This document summarizes a study that applied neuroscience techniques to analyze users' emotional and attentional responses while navigating three mobile commerce apps. 30 participants used an EEG neuroheadset and eye tracking glasses to measure their brain activity and eye movements. The study found insights about which app elements engaged or disengaged users that can help optimize mobile design. Key findings involved browsing vs checkout, brand perception, screen real estate use, images, and load times. The report concludes this approach provides a new way to measure usability that will influence mobile experience and transaction design.

1. THE SCIENCE
BEHIND MOBILE
DESIGN

2. T H E S C I E N C E B E H I N D M O B I L E D E S I G N
ABSTRACT 3
BACKGROUND 9
METHODOLOGY 13
FINDINGS & INSIGHTS 20
CONCLUSION 61
SURVEY DATA 66
EEG & EYE-TRACKING DATA 78
PIZZA PIZZA 79
BEST BUY 84
HYATT 89
AT A GLANCE 94
REFERENCES 96
CONTENTS

3. ABSTRACT

4. Two firms team up to apply neuroscience
to user experience and spark a revitalized
way of understanding usability and
design preferences.
4

5. This year, total digital
spending is forecasted
to reach $260 billion,
with mobile commerce
contributing $34 billion.
5
ABSTRACT

6. Background
The growing global adoption of mobile is becoming undeniable.
Despite this, mobile commerce continues to underwhelm. As it
becomes more and more second nature to consumers, marketers
need more than general demographic information about their target
markets in order to create engaging mobile experiences. Mobile now
demands that we know what users like to do, where, when and how.
Until now, marketers have relied heavily on users’ explicit responses
and feedback to mobile applications to determine whether their
mobile commerce efforts have hit the mark. However, with so many
external variables, expectations and preconceived notions weighing
on people’s responses, traditional research methods, like surveys
and focus groups, can be notoriously unreliable. Neuroscience, or
the study of the brain’s response to stimuli, shines a light on the grey
area of user response. By determining positive and negative
emotions and attentional activation, the study finds new insights into
engagement, helping marketers and user experience designers
optimize every precious pixel.
6
ABSTRACT

7. Hypothesis
A well-crafted UX is critical to the success of a mobile application.
The traditional methodology of testing UX design through focus
groups and click through percentages may not be giving us the
complete picture. Therefore, applying neuroscience to user testing
allows us to measure the subtle layer of quality associated with a
well designed UX, something not always distinguishable to the
average user. By doing this we can better pinpoint the areas of a
successful UX by attributing the user’s emotional response to the
design.
Methodology
We outlined a single user journey for three transactional mobile
applications to get a better understanding of how users are
navigating mobile commerce. Using an EEG neuro-headset and
eye-tracking glasses to measure the attentional and emotional
activity of the user, we measured what they were looking at first,
last, most and least.
7
ABSTRACT

8. Results
The report showcases the results from the participants’ journey
through all three mobile applications. We charted their emotional
engagement and levels of attention, throughout the journeys. As
well, we looked at participants’ pre- and post-study survey
responses, the time spent and visual areas of focus from the eye-
tracking portion of the study.
Insights
From the findings, we identified seven recommendations for brands
when refining their mobile offerings. The study’s findings involve
browsing vs. checkout, brand perception before and after using a
mobile application, the use of the limited screen real estate on
mobile devices, the use of images, and the effect of long load times.
Our insights are aimed at taking these areas of a mobile transaction
and ensuring that they are completely optimized to increase user
experience and, ultimately, widen the revenue stream for mobile
commerce transactions.
Conclusion
This report, The Science Behind Mobile Design, has unlocked a new
way to measure usability and will shape the way we look at the user
experience and design of transactional mobile experiences from
here on out. Knowing what users are thinking, feeling, and paying
attention to about mobile applications, can help brands optimize
their purchase paths, enhancing their mobile commerce efforts
which could ultimately become a new revenue channel.
8
ABSTRACT

9. BACKGROUND

10. As mobile continues to expand its
presence in our everyday lives, what
insights can we gain from analyzing the
emotional and attentional responses of
consumers as they journey through a
mobile app path to purchase?
10

