Aveneu Park, Starling, Australia

1- and new information is obtained in


The numbers of individuals that are using the Internet
are constantly increasing. In 2002, only 10,58% of the world population had
access to the Internet and, in 2016, this indicator reached the value of 45,91%
(World Bank 2017, https://data.worldbank.org/indicator/IT.NET.USER.ZS, accessed in December, 02, 2017). With the
development of the Internet, the society changed, including the way people shop.
Current e-commerce statistics show that 40% of the worldwide internet users
have bought products online using various devices (Statista 2017, https://www.statista.com/markets/413/e-commerce/, accessed in December, 02, 2017). This corresponds to
more than 1 billion online buyers and it is expected to keep growing. Focusing
in the B2C market, e-commerce sales have reached an amount of more than 1,2
trillion US dollars in 2013.

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This information is highly important to encourage
firms to invest in e-commerce solutions and improve the consumers’ online
shopping experiences. The possibility of marketers to track the behavior of
consumers is crucial, so they can measure the reasons behind the success and failures
of the e-commerce websites. Knowing exactly to where the website users are
looking at and the spots where they spend more time paying attention has a huge
value for companies. Eye-tracking equipment allows doing this and, therefore,
it is an excellent tool to improve a website.

The idea of this project is to perform an eye-tracking
study on the Sportzone website and with the data extracted from the
eye-tracking equipment, analyze and study the information in order to improve the

The main aim of this study can be defined as the
optimization of the Sportzone website. Regarding the research questions, they

the movement of the computer mouse different from the movement of the eye?

this behaviour varies between generations?




Visual marketing can represent the first contact
between a brand and a customer. Thus, attracting the customer attention is
crucial in order to be possible that the client understands the message. The
fastest movement the human body can make is eye-movement (Holmqvistetal,2011),
that is comprised by a series of stops (fixations) and moves or jumps (saccades).
Visual cognitive processing of a scene demand the eyes to attend to an object
and the eye movement is required in order pay attention (Russo, 1978). Vision
is suppressed during the actual eye movement (or saccade) and new information
is obtained in the fixation period (Wedel and Pieters, 2008). Eye movements
compose measures of the unobserved visual attention process with a high
temporal and spatial resolution, and thereby have the potential to produce
insights about target search that are hard to obtain otherwise (Findlay and
Gilchrist, 1998). The process of locating a target among a set of distractors
in a scene is defined as visual search (Wolfe, 1998). Therefore, it is during
eye fixations (that reflect the moments of visual attention) that consumers
extract information from advertisements (Pieters et al. 2002). For complex
visual stimuli such as displays, the identification of objects is obtained by
eye fixations (Chandon et al.,2009). In fact, the probability of brand
consideration increase with fixation counts; more detailed, at least two
fixation counts increased the probability of brand consideration by 13 per cent
(Chandon et al., 2008).










In online shopping, website design is considered to be
a relevant element that influences user’s attitudes and behavior (Y.Lee, K.A.
Kozar, 2012). According to Berlyne (1970), complexity can be defined as being a
function of the quantity of variety in a stimulus pattern. Geissler et al.
(2001) claimed that there are three factors on which the complexity of stimulus
depends: number of elements, the level of dissimilarity between elements and
the level of unity between elements. Huang (2003) identified complexity,
novelty and interactivity as crucial website characteristics and indicated that
complexity remit to the amount of information that a site is offering,
including components such as text, hyperlinks, pictures, animations, and video,
and the variation in these components: picture size, arrangement of these
characteristics, etc. Deng and Poole (2010) determined webpage visual
complexity as constituted of two dimensions: (1) visual diversity, that is
related to the varieties of design elements, like graphics, text, and links,
and (2) visual richness, which remit to the detail of information present in a
webpage as measured by the amount complexity on the web content.

Existing studies indicate that website complexity
affect many user outcomes, like communication effectiveness (Geissler et al.,
2001), usability (Tuch et al., 2009), flow (Huang. 2003), arousal, and pleasantness
(Deng and Poole, 2010). Studies carried out give different point of views about
whether a simple website is better or worse than a complex one. Agarwal and
Venkatesh (2002) defend that simple websites are easy to use and effective.
According to Germonprez and Zigurs (2003), a complex website is able to
transmit richer information and intrigue consumers and, therefore, positively
impact consumers’ arousal (Deng and Poole, 2010). Additionally, Geissler et al.
(2006) present an “inverted U relationship” between website homepage complexity
and communication effectiveness. Regarding experiential users, Deng and Poole
(2010) discovered that webpage complexity had a positive impact on users’
approach behavior, while Nadkarni and Gupta (2007) proposed an “inverted U
relationship” between website complexity and user satisfaction.



