you predicted it before. No one can prove that you didn’t and it can make you seem very smart. But it hinders the scientific process of moving the neuromarketing field forward. If we are not using real findings and making real discoveries, then we are not really accomplishing anything of value.But more importantly, this doesn’t help our clients.The problem with this approach is that it doesn’t give credit to what applied consumer neuroscience is best used for: helping us to better understand the consumer. It’s not a replacement of current market research methodologies. And so being directly predictive of something that could have just been asked is not helpful. But when used as an addition to instead of replacement of traditional measures, applied neuroscience can be a valuable complement to current research.The question then is not whether neuromarketing could have predicted liking. If we want to know if someone liked something you can simply ask them. The better research question for applied neuroscience is ‘why do they like it’.
  5. Claims that counter scientific fact Again, it’s not currently possible to “read the mind” with any tool. However, there was a recent academic study that got close (sort of). fMRIs were done on participants as they viewed a movie. Participants watched the same movie for 3 months. After 3 months of training on the same movie, researchers were able to identify which movie the participants viewed by identifying a similar pattern in brain activity. But this is not the same as “reading the mind”. They trained people to exhibit a response and then identified that response in testing. Further, it is known that certain patterns are identifiable as synchronicity rhythms in brain activity due to blinking that is often caused by the phrasing used in cutting scenes together. Definitely not mind reading.

    Brains are really complicated (neuro-understatement of the year). They control our breathing, eating, standing, walking, etc., and so on… everything. So there’s a lot going on up there even when we don’t appear to be doing anything but sitting quietly and still. So imagine the amount of activity happening while you are walking through a store. Now imagine how differently your brain might look than another person’s brain might look as they walk through a store. You might hear different sounds or different people. Your experiences would be different and so activity in your brain would also be different. This makes studying this sort of behavior with neuroscience tools very difficult. The acts of walking and breathing and staying upright (balance) are very complicated things we do without having to consciously think of them. But these acts require a significant amount of brainpower, causing a lot of noise in the data if you are not interested in how well someone is walking, but interested in what they are seeing in a store. Real-time, naturalistic experiences are not well suited for neuro-measures and require a great deal of attention to proper research design. This is the fact of the situation, and if your research provider ignores these facts, again, buyer beware.

  1. Absence of adequate peer review One of the biggest problems in neuromarketing is the absence of peer review (though some are trying to correct this problem). The scientific method is clearly about testing hypotheses. But even further, it’s about replicating results and presenting your research to the  larger scientific audience for critique.
    However, criticism is not something that the many in the neuromarketing community encourage and the lack of a legitimate scientific peer review process for proposed methodologies has allowed many companies to get away with peddling non-validated widgets unchecked.Because neuromarketing companies don’t provide the key details of the analysis techniques they use, it’s hard to evaluate them objectively.
  2. Claims that are repeated despite being refuted If it sounds too good to be true, it probably is.While it would be amazingly convenient to measure neuro- responses while a consumer walks through a store, this simply is not a valid methodology.  While it would be great if we could really read the mind, it’s simply not that simple. As discussed earlier, the brain is complicated and so when we measure it we need to do so using validated tools and thoughtful research design. It is possible to use applied neuroscience to better understand consumer response.Making claims from brain response is highly difficult. Labeling a set of brain data as a signal of attention or anxiety based on one set of data is similar to saying “tomatoes are red, this apple is red, therefore this apple is a tomato” and continuing to state that an apple is a tomato despite evidence to the contrary.We see this in neuromarketing frequently, probably due to the lack of a strong peer-reviewed scientific process and the drive to sell methodologies. For example, while academic research has found that social setting (whether in presence of another person or alone; see research: http://psycnet.apa.org/journals/dev/32/2/367/, http://psycnet.apa.org/journals/emo/1/1/51/) can influence facial emotional response, many neuromarketers use facial coding in group settings such as focus groups.

    Unfortunately, there is a tendency of neuromarketers to keep methods secret, therefore, hampering serious evaluation. This does not, however, mean that all the data is bad. With a properly designed study, it is possible to look for meaningful (statistical) changes between stimuli or products, as well as look for meaningful changes from baseline measures. And it’s possible to make inferences from those changes in a well designed study, but those claims need to me made cautiously and be backed up by research.

So let’s all resolve to do better in 2019.

As always at HCD, we are happy to spread knowledge about our measures and will continue to do so in 2019!

Is facial coding a valid means of collecting emotional state?

Cheaper, faster, better. This is what we want and we want it now. But what is best is not always what is fast or cheap.

Facial coding is a popular method for collecting the emotional reactions in “neuromarketing” work and was recently featured in a WSJ piece, The Technology that Unmasks Your Hidden Emotions. The article focuses on the uses of facial coding in assessing consumer emotional response as well as potential abuses of the technology concerning privacy and public safety. These are definitely important issues. But it’s even more important to take a step back and think about what the technology is and should be useful for.

Can it do it? Yes… sort of.

Facial coding or FACS (facial action coding system) was first developed by Carl-Herman Hjortsjö and then later adapted by Paul Ekman as a means to record and categorize facial expressions to describe emotional response. Originally, these responses were coded and interpreted by people, making for very subjective data. Ekman’s work used 3 HD video cameras to get clean readings from people’s faces in controlled experimental settings.  However, more recently computer automated programs analyze video-captured responses, as used by companies like Affectiva and Emotient. So it may be a good option so long as you don’t mind having to throw out a significant amount of bad data and over-recruit to make up for it (one must wonder the importance of the data points that get thrown out and if that skews the results).