11. Background
Mobile phones have quickly become the most indispensable and
intimate devices we own today. As such, for any brand offering an
electronic transactional channel to their customer, understanding the
mobile medium is as pertinent as understanding the customer.
Gathering and interpreting data and analytics can be empowering to
brands in understanding their customers’ habits, profiles, and
preferences. However, combining neuroscience with mobile
marketing can help brands ascribe meaning and qualitative insight
to consumer behaviors. Knowing what they are seeing, feeling and
paying attention to when using a brand’s mobile app can help
marketers better tailor their mobile solutions to their specific target
audience, and create a more intuitive and frictionless shopping
experience through mobile applications.
Traditional market research methods have relied heavily on users’
explicit feedback to mobile applications to determine whether their
mobile commerce efforts have succeeded. Coupled with the fact
that this research is often done after the app has been on the market
- ergo, allowing only for fixes to the updates, and not to the initial
offering - this kind of research issues subjective results. It relies
completely on the assumption that people are able and willing to
disclose exactly how they feel. On top of that, a myriad of external
variables, expectations and preconceived notions can have an
impact on people’s responses, leaving these traditional research
methods, such as surveys and focus groups, notoriously unreliable.
For example, certain soft drinks conduct blind taste tests to identify
which soft drink consumers actually like better, because people’s
judgements can be clouded by strong positive brand associations,
which can overpower senses like taste.
Neuroscience, or the study of the brain’s response to stimuli, shines
a light on the grey area of user response. By determining positive
and negative emotions and attentional activation, we are able to
glean new insights into engagement. When combined with mobile
marketing, neuromarketing is created for the purpose of this study
to discover the impact of mobile design on a consumer’s emotions.
Although there has been some speculation around the
understanding, the techniques used are cutting edge and have
helped various industries at large identify exactly what their target
audience is feeling at the time of specified stimuli. Therefore, the
results from neuromarketing can help marketers and user
experience designers optimize every pixel.
This Study is designed to serve as a starting point in understanding
the impact of mobile applications. Further studies should consider
sample sizes of 50+, multiple applications, as well as more rigid eye-
tracking studies.
11
BACKGROUND

12. 1. Usability and UX design are critical to overall user engagement and
experience, and ultimately, the success of transactional mobile apps
2. Neuromarketing techniques provide more accurate insights into the emotional
response of subjects, and are ultimately more indicative of human behavior
12
RESEARCH HYPOTHESIS

13. METHODOLOGY

14. Participants
The study was conducted in March 2013. The group
included 30 participants with the following attributes:
• 14 men, 16 women
• Young professionals
• 25-45 years of age, with an average age of 31
• Owners and users of smartphones
(iPhone 4, 4s or 5)
Stimuli
The stimuli came in the form of three iOS mobile
transactional applications across three verticals including
quick service restaurants (QSR), retail, and hospitality.
Participants viewed:
1. Pizza Pizza
2. Best Buy Inc.
3. Hyatt Hotels Corporation
5 Step user journey
The subjects participated in the following user journey:
1. App download and open
2. Browse products and services
3. Select a predetermined product or service and add
to cart
4. Go to checkout
5. Purchase by entering personal information
Technology
SURVEY DISTRIBUTOR
FluidSurveys.com
EYE-TRACKING DEVICE
Tobii Glasses Eye Tracker, 30 Hz, dark pupil. Tobii Studio
Enterprise Software.
EMOTIV EEG NEUROHEADSET
14 channels - International 10-20 System - AF3, F7, F3,
FC5, T7, P7, O1, O2, P8, T8, FC6, F4, F8, AF4
2048 Hz internal sampling – down sampled to 128 Hz
0.2 – 45Hz bandwidth
Digital notch filters at 50Hz and 60Hz
Digital 5th order Sinc filter
Emotiv proprietary impedance monitoring
EEG ANALYSIS
Artifact rejection and independent component analysis
Fast-Fourier Transform with rectangular windowing
Extraction of emotional engagement & attentional
activation
Within-subject z-score normalization and outlier rejection
SELECTION
Evaluation of options &
decision making.
DISCOVERY
Gaining familiarity
with mobile app
environment.
CONVERSION
Final call to action; the
payment step.
METHODOLOGY
Technology 14

15. 15
EEG &
EYE-TRACKING
POST-STUDY
SURVEY
PRE-STUDY
SURVEY
METHODOLOGY
Steps & Results
Pre-Study Survey
Asses spoken (explicit) opinions of each brand and the mobile usage
patterns
1
2
3
4
Eye Tracking - Navigating each app freely for a 1-2 minutes
Qualitative insights about first impression and most visited pages
Eye Tracking and EEG receiving step-by-step instruction to get
familiar with app, evaluate options and proceed with the CTA. *refer to
diagram on the right.
Qualitative and quantitative insights about brain reaction (implicit) and
visual attention.
Post-Study survey
Asses spoken opinions after utilizing each app.

