Mind Control - Neuromarketing
Neuromarketing may sound like the latest in science fiction mind control, but research has increasingly shown that the human brain responds to particular stimuli in very distinct ways that may surprise you.
This post also appears on Wearable.ai, a news summary and intelligence gathering service for the emerging wearable computing industry. For inquires, please email interviewer and publisher Mark Brooks.
For the budding startup business looking to connect with customers, knowing how to tap innate responses can make all the difference. Wearables makers should also take note: As more companies seek to study the phenomenon, wearables will become an important tool in gathering the necessary data to inspire the desired reaction from a target audience.
I spoke with author and neuromarketing expert Darren Bridger, who shared some insights into the opportunities this form of marketing can bring with it—and the large roles that elements like neuroaesthetics and neurotesting can play.
Mark Brooks: What is neuroaesthetics?
Darren Bridger: Marketers are often thinking about their designs (ads, packaging, point-of-sale materials etc.) at a high level: i.e. their meanings, cultural references, injecting humor or style.
However, a lot of lower-level elements can be missed. Things like the complexity of the image, its level of colorfulness, and compositional elements (like symmetry or where text is positioned in relation to images) can all play a crucial role in how effective the design is.
Since classical times, artists have been interested in figuring out the rules of aesthetics but the effects of design are only just being discovered thanks to our increasing understanding of the brain, and new research tools at our disposal. Some of the most powerful effects of designs occur within a second of seeing them and are non-conscious (hence people find it hard to describe their reactions to the design).
MB: Could you give us some examples relevant to marketers and designers?
DB: A couple of examples of this that marketers need to pay closer attention to are first impressions and visual saliency. Webpages are a good example of first impressions. Web-users tend to be impatient and fickle: often clicking on a page and clicking away again within seconds. Research shows that people form a first impression of a page within 0.05 of a second, too fast for them to consciously process the detail of the page, and the impression formed strongly biases how they view the page in general.
The first impression effect is largely influenced by the simplicity of the design, or its lack of clutter. Secondly, visual saliency is a property of an image that makes it grab our eye: something crucial to print ads or package design. Putting some attention on good old fashioned design elements that draw the eye—for example, color contrasts, large and/or clear text—is often overlooked but can be critical to the success of a design.
MB: How do you use neurotesting to find optimal pricing? What are the indicators?
DB: A range of prices can be displayed paired with a product image or logo and there are neurotests, usually implicit response or EEG, for finding which pairings feel most natural to the consumer. You can also test different ways of expressing a special offer or price reduction to measure which is most emotionally appealing.
The Future Of Neurotesting
MB: How do you think neurotesting will be done in 20 years? What new technologies are being considered?
DB: Shoppers will increasingly be carrying web-connected devices, giving marketers access to far richer, real-time, real-world data on shopper behavior. This explosion of data will demand neuromodels to understand behavior in order to yield understanding and insights.
One scenario is that tech/software companies "disrupt" the traditional market research industry by gathering, modeling and predicting shopper behavioral data in far more direct and sophisticated ways. For example, this could include factoring in data from cameras on people's facial expressions and eye-movements, and perhaps even physiological data from wearable devices, like smart-watches, on people's real-time emotional reactions.
In terms of technological developments: The main story is likely to be the existing technologies becoming cheaper, faster, and more sophisticated. Our growing understanding of neuroscience and research companies developing their own databases and increasing computing power will likely drive this. Equally, I see a growth of the use of computational neuroscience: software models based on the human brain that can analyze things like images and videos and predict their likely real-world performance.
One possible new brain-scanning technology that could be in wider use in 20 years is fNIRS (Functional Near-Infrared Spectroscopy). This is essentially a cap, like an EEG cap, that shines near infrared light through the skull then uses sensors to measure the diffusion of light through the brain to figure out which parts of the brain are "working harder." Currently, if you want to measure activity in the deeper regions of the brain you need to use an expensive, and uncomfortable fMRI scanner. These scanners will likely improve in affordability and comfort in the coming years but fNIRS could be an even cheaper, more portable, and less invasive alternative.
Neuromarketing
involves the study of how the human brain responds to particular
stimuli in distinct ways, and and how businesses can employ that
information to connect with customers and increase their business. Its
foundation on neuroresearch offers a route to deeper insights and
better design. The following covers ways this strategy can accelerate
business, and the opportunities it presents for Internet of Things (IoT)
and wearables initiatives.