Being able to capture consumer responses via quick videos (like surveillance in stores) and webcams is certainly an attractive idea to marketers. It’s cheap and it’s fast. But is it better than other methods? The WSJ article missed this important question, instead stating that it’s the best.

Facial coding certainly has its advantages for certain situations, consumers or questions, but definitely not for all. There are, in fact, a lot of different methodologies and technologies that can be used to measure consumer emotional response and a lot of situations where it may not be the best choice at all.

In fact, the very theories that facial coding is based on are still hotly debated. Ekman claims that there are 6, maybe 7, universal emotions: anger, disgust, fear, happiness, sadness, surprise, and contempt. Contempt, as a universal emotion, is less clear in the research and debate over the universality of the other 6 are also in question after several new papers came out this past year questioning the theory.

The real problem comes in when thinking of the practicalities of its use in market research. One already mentioned is the data throw-out rate which brings into question the validity of the data collected. But further, given the categorical nature and variable technology (webcams, single low-definition video), the sensitivity of facial coding may not be as good as other methodologies.

This can mean that if you want to check the performance of a product, you may not be able to tell the difference between reactions from two similar products, like fragrance or color of a lotion. Other methods, like fEMG (facial electromyography), measure the electrical changes in the facial muscles, heart rate, and skin conductance directly and are therefore more sensitive to subtle changes in emotional expression that may not be visible via camera. Further, using multiple methods to measure experience gives a more complete insight into the emotional experience. Being able to differentiate products and experiences in this way allows for meaningful and actionable conclusions.

Ekman says “Emotient’s software is highly accurate, but the accuracy of the system hasn’t been independently tested," as stated in the WSJ article.

Additionally, we know from our own research that people do not experience all the possible emotional reactions at the same time.   Emotions develop over an experience and that development can be just as important, if not more important, to a product designer or brand manager than the global or initial response alone. As stated in the article: "Ken Denman, CEO of Emotient, says his company makes a point of discarding the images of individual faces within seconds after it has logged the sentiment they express. ‘There’s very little value in the facial expression of any individual,’ he said.” Unfortunately for this approach, humans simply aren’t this simple.

Example: Fragrance companies are great at making well-liked fragrances. So if you ask people to smell them and rate them, they will say they like them all. Now if you have 6 well-liked fragrances but need to choose only 1 for your product improvement, which do you choose? By using a multidimensional approach you can diagnose the differences (one may be slightly more arousing, or more comforting, etc.).  Furthermore, by tracking those changes over time with a well designed psychological paradigm, you can get rich results that help a brand manager understand why one is better than another.

And yes, it may be argued that each has its best place. At HCD, we strongly believe that many validated technologies exist that have advantages and disadvantages depending on the question being asked. Facial coding may be easily used for gauging global "emotional" reactions to commercial watching or group behavior where accuracy loses to speed and large groups.

Other restrictions may also apply with any technology that is used, such as how well the technologies work together. In most situations, more than one technology is required to understand the consumer experience and so those technologies must work well together. For example, if you want to gauge the reactions of a person walking through a store, we would recommend using eye tracking to see what the consumer sees and focuses on in the experience. In that situation (walking, interacting), you would need eye tracking glasses, obstructing facial coding video collection, making this approach difficult – if not impossible.
It’s really a question of quality over quantity and the old saying that you get what you pay for.  One thing you will notice when looking at the results of neuromarketing studies is that most of those "findings" are things you could have either gotten from your traditional measures (simply asking) or by rational hindsight generalizations or educated predictions. Recent headlines have included revelations like “sex sells” and “puppies make people happy”. We don’t find that kind of insight to be useful to clients.  They need something more than that for the cost of the work to be worth it as well as useful.
“Neuromarketing” or consumer neuroscience shouldn’t be about “reading minds” or replacing traditional methodologies. Real and thoughtful applied consumer neuroscience is about using the right combination of sensitive physiological measures from psychology and neuroscience so we can get at the "why" of consumer behavior and this is something that can be most useful for making better products.

HCD On The Road:  Debunking Neurohype

For the past year or so (starting at Pangborn 2017), I’ve been sort of on tour discussing the trials and tribulations of using applied consumer neuroscience.

I’m calling it my manifesto, where I’m basically burning down my own house.

You see, my background is in behavioral neuroscience. My undergraduate degree is in psychology, PhD in behavioral neuro-genetics, and my postdoctoral research focused on sensory perception. I’ve been passionate about research and science my whole life. For the past 10 years I’ve worked as a student mentor and have judged several high school and middle school science fairs. I speak regularly on topics of science in industry as well as write my own blog and magazine columns.  When I speak to student researchers, I always focus on proper scientific method use and scientific integrity.

When I entered the industry, my first job was to act as the scientific lead for external research/innovation at a large CPG company. Basically, it was my job to work with external research providers and vet out their methodology and conclusions, mostly around using what is now referred to as consumer neuroscience, but back then, it didn’t really have a name.

I now work on the other side of things as a research provider. And as chief methodologist and VP of research and innovation at HCD, it’s really my job to ensure we are working as hard as possible to do things correctly.

And so it has really pained me to see how this field has developed. When I speak my manifesto at various market research conferences, I start with a question:

How many of you have heard about neuromarketing?

And of course, many have. In fact, typically there are many other talks at these conferences on the topic. You may see them with key words like “System 1” or “consumer neuroscience” or “implicit” or “behavioral economics.” The name changes with what is currently popular (from neuromarketing to now System 1) or trending.