16. Technology Overview
Neuromarketing is an umbrella term which encompasses
neuroscience, biometrics and other methodologies.
Neuroscience technologies include EEG, fMRI and MEG. For the
purpose of this study, we elected to use EEG since it was the most
portable and it allowed participants to physically interact with a
mobile phone. By placing sensors on designated areas of the head,
we measured which stages of a mobile transaction elicited positive
or negative emotions, and which areas received the most attention.
While brain measurements are very interesting, it was more
beneficial to couple this data with a secondary measure, since it
could confirm what the brain manifests and add another layer of
insight. Therefore, a commonly used biometric technology, eye-
tracking, was combined with EEG in order to highlight where the
participant was looking. Areas of visual interest are highly correlated
with attention, hence it was important to see not only how
participants felt but why (i.e. where are they looking).
EEG alone would not explain what was visually interesting, and eye-
tracking alone would not explain whether a visual stimuli elicits
positive or negative emotions in the brain. For example, one may
look at a picture of a train wreck for a long time, but it won’t mean
that he or she has a positive emotional engagement with the image.
This is why it was more powerful to combine EEG with eye-tracking.
16
METHODOLOGY

17. 17
The complete study was composed of 30 compensated
participants, 14 females, and 16 males.
Upon arrival, each participant completed a release form. This
allowed Plastic Mobile and True Impact Marketing to use their
personal information to identify them as part of the entire group of
participants, for both research and marketing purposes.
Each person completed an 11 question pre-study survey. The
survey gathered their personal information and helped us
gauge their perception of the 3 brands before exposure to the
mobile apps.
Upon completion of the pre-study survey, each participant
was outfitted with the eye-tracking glasses, and calibrated
accordingly, using a 9 point calibration.
Each participant was instructed to wear the glasses, and
navigate each app freely for 1.5 minutes per app. The goal
was to ensure we eliminated novelty effects, and that people
were comfortable getting into the app and performing a given
task.
They were instructed to bring their own iPhone 4, 4S or 5. The
person was seated at a table, with their phone being held up
in front of them by a table-top phone stand. They were seated
about an arm’s length away from the iPhone. The device was
positioned within comfortable reach of their hand.
After the free navigation, each participant was outfitted with
the EEG headset, and had a rest period of 3 minutes before
starting the test. Next to the iPhone was a laptop which
presented the navigation instructions in a slide show. The
participant would press the space bar to move forward from
one instruction to the next.
The study consisted of 3 tasks on the iPhone apps, all of
which resulted in a transaction; order a medium pizza and
select 3 toppings, buy a waterproof digital camera, and book
a hotel room for 5 nights in New York.
The task order was randomized. Each person went through
and completed each task, guided by the step-by-step
instructions, without assistance.
Upon completion of the purchase journeys, their headsets and
eye-tracking glasses were removed.
The participants then completed a post-study survey of 16
questions in order to detect any variance of brand perception
from the pre-study phase. We included some of the questions
of the pre-study survey as well as additional questions to
gather their explicit opinions of the mobile apps. Their explicit
opinions were then compared with their implicit (brain
measurements) analyses gathered from the EEG headset and
eye-tracking results.
Upon completion of the post-study survey, the participant was
released and rewarded for their time.
METHODOLOGY
Overview

18. The two main metrics of this study
include Emotional Engagement,or the
ability to determine what a user likes and
dislikes, and Attentional Activation,
measuring how engaged a user is in what
they are viewing
18
METHODOLOGY