Neuromarketing joins neuroscience
to marketing and it is a very recent topic. The past decade has experienced a
blast of research in neuroscience and to study marketing, consumer behavior,
and advertising phenomena with the use of multiple neurophysiological methods,
broadly referred to as consumer neuroscience or neuromarketing (Ariely and
Berns 2010; Camerer, Loewenstein, and Prelec 2005; Dimoka 2012; Smidts et al.
2014; Venkatraman et al. 2012; Yoon et al. 2012).The interest in this subject
aroused in the past 90’s decade by Gerald Zaltman, a professor at Harvard
University, that in the pursuit of consumer research began to study MRI and
brain activity. Nevertheless, only in 2002 the term was coined by BrightHouse –
a marketing firm in the USA (Morin, 2011).

The neuromarketing emerges as an
application of neuroscience to marketing by quantifying the consumer reaction
to an element or product in advertising with the usage of any mensuration of
brain activity. In fact, the use of this tools allowed the growth of a new
industry in the past decade due to a combination of technological advances in
fMRI, electroencephalography (EEG), eye tracking, and other neurophysiological
tools with increased accessibility of these methods due to decreased
administration costs (Dimoka, Pavlou, and Davis 2011). Given the fact that
these tools work at the subconscious level of the individual, they are more
trustworthy because they permit to surpass all barriers and difficulties in
transmitting ideas and are better to understand client preferences than other
types of market research (that have some limitations).

This improvement was allowed by
some knowledge like mapping of the brain, the nervous system function and
neuronal activity, and with them it is practicable to interpret the meaning of
a reaction.







Figure 1-mapping of the functional
areas of the brain. Source: CERN Foundation

The anatomy and the mapping of
the brain are very important to achieve conclusions from studies. It is very
important to translate what you see in order to give meaning to an MRI or other
type of brain imaging.  To be capable of
measure the individual’s subconscious response to a given stimulus it is
crucial to understand the meaning of each of these areas, that can be divided
into four main areas, as illustrated in Figure 1: occipital lobe, temporal
lobe, parietal lobe and frontal lobe (Nolte, 2002).

Each of these areas has a
distinct functionality, as it is described by Nolte (2002):

Occipital lobe: Corresponds
to recognition and perception of images in the visual field and are areas that
before a stimulus and the following reaction may indicate that subject’s
connection to what he is seeing.


Temporal lobe: It is related to the recognition
and memory of objects, hearing and language (semantic memory) and even episodic
memory (on the autobiographical occurrences). It is in this  part of the brain that brands and products
are recognized, the temporal lobe is activated when the individual is facing
any of these stimuli and it is possible to understand, by the level of
involvement, how much a brand or product is likely to be remembered by the


Parietal lobe: Muscle memory, motor function and
touch are functions that are located in this area.


Frontal lobe: Some of the most important tasks
to be considered in the study of consumer behavior, like short-term memory,
motor behavior, preferences and the entire process of decision-making, are situated
in this area. The area of the frontal lobe is intrinsically related to the
conclusions that can be drawn from any study involving brain imaging.



To be able to understand and
anticipate certain behaviors it is necessary to analyze the neural connections
that are activated when the subject is facing diverse situations. Some
marketing processes are key to the knowledge of the consumer, like the
decision-making process and the reward experience.

The decision-making process aims
to understand and map out which brain activity involved since a problem or
question arises until the decision about the resolution is taken. Taking into
consideration the mental steps by which the consumer goes through until the
purchase of a specific product allow to improve and influence this process,
i.e. What are the actions that can be taken to make the purchase of the product
simpler and faster (Solnais et al , 2013). With this in view Pennings, Garcia
and Hendrix have developed a conceptual model of the individual decision-making
process, as can be seen in Figure 2. This model seeks to understand “the
cognitive mechanisms responsible for the transformation of the stimulus in
decision-making behaviors to identify how the best decision can be
reached” (Cesar et al, 2012).


Figure 2-concetual Model of
individual decision-making by Pennings & Garcia, 2005.

The decision-making process is
represented by the authors with a two-phase composition, as well as an
interactive process. The first stage occurs with the initial stimulus and retransmission
and transformation in perception, which creates the multidimensional space.
Later there is a pivot of the cognitive processes that reflect the previously
created perceptions in stock. This is the moment of decision making. (Cesar et
al, 2012).

The reward experience obtained at
the time of the decision is intrinsically linked to this process. The neuronal
signal activated in this moment can be a factor of predictability of the
experience of reward that will later be obtained at the time of consumption.
There is also the possibility that these two signals are maintained even when
the preference elicitation methods are not compatible with incentives. Both
claims are only possibilities that are yet to be verified, but if it can be
proven, neuromarketing might be able to measure consumer preferences. (Ariely
and Berns, 2010).



Electroencephalography is one of
the tools that assist neuromarketing and, according to Wang and Minor (2008),
it is possibly the most frequently used neuroscience method in advertising
research. The technology is based on EEG, electrophysiology study of the
electrical properties of biological cells and tissues, which encompass
measurement of the change of electrical current in the organs. In the area of
neuroscience it corresponds to the mensuration of the electrical activity in
neurons. Thus, this is a method of observing the electrical brain activity.

