Interview with Steve Genco leading author “Neuromarketing for Dummies” (I/III)

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.Neuromarketing. its complexities, methodological and other neuro-points

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Hello, I’m Edgar Sánchez (E.S.). I am with Steve Genco (S.G.), leading author of the book “Neuromarketing for Dummies”.

E.S.: Steve, thank you for taking time to join this conversation about Neuromarketing.

Steve, let’s begin with the basic things, What is Neuromarketing, what is the definition?, your definition of Neuromarketing?

S.G.: Well, Neuromarketing is basically the study of consumer behavior in terms of the process of the human brain and applying a huge amount of knowledge that has been developed over the last couple of decades in the brain sciences which I include Psychology, Neuroscience and also Behavioral Economics. The application, those insights which those include topics of Marketing in Consumer Behavior, Consumer Decision Making, and basically looking at the consumer as kind of full picture of the consumer brain that we have today as opposed to the kind of limited models that we used to have before this new information became available.

E.S.: Great.

 

 

E.S.: What are the complexities of Neuromarketing?

S.G.: There’s a necessity for Neuromarketers to have a pretty strong scientific background. It’s not a do it yourself kind of certain methodology. There is a whole specter of methodologies. Some which are very detailed require Ph.D. level, scientific training in order to do and some others that are easier to perform and to understand how do they operate the data and still get a pretty strong background. So I think the biggest complexities of Neuromarketing, you have to be serious about is the science. Neuromarketing is a field that at least today people come into from other fields where they’ve already established credentials and scientific knowledge and to apply that knowledge to Marketing and Consumer Behavior.

 

 

E.S.: Generally speaking, what is the way to measure the Neuromarketing projects, is there anything like a ROI ( Return of Investment). What would be those measurements, those successful measurements.

S.G.: Ultimately, Return of Investment is kind of the ultimate measure marketers need to justify the cost to companies that they worked for. Measurement is a piece of marketing, ultimately its marketing itself is an effective or non-effective cost to testing , marketing pre-testing, post testing and monitoring. Any large product company or small product company for that matter needs to determine how it’s going to allocate it’s spending, it’s expenses in order to maximize the overall ROI. So that’s the kind of long sophisticated answer.

In fact, companies tend to measure their research results I think in a less quantitative or precise manner. And it’s often a kind of a satisfying sort of model where things are going on ok. You know we’re selling, increasing share or maintaining share, and as long the boat is kind of floating along, at an appropriate level. If something bad happens and then is a flurry of activity. What will we need to do, what will we need to adjust and then you might see a lot more research. And then you might see changes in terms of how the company has whole response to the marketing situation.

 

E.S.: Talking about the methodologies, I would like to ask you about the sample size. On the one hand, how big should be the sample size? and on the other hand, how important is to have a representative sample for the studies?

S.G.: I think sample size is actually somehow overrated problem. I think that a lot of times marketers and market researchers are more comfortable talking about sample size because it’s an issue they have to deal with in every kind of research. So the issue the same sample size in Neuromarketing  is something they can correspond to and talk about. But in fact sample size is a matter of statistical power. Sample size is not, there is no number that it is appropriate, sample, you need to know the strength and the effect that you are measuring and then you need to be able to calculate, you know,  power calculation or to determine what is the sample size in order to extract that signal. You know, from the noise of the data.

So for some kinds of effects, brain effects they are very prominent signals to noise ratio and because of that, in order to identify them, you don’t need a big sample.

Now, the second part of the question. The important issues are which is what is the population that your sample is represented. It may be the case that a signal can be identified with twenty or fifteen people but if you’re interested in what that signal represents in terms of a kind of consumer’s behavior or the kind consumer’s response, and you’re interested in the response of particular segment of the population then you have to be sure that the people that you’re testing are in the right sample, are in the right group.

Second, but a lot that we’re interesting it is comparing segments. So, the sample size issue kind of goes away, if you want to compare so say, that in order  to determine the presence of a signal in twenty people let’s say for EEG or some  other kind of methodology, well so you need 20 people to determine the straight signal, in a particular group, say pair of men and women you have to go to 40 people because you have 20 men and 20 women, because  each of those sub-segments used to have an adequate number to be able to identify the signal.

You also need to be able to do young and old, now you’re up to 80 because if you take each other’s groups you take young men, young women and older men, older women and you got to eighty people. So, it’s really easy to get the sample size up, if the comparison that you want to make require comparing different groups, product loyalists versus product diagnostic. New users versus long term users, every time you want to compare any of those groups you have to double the samples. That’s a limitation because unlike survey methodology where you start off  with a big sample, you can slice the dice according to maybe identifying an interesting distinction in the sample for people who live in a certain sized city, in a certain region, shop or a certain store, they seem to have an interesting characteristic, you can cut and tease that out of the data.

But in experimental research you have to predefine  those groups, you can’t find them afterwards so that’s how often something that focused to survey research has a little trouble understanding the data pre-specified and you can’t just slice the dice of data. You have to create an experimental protocol that gives you, each self one study, for comparison you have to have more people to have this statistical power to do the comparison.

 

 

E.S.: The first part of the question was because I have read somewhere that the golden number for a sample size in Neuromarketing is 30. And that’s why I’m asking you this.

S.G.: For some kinds of study to identify some kinds of patterns, 30 may be perfectly adequate, but 30, of who? 30 women, you want 30 young men, you want 30 buyers of a product that buy it at least 10 times a year. So you often find that the most powerful research has some kind of built-in comparison. An absolute measure does not mean very much, if you gonna have a general population and the general population, the amount of attention allocated to this ad, is whatever the number is, that’s much less helpful than the amount of attention allocated to this ad was 47 and this ad was 39 and given this sample sizes, you know that is statistically significant difference. Now you know something as opposed to a general level.

 

E.S.: The second part of the question was because I’ve read again somewhere that it’s not important the composition of the sample. If you do Neuromarketing study in Sao Paolo Brazil, you can extrapolate to people in the UK or Finland. Some people are claiming so because they say the idea they claim, that the brain does not have so much variability among people and they are claiming those things.

 

S.G.: I think it’s a kind of misnomer, I’m aware that these claims have been made and I think it confuses a couple of level of analysis. It’s the case that if you get excited about something, and I get excited about something and we get excited in the same way, so we may have arousal, skin conductance increase, frontal lobe symmetry, that’s the way our bodies and our brain process being excited about something. But you may be excited about something completely different than what I’m excited about. It’s not a machinery of excitement that it’s relevant. It’s what is exciting to you, and that very significantly there is a lot of very interesting research coming out now, cultural differences, even perception the way in which some Asian  cultures and Western cultures perceive the scene. They are using eye-tracking, where they’re focus on the scene, literally the way in which, what seems to be a very hard wired perceptual function can be different in different cultural context, in which people learn how in our culture we absorb information. So there’s a lot of really interesting differences. So the idea in defense  and resilience, Spaniards all respond in the same way, at one level is true, all of our brains work pretty much the same, but what we respond to can be very different.

E.S.: Okay,

 

I want to continue reading the second part…

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