Neuromarketing – The Art and Science of Marketing and Neurosciences Enabled by IoT Technologies
Neuromarketing looks to remove hidden
biases to try and tap into customers at their
subconscious level through a number of
different types of IoT-enabled technologies.
These technologies include:
When these tools are assembled and used
together as integrated IoT technologies, they
bring forth a unique capability to understand
a consumer’s sentiments to brands and
advertising messages and help retailers
meet or exceed shifting customer needs and
expectations.
Functional magnetic resonance imaging
(fMRI) – This measures changes in
activity in deep parts of the brain known
as the “pleasure center” based on
measuring blood flow. For instance, if
you use a part of your brain more, it
requires more oxygen and more blood
will flow to it which might determine
your preference of a dress or color;
W HAT T YPES OF T ECHNICAL
C APABILITIES ARE A VAILABLE ?
Today, facial recording, tracking and
matching trough video surveillance is widely
used in law enforcement. Faces captured
through video can be matched with a high
degree of accuracy against existing photos.
In addition to face matching of known
persons, general demographic identification
of unmatched persons is available. Examples
of demographics available include age,
gender and ethnicity.
Electroencephalography (EEG) and
Steady State Topography (SST) – These
measure electrical activity in specific
regions of the brain. It measures a
person’s motivation and cognitive load
(i.e., how much effort and thinking a
customer
needs
to
put
into
understanding an ad);
Biometrics Sensors – These measure
changes in one's physiological state.
These sensors track heart rate,
respiratory rate and galvanic skin
response;
Motion Tracking – This is the use of eye
tracking to identify focal attention, and
facial coding to categorize the physical
expression of emotion – both in order to
learn why consumers make the decisions
they do;
Big Data Analytics – The integration and
analysis of disparate and unstructured
data
to
understand
patterns,
correlations, relationships and develop
predictions.
While face matching and demographics
provide descriptive identification, emerging
capabilities exist around behavior detection.
Technologies such as emotion, facial
expressions, gesture, eye tracking, eye gaze
and human tracking capture non-verbal
behaviors while verbal behaviors are
captured through audio with tonality and
semantic analysis. As technologies such as
artificial intelligence and machine learning
continue to evolve, the ability to capture
specific consumer behavior, for example
picking up and putting down a product, will
become more accurate. These types of
capabilities provide retailers with the
opportunity to systematically identify
shifting consumer preferences with depth
and accuracy unavailable in the past.
30
June 2016