Figure 3-brain waves recorded using

The figure 3 is an example of the
data extracted from this technology that are brain-wave oscillation in several
stages. In one hand, it requires significant resources for the treatment of the
data. On the other hand, the costs associated to this technique are not very
high. Although the spatial resolution of this technique is low, about a
centimeter, depending on the number of electrodes placed and with little
sensitivity to the deeper areas of the brain, has a high temporal resolution,
in milliseconds, and can detect fast changes of brain activity. (Ariely and
Berns. 2010).



The idea that is possible to better understand the
customer behavior by knowing to where customers are looking and focusing their
attention is very interesting. According to Tangmanee (2013), it is very
demanding to track what a person looks at. A flow of information about the
user’s mental state in actual time can be provided by eye-tracking (M.A. Just,
P.A.Carpenter, 1976; C.Martin, J.Cegarra, P.Averty, 2011). Eye-tracking is an
objective process that is able to demonstrate cognitive processing through
eye-movement metrics (S. Djamasbi, M.Siegel and T.Tullis, 2010). Schmutz et al.
(2010) claim that eye-tracking removes the subjectivity of self-reporting data.
A more satisfying shopping experience can be obtained by the data extracted
from eye-tracking (Klingensmith, 2013). The eye-tracking literature has changed
over time, ranging from studies related to the act of reading (Rayner, 1998) of
package labels (Bix et al., 2009) and more recently, consumer perceptions and
liking of outdoor advertisements (Maughan et al., 2007), and of mall media
(Thomas-Smith, 2011) have been the eye-tracking studies. To attract consumers’
attention to merchandise, retailers generate point of purchase displays.
(Allenby and Gintner, 1995; Chandon et al., 2009; Clement et al., 2013; Drèze
et al., 1993). Subsequently, it has been confirmed by researchers that
increased visual attention will increase the likelihood of choice (Armel and
Rangel, 2008; Busemeyer and Diederich, 2002). Thereby, the probability of
choosing an item depends on the relative amount of time that consumers fixate
on it during the process of decision-making (Armel and Rangel, 2008). In other
words, the quantity of time that a consumer focuses attention on an item can be
a prevision of the actual purchase (Armel et al., 2008). The competition for
attention when a focal product in a catalogue display is surround by other
merchandise that compete for consumer attention it negatively influence the
attention to the catalogue display and sales. This was discovered by Janizewski
(1999) in an early eye-tracking study. Teixeira et al. (2010) found that more
viewer attention was given to branded products than unbranded products. In
addition, the number of consumers’ eye fixations was greater in product
attributes that were more important to them (Meissner and Decker, 2010).  Maughan et al. (2007) found that eye
fixations and “liking” of an advertisement are correlated. Eye-tracking permits
us to track how users react to webpage elements without affecting the
ecological validity and/or “wholeness” of the stimuli and it can also show the
parts of the webpage that participants paid more attention (M. Byrne, 1999). Kuisma
et al. (2010) found that viewer’s attention in vertical advertisements was
higher compared to horizontal advertisement in animation in online
advertisements. Schmutz et al. (2010) examined the effects of different
presentation types (matrix versus list) on cognitive load and consumer
decisions by combining an online study and an eye-tracking study. Cyr et al.
(2009) gain insight into how internet users perceive human images as one
element of website design by using an eye-tracking methodology, interviews and
a questionnaire. And Leuthold et al. (2011) realized an eye-tracking laboratory
study with 120 participants in order to compare the influence of diverse
navigation designs (vertical versus dynamic menus) on user performance. These
are studies on website design elements. Then, we have some studies that focus
on fixation behaviors of users. Nielsen (2006), based on an eye-tracking study
of 232 users, elaborated an F-shaped pattern when reading webpages. Djamasbi et
al. (2010) evidenced that members of generation Y favor webpages with a main
large picture, pictures of celebrities, a search feature and little text by
collecting users’ fixation data with eye-tracker. Cross-cultural studies were
also made. Dong and Lee (2008) elaborated a cross-culture study of webpage
design and clarified the differences between the three cognitive styles
(Chinese, Korean and American) using the different fixation and browsing
patterns recorded by the eye tracking device.












In this section, I will explain in more detail how the
study is planned to be performed. An eye-tracking device should be used (an
example is presented in the image below). This equipment is located in Faculdade de Engenharia da Universidade do
Porto (FEUP) and the authorization to use it has already been given.

Several experiments will be realized on the Sportzone
website, with different people from various age groups while using the eye-tracking
device in order to check if the the movement of the eye is different from the
movement of the computer mouse. The fact that the experiments will be made with
people of different ages allows seeing if the behavior is different between
generations. Thus, this is an experimental methodology.

The target population is the individuals that acquire
products related to sports at least three times per year and the sample is
expected to be around 100 people.


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