19. Neuromarketing involves the use of brain-imaging technology to gather consumer insights.
In this neuromarketing study, EEG (electroencephalography) headsets were placed on the heads of participants. The
brain’s electrical activity (brainwave data) is recorded while the individual is exposed to various media stimuli.
The data is decoded into two distinct metrics: emotional engagement and attentional activation.
We analyzed left-right alpha asymmetry in the pre-frontal cortex to measure and track changes in the subjects’
emotional reactions.
Greater relative activity in the left frontal region (blue area) strongly correlated with approach motivations, including
liking, wanting, and motivating to action purchase intent and willingness to pay.
Greater relative activity in the right frontal region (yellow area) correlated with withdrawal motivations, such as
disliking, disgust and avoidance behavior.*
*Based on studies by neuroscientists Davidson, Harmon-Jones, Ravaja, Ohme, et al. "
We analyzed alpha wave desynchronization in the occipital cortex (red area) in order to measure and track
respondents’ activations of attention.
Increases in attentional activation are strongly correlated with recall, cognitive, processing and learning.*
*Based on studies by neuroscientists Rothschild, Klimesch, Woldorff, et al."
19
Right Frontal
Negative Withdrawal
Left Frontal
Positive Approach
Occipital Attention
METHODOLOGY

20. FINDINGS
&
INSIGHTS

21. The following findings are based on the
data from our pre- and post-study
surveys, EEG & eye-tracking studies, as
well as existing literature. For data,
please see the Appendix.
21

22. 1. TO BROWSE OR
TO CHECKOUT

23. While users may say they like browsing
more than checkout, our data suggests
the opposite to be true.
23

24. 24
EEG Emotional Engagement While Using App
We monitored participants’ emotional engagement - or their positive and negative emotions - while using the applications.
The Results
The Pizza Pizza app saw a valley during
browsing at 2%, but checkout was at an all-
time high at 100% emotional engagement.
The Best Buy app saw an emotional peak as
it opened, at 92%, and a low of 16%
engagement at selection.
Participants were also most engaged in the
Hyatt app at launch with 80% engagement,
and least emotionally engaged at checkout,
showing 0%.
EmotionalEngagement(%)
User Journey
FINDINGS
OPEN APP BROWSE SELECT ADD TO CART CONFIRMATION
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
110%
P"##$%P"##$ & '()%& * + , +$))

25. 25
EEG Attentional Engagement While Using App
We monitored participants’ attentional activity - or level of interest - while using the applications.
The Results
The Pizza Pizza app also saw variation in
participants’ attentional activity, being
most interested as they opened the app at
86%, and least interested as they
confirmed their purchase at 48%.
The Best Buy app likewise saw a peak in
attention as the app opened at 56%, and
a low of 0% at the end of the journey.
The Hyatt app also saw a peak in
attention at open at 41%, and a low at
confirmation at 8%.
AttentionalActivity(%)
User Journey
FINDINGS
OPEN APP BROWSE SELECT ADD TO CART CONFIRMATION
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
110%
P"##$%P"##$ & '()%& * + , +$))

26. 26
Mobile Application Post-Study Survey vs EEG Responses
Survey questions: What was your favorite part of the experience, and what was your least favorite part?
The Results
When asked what their favorite part of the Pizza Pizza app experience
was, 62% of participants said their favorite part was selection and
55% said their least favorite was checkout. However, according to the
EEG monitoring, selection was second lowest in terms of emotional
engagement, at 19%, and also second lowest for attention activity at
56%. According to their level of emotion and interest, participants’
favorite part was the checkout, at 100% emotionally and 76%
attention activity.
NumberofPeopleEEGScale(%)
User Journey
User Journey
FINDINGS
!"#$% & "'("#$%
OPEN APP
CREATE
PIZZA
SIZE/
TOPPINGS
CHECKOUT
CREATE NEW
ACCOUNT
0%
20%
40%
60%
80%
100%
120%
0
5
10
15
20
25
DISCOVERY
open & create
SELECTION
size & toppings
CHECKOUT
create new account

27. 27
The Results:
When asked what their favorite part of the Best Buy app was, 62% of
participants explicitly stated that the selection was their favorite, however,
their emotional engagement was at its lowest point at 16%. Although,
their attentional engagement spiked at selection from 24% to 46% (refer
to Appendix).
In the case of Hyatt, when asked to identify their most and least favorite
parts of the experience in two separate questions, it appears they were
torn between a love and hate for selection. 52% suggested it was their
least favorite, but 66% explicitly stated it was their favorite. According to
the EEG monitoring, their emotion/attention? showed a significant spike
at selection, going from 15% to 60% engaged.
BEST BUY
HYATT
NumberofPeopleNumberofPeople
User Journey
User Journey
FINDINGS
Mobile Application Post-Study Survey: Best Buy & Hyatt
Survey questions: What was your favorite part of the experience, and what was your least favorite part?
0
5
10
15
20
DISCOVERY
open & browse
SELECTION
select & add to cart
CHECKOUT
!"#$% & "'("#$%
0
5
10
15
20
DISCOVERY
open & browse
SELECTION
select & book room
CHECKOUT
DislikedLiked