And so then I ask another question, how many of you are skeptical of neuromarketing?

And to this, many hands will go up.

Why so cynical?

Well, potentially for good reason. What started out as an interesting concept has turned its course a bit. Published in 2011, Kahneman’s book Thinking, Fast and Slow has become dogma to neuromarketers, dividing consumer decision making into two processes: System 1 and System 2. System 1 being the fast and emotional reactive decision-making process and System 2 being the slow and deliberate, purposeful decision-making process (*this concept isn’t all Kahneman, and in fact, can likely be traced back to Plato’s Chariot Allegory or maybe even Freud’s Id, Ego & Super Ego). Or an easier way to consider it, when car shopping, perhaps your System 1 is excited by a shiny, red, convertible sports car while your System 2 is more convinced by the more reliable, more appropriate, compact sedan.

Far too often neuromarketers propose that marketers and market researchers should forgo System 2 and focus on System 1. And those of us who are familiar, know that marketers have being targeting the consumer “id” for a long time, this is nothing new. But does it work? If we revisit the car purchasing scenario, sales of compact sedans far outnumber sports cars. Why? Well, as attractive as a flashy sports car may be, when we make our final purchase decisions, we ultimately rely on what is most practical. With work commutes and budgets, the compact sedan ends up being the better choice in most cases.

Once upon a time, a neuromarketer tossed out a number: 90% of all purchasing decisions are made subconsciously. It sounds great, but it’s total fiction. It seems to stem from the idea that we only use 10% of our brains for conscious thought and all else (95%) is non-conscious. Of course, this ignores the fact that our brains are mostly involved in maintaining body homeostasis (breathing, cardiovascular functions, balance, hunger, thirst, etc.). The stat is often credited to Martin Lindstrom, in reference to mirror neurons, or sometimes to Dr. Gerald Zaltman (with no real agreement on who owns this number); however, no actual evidence exists proving that this statement is true. Unfortunately, it’s also impossible to prove incorrect because you can’t prove the negative.

That’s not to say that System 1 (or non-conscious) style thinking is useless when considering consumer appeal. In fact, a lot can be learned from what activates System 1. However, a neuroscientist or psychologist would not view consumer behavior as divided decision-making processes. Instead, they would more likely view the consumer experience and decision-making process on a continuum or process of thinking.

When you think about how people interact in the world and the environment around them, you will see that it isn’t a completely divided process. Certainly, there is a “non-conscious” and “conscious” in that there are sensations of which we are not consciously aware and sensations of which we are aware. The example I like to use is the behavior of answering your cell phone. When your cell phone rings, the hair cells in your ear react to sound vibrations and send a neural signal to the brain. This happens without you being consciously aware of the sound quite yet (non-conscious). But as your brain receives the signal, it classifies its meaning and value and then deliberates on that information (as you become more conscious of this effort) to finally decide (consciously) how you will react.

The value in measuring non-conscious reactions is that by better understanding of the non-conscious response we may be able to influence the cognitive behavior. For example, changing the tone, pattern or length of the ring tone may influence how quickly you respond to it, or changing the color of a package may influence perceptions of a product.

Using The Right Tool For The Right Question

And this is where my manifesto becomes a bit more controversial, addressing the misuse and bad science methodology and technology. By calling out the misuse of the most common tools, certainly I’ve managed to anger a few companies that rely on using those tools in their research. But I’d like to stress here that it isn’t that the tool itself is bad, in fact, I do say that the tools do exactly what they are supposed to do. Humans, however, are more often the problem, overinterpreting results or designing studies incorrectly.

The image above is directly from my presentation. In it, I describe the methodologies on the left being more reliable and those on the right as being less reliable. On the left, more reliable side, I start with the “gold standard” biometrics measures (fEMG – facial electromyography, HRV – hear rate variability, GSR – galvanic skin response). These are considered gold standards mainly due to their simplicity and direct correlation to what they measure. For example, increases in GSR are directly and positively correlated to increases in arousal. Similarly, eye tracking is a direct measure of gaze behavior, and implicit reaction measures are directly correlated with association. However, I set eye tracking and implicit reaction slightly more to the right (less reliable) side because there is room for misinterpretation and misuse. For example, far too often eye-tracking behavior is attributed to attention when in fact it is possible to be looking at something but not paying attention. There have also been cases of improper design in implicit reaction studies that make their results less reliable. Further to the right of the image, you may be surprised to see EEG and fMRI. Arguably, these methodologies are more consistent of what we think of when we think of using neuroscience in research, and they have been wonderful tools in academia. However, their application in industry research is often plagued with improper research design. For example, extrapolating emotional conclusions from EEG or fMRI work is not as simple as it may seem and typically requires evoking the reactions, not passive measurement. Thus, this step has often been skipped in industry use, making the conclusions hazy at best and total false at worst. Further, fMRI studies are notoriously expensive and difficult to perform in the confines of consumer research. Perhaps most controversially, I placed cheaper EEG headsets and facial coding at the far right end of the reliability spectrum. Both are cheap solutions to adding neuroscience to consumer research, but as one would expect, you get what you pay for. Cheaper EEG headsets mean a poorer signal thus, more difficulty in interpreting already difficult to interpret results. And in our opinion, facial coding is not nearly as useful as it is being sold to be, as its proponents often neglect to reveal its limitations (socially driven reactions, dropout rates, interpretations, etc.).

However, I do want to stress that it is not the fault of the measures. It is perfectly reasonable to use any one of these measures as long as you are clear on all the limitations AND use them properly.

