Today, when it comes to advertising, real-time insights into responses evoked at the neuro -- or brain -- level have only made their way into movies such as “Minority Report” (see clip) as Hollywood plays with the eerie potential of addressability. Nevertheless, last year’s acquisition of Neurofocus by Nielsen and the work of companies like Affectiva are early “mile markers” in the combination of marketing and neuroscience – a.k.a. neuromarketing.
For Neuromatters co-founder Barbara Hanna, who has a Ph. D. in Computer Vision, and her co-founders, they see applications across industries. Whether her company decides to go the “marketing” route remains to be seen as it is somewhat driven by the customers who arrive at their doorstep as they cobble together a range of projects unlocking the human brain’s potential and its limitations.
AdExchanger spoke to Hanna recently about her company, neuroscience, and marketing.
AdExchanger: How do you characterize your company’s interest in "neuroscience"?
BARBARA HANNA: What we're interested in is the neuroscience that's concerned with neuroimaging - analyzing and decoding neural activity as it is captured through modalities such as electroencephalography (EEG). That is a very portable type of measuring device that consists of electrodes and can involve electronics that are put on a person’s scalp to record electrical activity.
Some of the findings that we've already been able to exploit show, for example, that people are good at responding very rapidly to things that they're interested in. To put it simply, there are certain brain signatures that are elicited when humans look at a lot of information. When people are bombarded with information, they rapidly get the gist of what they're looking at and then certain brain signatures can be decoded from the EEG strain that we record.
So neuroscience is about decoding and better analyzing neural activity as it is captured and provided to us through neuroimaging modalities and also working with specialists or scientists that have made advances into understanding better what the information tells us about how people process information or how they react to what they're presented with.
So, how about the basic venture capital question - what problem is NeuroMatters solving? – and a bit of background, too.
NeuroMatters has been in existence for more than four years now. Myself and the other two co-founders - one is a professor of Columbia University, Paul Sajda, the other one, Lucas Parra, is at City College of New York – quickly recognized that there is an information overload problem.
On a daily basis, humans receive more information that we can process and that becomes particularly true for some people whose jobs it is to analyze data day in and day out. But I think it touches all of us at this point and the question becomes, "How do you deal with that amount of data as you prioritize your attention on a daily or even hourly basis, and when you have very limited amount of time to actually do so?"
That idea probably ties into the advertising world in a reverse sense in that there are a lot of advertisements to compete for people's attention. Therefore, it's important that [marketers] get their message out clearly.
While we haven't addressed that state, in particular, it’s been one of the cores of neuromarketing and other neuromarketing companies: understand whether the marketing messages can be effective, how they can be more effective, and if there is an emotional reaction that people may or may not have. These are the types of questions that are relevant for the advertising world.
In our case, we started looking at a slightly different problem, which is information overload and a potentially, increasing problem with search. If you are somebody who needs to search through large amounts of data -- and specifically, visual data, where one of the cruxes of the problem is -- visual data is harder to structure.
There are tons of images out there and videos. If you look at the stats of YouTube, they have millions of videos uploaded daily with similar challenges on Twitter or Facebook. All that visual imagery circulates and the question becomes how can you get to the things that are mostly likely to interest you. You can also extend that to imagery on a larger scale.
Having said all that, our company also realized -- and we're not necessarily the only ones -- that brain-computer interface systems are not necessarily going to be useful or have application for medical purposes.
Traditionally, brain-computer interfaces were designed for people who had medical disabilities or conditions that required them to have different types of interfaces with the world. We changed brain-computer interfaces to a general interface for people, potentially, and that's very powerful.
Because our company develops neurotechnology, we have started seeing other applications. We're constantly working to evolve and push the envelope of brain-computer interface systems, which we highly believe in.
So, I’d imagine you’ve heard of “big data.” Do you think you are solving a “big data” problem?
Some of it is directly relevant to the big data problem. For us, we were interested in tackling some aspects of it. The problem is it's a big concept. I mean, “big data” is two simple words that encompass a lot of different problems.
What we're trying to tackle is one aspect of the big data problem, which is the fact that there are few trained and skilled people to look at a “mountain” of data.
Big data also involves -- and “involves” means a partnership between the human and the machines that they use -- the recognition that to solve the big data problem, there's going to be some computational frameworks that are going to need to be put in place. Folks at IBM spend a lot of money looking at data analytics.
On our end, we also see that there is the need to keep the humans in the loop. At which point in the chain? Well, I think that's still to be determined, but the human does have these unsurpassed capabilities of recognizing patterns, for example, and you want to be able to exploit that. We think that brain-computer interfaces are a great conduit for that.
So, do you think data can be truly visualized beyond what spreadsheets can do?
There is definitely a visualization component. Even for us, as we create our interface, we hope to provide useful information from the information that we have.
As I said, the human brain is good at processing visual information and recognizing patterns.
For example, when facts and numbers are put into an infographic or something with visual underpinning, we start getting attracted and start remembering, perhaps creating memories and appreciation much faster or better.
Visualization is going to be very important. It comes back to this one idea, which is that we can comprehend only so much once we start seeing a sea of numbers. We need to be able to have these numbers or this information to fall into a few concepts that we can rapidly digest. And, sometimes that means it is better performed through visualization of that data.
There is an oft-cited moment in the movies of the combination of neuroscience and advertising. In “Minority Report,” a character played by Tom Cruise walks through a mall and there's a babbling brook of advertising addressing his character. How close do you think we are to a "Minority Report" moment, if you will?
There are several ways of answering that. As as a technologist, I'd love to see this sort of thing happen soon because that movie is obviously a playground for us. A lot of the technologies you see in that movie actually exist.
Along with the other co-founders, we've thought about a world like that and the neurotechnologies that are going to be developed for that. I would say how close we are is best defined by the technology. It’s definitely going to take some time to sort that out because even developing the neurosensors [which Cruise’s character wore] that people can wear very easily day in and day out is probably a few years away.
It's also going to be about how consumers and companies are going to want to invest and make a push for this - and that's not predictable. I've always said that neurotechnology can solve a lot of problems, usually it's a matter of money and time, but we always get there.
It's creating a lot of questions as to individuals being comfortable with an environment such as the one “Minority Report” suggests. It will definitely bring a lot of conveniences. It may raise a few ethical questions, too. The question is going to be if and when people are going to be ready for that at a business level - and then, just from the human perspective. I don't think there's an easy answer to that question, but as technologists, we definitely get excited by that picture and that picture of the future.