MB: How is neuromarketing using wearable computing and Internet of Things. What are the challenges and opportunities?
DB: The most obvious place is with wireless/portable wearable sensors. The main ones are wireless EEG caps, heart rate sensors, GSR (skin conductance) sensors, and wearable eye-trackers.
At the moment, most of the devices used for research are specialized kit, and not the typical consumer wearables. As devices like smart-watches become more widely used and have better sensors and become more web-connected, the potential could be there to tap into data from consumer wearables.
There are more challenges with collecting brain/physiological data out in the real world than in-home or lab. For example, if you want to understand how people respond to a real world experience you could send them out with portable sensors, but for each person within your test-group you then need to correlate where their head and gaze were pointing at each second. It’s just a more time/computational intensive exercise compared to sitting them in front of a video-simulation, where you know exactly what every person saw second-by-second, so you can more easily compare and aggregate their responses.
More computational power and larger testing groups could solve this problem. This is why I think there is the potential for tech/software companies to move into this field. A consumer wearable that is being worn by millions of people provides a big sample base, and then it just becomes a challenge of (a) gaining access to that user data, and (b) crunching the numbers.
You can also extract information from cameras on people's emotions: from facial emotional expressions, and even heart-rate. As blood pumps around our bodies our faces are slightly, imperceptibly 'flushing' different colors. We can't see this, but point a camera at someone's face then amplify the visual changes in hue and it becomes measurable. There are also more exotic camera-based applications such as extracting information from a person’s gait and movements, or eye-trackers built into smartphones.
Even a simple sensor like a camera has the potential to collect useful information on people's emotions and behaviors when combined with the right algorithms. For example, posters with built-in eye-trackers have already been trialed. As cameras and computing drop in price, you could have more eye-trackers embedded around shops, buildings and public places that understand where people are looking and adjust displays accordingly.
As we interact more with screens and "smart devices" there will undoubtedly be increasing demand for those devices to understand human responses, to optimize themselves to our levels of interest, emotions, and behavior. This pressure to make emotions and attention "machine-readable" will likely expand these applications out of the domain of market research into other sectors.
MB: How would you recommend startups on a budget get early access to neuromarketing labs?
DB: I see neuroresearch tech at a point analogous to computing in the late 1970s: poised to move from being a big/expensive lab application to something more accessible to a far wider range of organizations.
The tech and computing power to run more lab-based studies are falling in price in many cases and most of these tests don't require many other fancy features. Usually just a quiet office room is enough. However, the software algorithms, and know-how to compute, analyze and interpret the results are still a scarcer resource. I would recommend smaller organizations like startups get some specialized advice before just buying sensors and using the software that comes with them. Often this can lead to misleading results.
A sister discipline to neuromarketing - behavioral economics - offers even more affordable options.
Making a Better Wearable
MB: Do you use any wearable devices? How would you advise them to improve, through the application of behavioral science? How could they do better?
DB: We use GSR, which is a measurement of emotional arousal based on skin conductance level changes, similar to the lie detector test. We also use wireless EEG to measure brain activity, although these currently tend to be more medical than consumer grade.
Behavioral science has two main useful applications in this area:
Firstly, knowledge from the behavioral sciences could be used and enhanced through 'quantified self' type applications. People already use sensors on watches and other devices to learn about their physical fitness. Other applications could give people feedback and insights on their own behavior and thinking and point to ways to improve their lives. Technology that learns and improves the more we use it is very appealing and could encourage more people to adopt wearables.
Secondly, behavioral sciences have a lot to add in terms of improving the usability and appeal of such devices. An obvious area of opportunity is to make them more intuitive and easy-to-use. Here there are many insights to be gleaned from neuroscience on attention and behavior.
For example, we all have limited attention, and there are increasing demands placed on it. Wearables can help deliver information to us in more easily digested ways, through things like better ways of filtering and delivering complex information to us in real-time, or through using communicating information to us through an underused channel. A field called Embodied Cognition can offer insights on making gestures and device interactions more intuitive. Sensory neuroscience can offer insights on making devices more comfortable to wear and more emotionally appealing and desirable.
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