Ultimately, there is no one tool that will cover all research, and so we must be willing to accept that certain tools are better at collecting certain types of information over other tools, and that we must be sure we are using the right tool for the right measure.

The Scientific Method. So when I talk about design problems in research, I’m talking mostly about people not following the scientific method. Most of us learned this process in elementary school, but I’ve updated it here for industry research purposes

  1. Make an Observation – this would be the scope of the research.
  2. Develop Research Questions – this step is most often skipped, unfortunately. We find it is best to identify current problems in Step 1 to revisit as research questions for step 2.
  3. Formulate Testable Hypotheses –this step is also frequently skipped, but very important as it helps drive which methodological approach will be most appropriate.
  4. Conduct an Experiment – specifically, design an experiment to test the hypotheses from step 3 using the most appropriate methodologies and minimizing confounds.
  5. Analysis – use the appropriate statistical methods to show real differences and effects.
  6. Conclusion – interpret the data as is, based on the limitations of the method and avoiding over-reaching claims

It sounds simple, and yet appears to be rarely followed when you see presented case studies. Far too often, there doesn’t appear to be any research question beyond wanting to add a neuroscience technique. Which is, of course, fun but…

While it’s great to use all of these scientific tools and be on the cutting edge of technology, it’s important to take a step back and think about what you are ultimately trying to accomplish. It’s my firm belief that if you can just ask someone, then just ask them. If the question is about liking, for example, you are much better off simply asking consumers if they like the product. Consumers are actually quite reliable at knowing whether they will purchase something or if they like something. So really, that’s not what the technology should be used for, and is in fact, not great at doing such. While skin temperature has been positively correlated with liking of different tastes, it is far more reliable to just ask the consumer. Neuroscience and psychological methodologies should, instead, really be used for measuring items beyond liking, to better understand the drivers of liking.

So while some research providers claim that you can’t trust consumers to tell you what they really think, I don’t agree that is necessarily true, although it makes for a very convenient story. The truth is that consumers can tell you what they think if you ask them correctly and neuroscience really isn’t a great tool for lie detection (except for pupil dilation which has some reliable correlation to lying).

So what can you do?

I suggest following a few rules/guides to help decide how to use both neuroscience and a potential neuroscience provider:

  1. Start with the research question.While it is often attractive to passively measure consumers in a naturalistic environment, and there certainly can be exploratory ideas uncovered in observational research, in order to get the best and most actionable results for applied neuroscience, you should really consider what the research question is. Do you need to compare prototypes to a benchmark product? Do you need to show more engagement with a particular communication? Starting with the research question will help guide the scope of the study and the approach of the method.But often, clients don’t have a clear research question outside of pressure to implement implicit or System 1 research. And so to help our clients, we suggest a few ideas to guide research question development:
    • Identify your current research pain point? Are there any areas of your current research which leave knowledge gaps? Are there areas in your current research that are not clear or provide incomplete results?
    • Who are we studying? Current brand loyal users? General populations?
    • What are the action standards? To approve this prototype, in what ways should it be different from the current product? Does it need to perform better in some aspect than a competitor benchmark?
  1. Always use the right tool for the right question.Once you have the right question, it can be a lot easier to choose which research tool will best provide an answer. This is a much more productive and cost-efficient approach than starting with a tool and looking to apply it somehow. For example, if your research question is about whether a new fragrance helps to suggest that the product is more “spiritual,” facial coding will not be able to help you, but implicit reaction may be able to help.And this is why it is important that your research provider be “methodologically agnostic.” Or as I often say, if you go to a widget salesmen he is going to sell you a widget and not something else. If the research provider is a “one trick pony” or only has 1 methodology to offer you, he likely won’t be trying to tell you about the limitations of that method.So how can you identify a good research provider? I suggest asking a few targeted questions about the limitations of the proposed methodologies. And if they can’t tell you about any limitations or suggest that there is one solution to fit all needs, then likely they are not a great research partner.Further, if the research provider does not suggest that proper research design needs to be followed, this may indicate they aren’t being entirely truthful. A major problem in using neuroscientific and psychology methodology is that it does require a level of experimental control to reduce noise in the test, to make sure you are measuring exactly what you say you are measuring. So if there is no effort to establish this, then again, likely they are not a great research partner.
  1. Build a story with multiple research pointsNeuromarketers often try to say that consumers’ cognitive responses can’t be trusted and that neuro measures are somehow more truthful. However, we assert that neuro measures should never be performed or relied on alone, nd that neuro measures should always act as a supplement to cognitive research. The reason for that is that neuro measures are not a replacement for cognitive or more traditional measures. They don’t answer the same questions. So instead of trying to prove one of them better or wrong, we would suggest that you use them both to be able to view the consumer response with “both eyes open.” By understanding both the cognitive and non-cognitive consumer experience, we believe we can help our clients better communicate with consumers and design better products.We suggest that instead of trying to make neuroscience data stand alone, you should supplement current research with additional insights from neuroscience and psychology. And that by integrating the data (either in story or through statistical modeling), it is possible to make better and more actionable, informed conclusions and interpretation.

Final Thoughts

In giving this talk during the past couple of years, I’ve been overwhelmed with the positive responses I’ve received from people on both the end client side and the research provider side. End clients have often said they were disappointed with results they’ve gotten from neuromarketing studies and were glad that it wasn’t because the science was bad, just misused. Research providers have been glad to hear that others in the industry saw the problems and were speaking out about them.