28. Observation Recap
What our participants explicitly stated in the surveys was met with the standard biases that are typical of questionnaires and surveys. While the Pizza Pizza
post-study survey suggested that users thought they most enjoyed the selection experience, they were not nearly as emotionally engaged as when they
were checking out, which they explicitly stated they disliked most. In the case of the Best Buy app, users explicitly stated their favorite step was the
selection, however according to our EEG results, it was the lowest point for emotional engagement at 16%. Lastly, in the case of the Hyatt app, our
participants’ explicit responses were confused and contradictory.
Recommendations
Ultimately, we can determine that people don’t always say what they actually think or mean. While we know that the browsing is what most mobile users
are doing on their devices, it may not be the thing that gets them the most excited. The Pizza Pizza app has a very simple and straightforward checkout
user experience, coupled with a more immediate reward, allowing users to be both emotionally invested and keenly interested. Whereas the Best Buy app
and Hyatt apps have lengthier and more cumbersome checkout stages. Conclusively, once you have something a consumer wants to purchase, it’s
important to give it to them as quickly and easily as possible.
28
PIZZA PIZZA BEST BUY HYATT
BROWSING VS CHECKOUT

29. 2. LIKE THE APP,
LIKE THE BRAND

30. For better or worse, apps can influence
overall brand perception.
30

31. 31
The Results:
The word clouds represent the words used to
describe each app. The size of the word
determines how many times it was listed by
each participant in the pre-study survey.
In the case of the Pizza Pizza app, most
participants described the app as:
Convenient, delicious, innovative and
affordable.
The Best buy app was described most as:
Technical, affordable, variety and practical.
The Hyatt app was described by most as:
Classy, comfort and luxury
Best
Buy
Hyatt
Pizza
Pizza
FINDINGS
Mobile Application Pre-Study Survey:
In the pre-study, we asked participants to describe the brand in one word.

32. 32
The Results:
The word clouds represent the words used to
describe each app. The size of the word
determines how many times it was listed by
each participant in the post-study survey.
In the case of the Pizza Pizza app, most
participants described the app as: Fun,
delicious, fast, affordable and reliable.
The Best buy app was described most as:
Technical, affordable, variety and practical.
The Hyatt app was described by most as:
Luxury, expensive, complicated and
pretentious
Best
Buy
Hyatt
Pizza
Pizza
FINDINGS
Mobile Application Post-Study Survey:
We asked the same question again in the post-study survey to determine if anything had changed after using the apps

33. 33
The Questions
In both the pre and post-study surveys, we asked participants
several rating scale questions about the brands:
1. Is the brand innovative?
2. Does the brand inspire loyalty?
3. Is the brand trusted?
4. Does the brand provide superior quality?
The Results
We found that after using the applications, there were no significant decreases
in people’s responses, however, there were several increases to note:
• The Pizza Pizza app saw a 54% increase in participants who thought the
brand was innovative.
• The Best Buy app saw a 10% and 11% increase, respectively, in participants
who trusted the brand and thought the brand offered superior quality.
• Last, the Hyatt app saw a 24% increase in participants who thought the
brand to be innovative and offering superior quality.
FINDINGS
Mobile Application Pre & Post-study Survey

