Top Neuromarketing Trends To Watch in 2019
Here is your list of Neuromarketing trends to look out for in 2019:
1. The Rise of Machine Learning
Machine learning is here. Even though artificial intelligence (AI) has been around for the last 3 decades and has been spoken of since the 1960’s (Coined by John McCarthy in 1956), it was only since late 2010 that it accelerated into the mainstream as big data continues to get bigger.
The amount of data and information produced and available is so great that it has become impossible for our limited cognitive processing capabilities to sift through it all and make meaningful estimations. This is especially true of market and economic research - and with the large biometric and neurofeedback data sets one has with neuromarketing, it is no different.
Increasingly, we are needing to rely on algorithms and/or machine learning to sift through this data and extract meaningful patterns. The methods and means in which these machine AI systems make this information meaningful vary considerably, from semantic, sentiment analysis to frequency and event estimations.
2. VR and AR
2018 was said to be the year of Augmented Reality (AR) and Virtual Reality (VR), yet VR is nowhere near as advanced as it was predicted to be. However, this does not mean that there is any less interest than before.
What many suspect, is that the advent of VR and AR has just not yet bloomed. Some have suggested that although VR has been suggested to be the KingMaker of human-computer interaction, it may be that AR begins to surpass VR. Unfortunately, VR is just not immersive enough or where it needs to be - just yet.
As AR (and VR) continues to advance, it will allow Neuromarketers to broaden the way in which we can optimise consumer experiences.
For example, if we wanted to test a planogram for a store shelf in a grocery store, we could superimpose different shelf design options using AR, or build them in VR, and use eye-tracking technology to assess how a person would visually navigate the same space in the real world.
The advantages of this kind of testing allows us to bring costs down by testing virtual and augmented environments for real world applications.
3. Access to low cost, high-quality studies
The reduction of the cost of various pieces of hardware, from cellular technology to neuroscience devices together with improved computing power in mobile devices, means that market researchers can scale their studies without sacrificing the quality of their data. This can be seen especially in the electroencephalography and eye-tracking fields.
This is also beginning to impact functional brain imaging research (fMRI) in the Neurosciences as more and more publications emerge in fMRI and especially in the less expensive Functional Near Infrared Resonance-spectroscopy (FNIR) hardware and methodologies.
4. Better analysis of data for better insights
Analytical tools have improved.
Broadly, due to the increased computing power available with lower costs to acquiring hardware; less expensive statistical software packages; the emergence of Bayesian-based analyses (and the move away from null-hypothesis testing); the introduction of artificial intelligence, neural networks and other forms of machine learning in data analysis processes.
The insights produced in the field of Neuromarketing are now more scalable, robust and have higher fidelity than when the field started out in the early 2000’s.
5. Transparency in the industry as a whole
In adopting the scientific approach and philosophy, Neuromarketing has become much more transparent about its reporting process and methodologies.
Reputable Neuromarketing firms now stand behind rigorous ethical principles, of which disclosure and transparency of the research process are paramount. Gone are the days of proprietary methodologies and black box techniques. Proprietary methodologies only serve to protect the interests of the service provider, but in no way serve the client or the Industry as a whole. This has also paved the way for the acceleration, development and growth of the current methodologies.
6. Better Tools
There are a host of new technological developments in applied neuroscience.
New EEG Methodologies
New EEG Methodologies such as variations in approach motivation detection, examination of visual cortex functioning, applications on multiple sensory systems and improved EEG artefact and post-processing algorithms, means keeping EEG in the Neuromarketing game and establishing EEG as a robust and important methodology.
Cheaper fMRI (fMRI 2.0)
There are moves to make less expensive fMRI machines and a goal of developing scalable, mobile and even less expensive fMRI. The industry players in fMRI hope to make the technology even more accessible in the coming years. This means more functional brain scanning, better techniques, more publications and eventually fMRI as a standard approach in Neuromarketing studies
Near Infrared Resonance Spectroscopy (NIRS) has been around for a few years now. This technology allows Neuroscientists to examine brain functioning, mainly of cortical (predominantly frontal lobe) activity. These devices are noise robust, meaning they may be used to detect brain changes and cognitive/emotional processing in a wide range of environments and mobile. They provide better spatial resolution of brain activation than EEG in general, but not yet at the scale of fMRI (although in time they are likely to match some fMRI studies). There are few papers in consumer neuroscience literature and many being published in the clinical neurosciences, which means in time NIRS will likely become an established methodology, which may even replace EEG.
7. Implicit Testing
Response time testing has become an established behavioural science methodology in Neuromarketing.
Response time testing measures the implicit motor response of consumers as they consciously select words or phrases that either match key brand categories or specific marketing stimuli under investigation.
Implicit testing using response time, allows Neuromarketers to scale their studies, reduce their reliance on physical hardware and massively reduce turnaround times on research
8. The Internet of Things
The internet of things is still in its infancy, but many still harken that it is merely a matter of time before almost all appliances, electronics, many household items and transport, for example, are networked and communicating with each other.
The internet of things will massively contribute to Big Data, as information continues to scale exponentially. It will offer new layers of insight into consumer behaviour, thinking and emotion.
9. Embedded Biometrics (By 2020)
Embedded Biometrics involves both wearables and technology that is either integrated biologically as part of our bodies or resides within our bodies.
Currently, some of these embedded biological cybernetics include devices such as AR lenses, GIT monitoring devices within our digestive tracts, implanted medical monitoring devices in capillaries/blood vessels, neurostimulators and specialised heart monitoring devices (often as part of a pacemaker device). There is even a small group of individuals who have begun to implant tiny CPUs and computers on their bodies.
Other embedded biometrics are likely to include unique and everyday wearables such as clothing, wrist devices, glasses and possibly any other type of clothing. These may monitor anything from location, body movements to heart rate, blood pressure, oxygen utilisation and even overall body metabolic processing. This is likely to offer Neuromarketers a host of new information to assist with understanding consumer behaviour.
So that’s the Top 10 for 2019, it’s sure to be another exciting year for Neuromarketing!