At one conference, I witnessed a research provider being called out. An audience member asked him how he had validated his methodology, and his shocking response was, “that’s not my job.”

It is the job of the research provider to use reliable, validated methods and technologies. The client-provider relationship is one of trust, and so we must do our very best to nurture that trust with full disclosure regarding the limitations of these tools.

I’m happy to report that since giving these talks, I’ve noticed more providers posting blog posts speaking critically about their own methodologies and the field in general. While it is important to always push the limits and create new and innovative applications, we must, most importantly, stay scientifically vigilant and maintain scientific integrity.

That being said, I’m certainly open to any discussion about any methodologies. While I know a lot about some specific things, I certainly don’t know everything. So I’m more than happy to have more conversations about any methodologies and uses and abuses in the research field.

Remember, the first rule of the Dunning-Kruger club is that you don’t know you’re a member of the Dunning-Kruger club.

When Neuromarketing Meets Academia: My recent talk at the Society for Affective Science 2017 Boston

This past month I was honored to be invited by Herb Meiselman to speak at the Society for Affective Science meeting in Boston. Herb, David from MMR, and I presented a panel on industry applications of emotional research. Our goal was to engage a predominantly academic crowd focused on the study of emotion in a discussion on how emotional research is being used in consumer science. We had a decent crowd attend our discussion, mostly out of curiosity (unfamiliar with industry research) as well as a healthy dose of skepticism.

Dr. Herb Meiselman speaking about measuring emotions in consumer products.

Herb shared some very interesting points about the differences between academic emotion research and consumer emotion research. For one, academic emotion research focuses on more negative emotional words than are found to be useful in consumer research. Consumer products are mainly designed to delight consumers, therefore traditional academic emotional batteries may not be the best fit for consumer research as many of the words reflect negative emotions (more prevalent in psychological research).

I find this idea particularly interesting on a more theoretical basis. First of all, I find that there is a huge misconception in the industry when it comes to emotion. Most people aren’t aware that a first step in emotion research is to define what is meant by emotion. This is because there is no set definition of emotion. Instead, there are many different theories and many different approaches to defining emotions and emotional response. Neuromarketers rely on defining emotion as a non-cognitive, non-conscious state of feeling resulting in physiological and psychological changes that influence behavior. However, this is not the only definition in academia. Some view emotion as a largely cognitive process. This is because, while emotional responses may seem non-cognitive or without thought, mental processes are still essential, particularly in the interpretation of events.

Neuromarketers follow Kahneman’s theory of decision making, dividing up the decision-making process into System 1 (the non-conscious emotional response) and System 2 (the cognitive rational response), with System 1 being behind consumer decisions. This theory appears closely related to Freudian Theory where the unconscious mind (id and superego) govern over the conscious mind (ego). Neuromarketers believe targeting System 1 (or id) encourages consumer purchase and interest.

Emotions are complex and other theories focus on how to define the emotions themselves. The Basic Emotions approach (Ekman and Plutchik) follows a categorical method for defining emotions, where the 6 basic emotions (anger, disgust, fear, happiness, sadness, surprise) are discrete (not related to one another), measurable, and physiologically distinct (often measured via facial coding). Ekman later added contempt to the basic list to make 7, though this is still under some debate. Plutchik has a slightly different list of eight primary emotions grouped by negative/positive opposition: joy versus sadness; anger versus fear; trust versus disgust; and surprise versus anticipation. So even within a theory, there is some disagreement on definitions.

Plutchik’s Wheel of Emotions

Another approach, the Multi-Dimensional Model of Emotion, defines emotions as riding along multiple vectors: positive to negative; arousing to relaxing; motivating to avoiding. In this approach, each emotion is seen as a point (or more like a general area) in a 3-d (or 2-d) space varying on levels of emotional valence (positive/negative), arousal (arousing/relaxing), and motivation (approach/withdrawal). Each emotion consists of a set of components. For example, anger is a combination of negative valence, arousal and motivation, while fear is a combination of negative valence, arousal and avoidance.

Academics are aware of these issues. They know that emotion is complicated and difficult to measure. And they know that in the sphere of decision making and consumption, it only gets more complicated. And they continue to push basic research for better understanding of human emotional response. For example, one talk that I attended at the meeting discussed the role of the vagus nerve in emotion. The vagus nerve is the 10th of 12 cranial nerves (nerves that emerge directly from the brain to the body). It controls and senses physiology relating to the heart, lungs and digestive tract, and it happens to have been the focus of my dissertation! The talk was titled, “Why Should Emotion Researchers Care About the Vagus?” presented by Dr. Julian Thayer from Ohio State University. Researchers (both academic emotional researchers and neuromarketing researchers) should care about the vagus nerve because it controls many things in the body, but in particular, it is involved in physiology directly linked to emotion, including heart rate variability (HRV) and brain response. This is very important for those of us who use HRV and/or EEG and is why I always stress the importance of proper research design and cautious analysis and interpretation of results. As Dr. Thayer reported in his talk, different people can have different physiological responses based on race, gender, physical fitness and even past traumatic experiences. These differences can change our vagal innervations, HR patterns and even cortical thickness. Without taking these things into account or at least understanding them, we risk misinterpreting the data.

The goal of my presentation was to address the skepticism from the academic crowd, specifically around using applied consumer neuroscience to study consumer perception and emotion given these issues (definitions of emotion and confounds of physiology). I wanted these researchers to know that despite the sensationalized headlines they may read about neuromarketing (often misuse of methodologies, over interpretation of results, exaggerated conclusions), many of us in the field are aware of the problems and are doing our best to correct them. We are fighting the good fight but need their help. I encouraged collaboration as well as opposition (for example what was done in this case: https://www.forbes.com/sites/matthewherper/2011/10/02/no-you-dont-love-your-iphone-in-that-way). The field of neuromarketing needs a healthy dose of skepticism, but it also needs help and guidance. I called out the great work being done by academic groups, like at Wageningen University, working to tease apart physiological responses to sensory stimuli, and a few of our own case studies.

We must continue to improve our methodologies and be cautious about our interpretations. We can’t read minds and shouldn’t claim to.

But we can offer insight into the consumer experience through intelligent research design.

While we at HCD employ a combination of traditional research (quantitative and qualitative methodologies) with applied consumer neuroscience, we also are some of the loudest critics when it comes to “neuromarketing.” Why? Because we believe in scientific validity in using the right tool for the right question.

Catch me at my next conference! I’ll be at Pangborn as well as Society for Neuroscience this year. Hope to see you around!

Connecting With Consumers: Communicating Through Packaging

(Part 3 in a blog series)

By Michelle Niedziela, PhD

This is part 3 in a blog series covering how we use consumer research to improve consumer products and communications.

In this series we will be discussing different methodologies and their applications including: traditional, psychological and neuro based research, claims communications and substantiation, packaging applications, user experience (UX) research, branding, etc.

When a product is seen on a shelf, it creates an immediate impression on the consumer. Immediate perceptions are communicated via the packaging and expectations are established. Therefore it is important to ensure that these initial impressions are communicated correctly.

At HCD we have assessed consumer reaction to product packaging by having the consumers see and hold products in packaging while we measured them physiologically using neuroscience methodologies. With a combination of psycho-physiological measures, traditional quantitative questionnaires and conjoint analysis, we have been able to understand the consumer’s experience as they encounter packaging elements (colors, images, logos, messaging, etc.). Our findings have been used to help identify elements of packaging that are working well (or not so well) at building a positive consumer experience and ultimately influencing purchase.

woman shopping

Brand perception is your first communication.

Understanding how consumers perceive your brand is paramount and a good first step in uncovering the unmet needs of a product or product line. Knowing how consumers perceive your brand compared to other brands can provide insight into consumer need gaps that can drive innovation and uncover innovation opportunities. Understanding brand perception is very important to package design. Once you identify the need gaps of your brand, it is then possible to create messaging and imagery on packaging to fill these gaps.

To uncover these unmet needs we collect consumer terminology around the product category through qualitative focus groups online. We then combine powerful tools from traditional market research to rank order these terms and attributes to uncover which are most important to consumer. Following that we then use implicit psychological measures to get valuable consumer understanding about the consumer product needs (Greenwald et al., 1998). Implicit measure gauge consumers’ associations with the brand. By testing the top generated terms implicitly, we can then identify which terms are, or are not, most associated with the brand or the competitors (figure below). This powerful combination of research tools informs us how brands are associated and fulfilling (or not fulfilling) these needs (need gaps). In the example seen in figure 1, the attributes ranked to be most important for this product category were: sweet, flavorful and refreshing. However, it was clear from the implicit testing that the client brand was not ranked highly for these attributes. This indicated some brand health issues: while developers were confident from consumer testing that the product was meeting consumer expectations, the brand was not. The disconnect between the product experience (positive) and the brand associations (low) suggested that there was a brand communication issue for this client. Upon studying the packaging, it was easy to find possible remedies for the situation, which we will describe below.

ranking 

Packaging real estate is a limited and valuable resource. Don’t waste it!

Real estate on packaging is highly valuable and limited and is the first explicit communication that a product has with the consumer. Therefore it is very important to understand how product labeling and packaging communications affect consumer perceptions. By combining traditional and physiological measures, we are able to demonstrate these affects.

Being able to assess the psychophysiological responses combined with behavioral measures such as eye tracking and/or behavioral analysis, we can then track consumer responses to specific elements of the package as they experience it.  In this way we can then gauge their reaction to package elements such as the brand logo, the package or brand messaging, product information, and imagery. For the example seen in the figure below, using this combination of methodology (eye tracking + psychophysiological measures) we were able to track consumer reactions to various segments of the package.

eye tracking

The logo for this package did not attract any visual attention compared to competitor packs (red-shaded box, fig. 3). This failure to engage the consumer indicates disinterest in the brand, which was also seen in the branding portion of the research described earlier (fig. 1). “New & Improved” messaging was completely ignored suggesting this is wasted space. We did see that meaningful messaging and communications on the package (green boxes, fig. 3) did attract interest and generate engagement. Therefore, we suggested to our client that if “new & improved” messaging was required, that it should be combined with useful and meaningful information to engage the consumer. In fact, the messaging on the pack was so effective that it elicited an effect we call “stopping power” – the ability to attract and engage the consumer in the product immediately and effectively, drawing the consumer in. Therefore, we recommended to this client that they move such effective messaging closer to the logo in order to create a “branding moment,” that would quickly engage the consumer with stopping power messaging and associating the brand with that message. Additionally, the product visual was positively engaging. When product visuals are used on the package it is important to capitalize on this engagement with the consumer by ensuring that brand logos are clearly visible on the product.

Holistic and cohesive communications in packaging is important.

Strong brand messaging and attractive packaging are key to enticing consumers to purchase products. It is important that the branding match the packaging and vice versa. However, if there is some disconnect between consumers and the brand, effective packaging can be used to bridge that gap. Therefore, it is important that key packaging elements (attributes) match the brand messaging and relate back to the brand (branding moments). But it is also important that those elements attract and positively engage the consumer (stopping power). Product consumer research examines how consumers perceive products holistically as well as by attributes. Understanding the impact of brand associations and packaging on consumers is key to winning at the shelf.

Real and thoughtful applied consumer neuroscience is about using the right combination of sensitive measures from psychology and neuroscience so we can understand the “why” of consumer behavior, something that can be extremely useful for making better products and packaging. In a larger viewpoint, it’s possible to see how understanding consumer needs for can help improve consumer communications.

Connecting With Consumers: Making Claims (Part 2 in a blog series)

This is part 2 in a blog series covering how we use consumer research to improve consumer products and communications.

In this series we will be discussing different methodologies and their applications including: traditional, psychological and neuro based research, claims communications and substantiation, packaging applications, user experience (UX) research, branding, etc.  

When making product claims, there are two important factors to consider:

  • How to substantiate your product claim
  • How to communicate your product claim

man_in_hat_winkHow To Substantiate Your Product Claim

You know all those claims you hear in TV commercials?

“9 out of 10 doctors agree…”

“Tastes better than the top competitor…”

Well, believe it or not, the product company has to be able to back up every word that they say. According to the FTC (Federal Trade Commission), under the law, claims in advertisements must be truthful, cannot be deceptive or unfair, and must be evidence-based. Companies making claims must show proof that their claim is true (especially health related products like drugs, dietary supplements, contact lenses, etc.).

So how to can you substantiate your claim?

Traditional consumer tests can help substantiate claims by providing answers such as whether people like one product more than a competitor (think the Pepsi Challenge – where participants were asked to blindly taste Coke and Pepsi and report which they liked better). In the case of the Pepsi Challenge, this was a taste test. Other types of traditional sensory tests (taste, smell, touch, sound, feel) can all be performed to show that consumers prefer one product over the other.

Other types of consumer tests may be more clinical in nature. For example, a clinical study may be used to show real improvements on skin after applying a lotion. Or participants may apply sunscreen to their arm and place it in a whirlpool to prove that it can last in water for at least 2 hours.

You can also use more sensitive measures, such as applied consumer neuroscience, to investigate more subtle differences and emotional effects.

Whatever methodology is used, the research results must be provided to the FTC and be statistically and scientifically sound.  This means no exaggerations or falsehoods can be claimed unless it is scientifically proven and that proof needs to be performed properly.

For example, if you want to prove that your yogurt tastes better than a competitor, but test your yogurt (a blended fruit yogurt) against another yogurt (fruit on the bottom, unblended) in an unfair manner (not presented in same way – blended vs unblended), then you are not being entirely truthful and your claim can be rejected.

How to Communicate Your Claim

cleaning_productsPerhaps just as important as developing valid claims is finding the best way to communicate those claims. Real estate on packaging is a valuable and precious commodity. There is no wasted space. Each graphic and communication must have an explicit purpose.

Further, time in a commercial is also a valuable and precious commodity. Within only 30 seconds, the advertisement must make its point in a meaningful, factual and engaging way.

man_on_tvPackage testing, shelf testing, and ad testing can all help determine the effectiveness of the communications that are being used.

In traditional research, liking scales, fit to concept questions, brand recall, and purchase intent can all be examined using surveys to assess the effectiveness of the communication.

However, we often recommend the addition of applied consumer neuroscience measures to truly examine the effectiveness of the communication. By adding the use of eye tracking, we are able to ensure that the consumers really see the communication. And then by assessing their engagement, emotional response and arousal levels via physiological or psychological measures, we are able to ensure that that communication is effective and engaging. But more importantly, we can use this information to provide actionable insights for our clients. For example, recommending moving communications to different locations on a package to achieve meaningful branding moments. Or changing the branding moments in commercials to ensure optimal brand recall and messaging.

But even further, we can use applied consumer neuroscience to ensure that the messaging fits to the brand or concept to help create a cohesive marketing communication.

By taking these extra steps, we can help clients build an optimized communication that gives consumers a reason to believe in their product. Because it’s not always what you say, but how you say it (or show it).

Connecting With Consumers: The How and Why of Consumer Science (Part 1 in a blog series)

This is part 1 in a blog series covering how we use consumer research to improve consumer products and communications. In this series we will be discussing different methodologies and their applications including: traditional, psychological and neuro based research, claims communications and substantiation, packaging applications, user experience (UX) research, branding, etc.

What is consumer science?

If you Google “consumer science” you will see a definition pop up stating:

Consumer science is a social discipline that focuses on the interaction between people and the environment. Some of the topics addressed by a specialist in consumer science are nutrition, aging, housing, food safety, community, and parenting. – via study.com/consumer_science_degree.html

If this sounds vague to you, that’s because it is. It seemingly would define consumer science as pretty much everything and anything. However, when speaking in terms of market research, marketing or product design, “consumer science” has a more important purpose. Consumer science can then be defined as a disciple of understanding consumer choices, behaviors/routines, and preferences in relation to products (including media, packaged goods, communications, food/beverage, user experience, etc.). The reason it is important for marketers and product designers to understand consumers is so they can ensure that their promises meet consumer expectations and thereby making better and more appealing products for increasing sales (and re-purchase).

How does consumer science or market research help both marketers and product designers?

A common tool used in consumer science is the survey. It’s how we can find out what consumers think about our product… it’s simple, we ask them.

Did you like this product?

Would you purchase this product?

We often ask these questions with statements and scales:

I would purchase this product.
scale1to7

The answers we get when we ask consumers what they think can be a great pat on the back for a job well done, or possibly a caution to go back to the drawing board to make improvements before releasing a product.

But often these types of surveys don’t provide enough information to make real decisions on product performance. This is because they do not tell us WHY the consumer felt this way. Yes, we can ask more questions: rate the intensity of the fragrance; check all emotions that apply to your experience; this flavor is appropriate for this product…

But these can all be difficult questions for a consumer to answer. Even the simple question “do you like this product?” can be difficult for the consumer to answer, but even more difficult for the product designer to figure out why they like or do not like it.

To solve this problem, qualitative research can be added. While survey/quantitative research can involve hundreds of consumer respondents to surveys, qualitative studies, like focus groups or interviews, may only involve 10 or 20 consumers. Using this approach, researchers can dive deeper into consumers’ thoughts and answers providing more information to add to the survey findings.

However, the problem with most qualitative methods is that they can introduce some influence or bias to the respondents, making it difficult for consumers to reveal their true feelings or reactions. Sometimes simply being asked by an interviewer may make the consumer feel judged or uncomfortable. Sometimes a consumer may feel intimidated by the opinions of others in a focus group. Sometimes the interviewer or other members of the focus group can sway the opinion of some consumers.

So is it possible to get to the true consumer reaction?

Whether it is survey or interview or focus group, these are all true consumer reactions. Can people lie in surveys? Yes, but that is why we aggregate the results of large groups for surveys. Can consumers’ answers be influenced? Yes, that is why having skilled interviewers or focus group moderators is essential to avoiding these problems.

So we do our best to make sure that we are getting the best information we can.

But another option is to not ask them at all.

Using applied consumer neuroscience (a combination of psychology and neuroscience methodologies for understanding consumers) can help us learn about consumer preferences, choices, behaviors, etc. without having to interfere with their thoughts by asking them. Or more importantly, it can help us understand the WHY behind consumer preferences, choices and behaviors.

And understanding WHY is how we can help our clients make better products.

Of course it is still important to ask the consumers, but by also observing them (through applied consumer neuroscience) and then marrying the two sides together, we can build a picture of consumer understanding that can ensure better connections, communications and creation of better consumer products.

HCD’s MaxImplicit™: Understanding Consumer Need-Gaps

This past week I had the opportunity to guest lecture for Dr. Boryana Dimitrova’s New Product Development course at the Lebow Business School of Drexel University. It’s always a fun experience for me to guest lecture. First of all, our field of applied consumer neuroscience (aka “neuromarketing) is relatively new. Not many students are familiar with the idea, so when they hear about neuromarketing, it’s always very exciting to see their reactions. For the few that have heard of this field of study, it’s always good to set the record straight on the difference between the pseudoscience, neuromarketing, neuro-hype and doing real thoughtful applied consumer neuroscience to provide real answers for real questions. (see blog post http://www.hcdi.net/applied-consumer-neuroscience-faq/)

womanIn preparing for this lecture it seemed a good time to write a blog post on how we help our clients identify innovation opportunities and consumer need-gaps (or areas where the consumers’ needs or expectations are not yet being met).

We typically like to approach the questions of innovation opportunities for our clients in two different ways:

  1. Top-down approach: this is focused on the consumer’s needs/routines/behaviors. Better understanding the consumer’s experience with your product can help to identify the need gaps and innovation opportunities by creating consumer technical models, a consumer-centric approach. This approach is typically larger scale research and involves three phases (exploration – exploring the consumers needs/behaviors; prioritization – uncover what needs and behaviors are most important and missing for the product; validation – creating proof of principle).
     
  2. Bottom-up approach: this is focused on the product’s performance. By understanding how the different elements of the product affect the consumer we can help clients improve products. This can involve an exploration of the sensory elements (fragrance, colors, sounds, etc.) or the functional elements of the product (product ease of use, etc.).

system1and2One of the methodologies that can be used in both of these approaches is something we call the “MaxImplicit™ ” method. This is our combination of powerful tools from both traditional market research and psychological research that we use to help our clients better understand their consumer with “both eyes open” as we like to say. By using both traditional and psychological methods we can see two sides of the consumer experience: the cognitive (what they say) and the non-conscious (what they mean). In the top-down approach, this methodology can be a means of prioritizing what is most important to the consumer (via traditional methodologies) and understanding how the consumer really views the client brand or product (via psychological methodologies). In the bottom-up approach, this can be a way of testing design elements and attributes to check for missing elements or missed design marks. Very much in the way Kahneman described in his book, Thinking, Fast and Slow, we believe that both the System 1 and System 2 pieces of decision making are important in understanding the consumer.

The precise approach to using MaxImplicit, whether top-down or bottom-up, is two-fold: prioritization measures (traditional market research) and implicit measures (psychological). But the approach is also customizable, as different techniques may be used to accomplish these goals for different situations (type of product, types of attributes, type of consumer, etc.). As with all of the methodologies used at HCD, we like to remain methodologically agnostic so that we can adapt to any type of research situation while ensuring that we are using the right tool to answer our client’s questions completely and accurately.

maxtop10

By being able to capture what is most important to the consumer AND how they really see the product or brand, we can then identify need gaps and innovation opportunities.

If you’d like more information, please feel free to contact us!

Applied Consumer Neuroscience FAQ

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!

https://www.youtube.com/watch?v=7bXJ_obaiYQ

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.