34. Observation Recap
In the case of all three brands, participants’ responses from the pre- to post-study survey were more positive after using the applications. They
found both Pizza Pizza and Hyatt to be more innovative, and Best Buy and Hyatt to offer superior quality. As well, we found the Best Buy brand
to be slightly more trusted by users after using the application.
In the pre-study survey, we asked participants to list the words they most identified with the brand before using the app and then again, after the
EEG and eye-tracking experiments. Pizza Pizza’s word responses had a slight change. Participants saw the brand as “fun, delicious, fast,
affordable and reliable” before using the app, and then, “convenient, delicious, innovative and affordable “afterwards. The survey results for
Pizza Pizza indicated that the app increased participants’ perception of the brand’s convenience, which is aligned with the inherent value of
mobile. With Best Buy, however, word responses remained almost the same, with participants seeing the brand mostly as “technical, affordable,
reliable and variety” both before and after using the app. Participants originally identified the Hyatt brand with the words “classy, comfort and
luxury”. However, after using the app, they identified the brand with the words “luxury, expensive, complicated and pretentious”.
Recommendations
While the study demonstrated that having a mobile offering can improve brand perception and encourage customers to view the brand as more
innovative, putting out an application that doesn’t offer an engaging experience can hinder the participants’ perception of the brand. For
instance, Hyatt’s app elicited a slightly more negative response in terms of the pre- and post-study survey word associations. This aligns with
the Hyatt EEG results, which showed that the Hyatt app experience ended with an all-time low in emotional engagement at 0%, and the Pizza
Pizza app, which finished on an all-time high of 100%. Lesson learned: finishing your mobile transaction on a high note can help produce an
overall better brand perception.
34
APPS AND BRAND PERCEPTION

35. 3. USE SCREEN REAL
ESTATE WISELY

36. How we use the limited real estate of
mobile screens makes a difference.
36

37. 37
The Results:
In the Pizza Pizza app, participants
spent 35.2 seconds on the selection
page, concentrating their visual focus
on pizza images, size selection and
prices.
In the Best Buy application, the average
time spent on the selection page was
22.8 seconds, and participants’ visual
attention was concentrated on the price
and the image of each item.
Lastly, participants spent 38.0 seconds
during the Hyatt app process and also
saw the areas of focus on the images
and the prices.
FINDINGS
Eye-tracking Heat Maps On Selection Stages
We tracked participants’ eye focus as they were in the selection stage to see where their area of focus was concentrated
22.8s Time Spent
BEST BUY
SELECT CAMERA
35.2s Time Spent
PIZZA PIZZA
CREATE PIZZA
38.0s Time Spent
HYATT
SELECT HOTEL

38. Observation Recap
All three applications saw participants focusing their attention on images and prices during the selection stage.
The bigger the image was, the more focus was observed. For instance, in the Pizza Pizza app, participants concentrated their gaze on the
images of the pre-made pizzas over everything else. Size options also drew participants’ focus, which was in line with the rest of our
observation, as they were visual assets.
In the Best Buy app, participants didn’t read the descriptions, in spite of the fact that they were taking up half of the screen real-estate, and
focused their attention on the images and prices. The Hyatt app saw a similar treatment of their hotel descriptions, with participants focusing
more on the images and the prices. Interestingly, the opening of the app and the selection, where there were images, elicited the best emotional
response from participants in both the Best Buy and Hyatt apps.
Recommendations
The use of mobile screen real estate is an important consideration when designing applications. With such a limited working space, and a short
user attention span, what we put on the screen needs to resonate immediately with the user. Since the eye-tracking and emotional engagement
responses suggest that users are most interested in and most likely to connect emotionally with images, optimizing every pixel should be a core
focus for design considerations. The assessment of the content on each page, and how that content will be prioritized would be another
important design consideration. By maximizing the browsing space with what users are most interested in, the content can capture the attention
of the user and then allow for exploration of more in-depth information. Best Buy displayed an image with the corresponding price, and only a
few participants looked to the product details. Alternatively, they could have prompted the user to tap through for more details in order to
maximize the image size and quality on the screen, while showing the price in clear view.
The use of high-quality images and assets as standardized in brand’s other mediums, such as in-store visuals or printed materials, should be
considered for mobile applications. For Pizza Pizza, high-fidelity food images complemented the motivation of hunger. Also, allowing users to
have quick and accessible alternative views for products, and the ability to zoom in and out for a closer look mimics the in-store experience that
they’re already accustomed to.
38
OPTIMIZING SCREEN REAL ESTATE

39. 4. IMAGES ARE
MORE THAN
JUST PRETTY
PICTURES

40. The images used in mobile apps serve
a greater purpose than just making
aesthetically pleasing accents.
40

41. 41
The Results:
The Hyatt app opened to a large,
nearly full-screen image of two
people. The participants’ visual
focus was concentrated on the
faces in the picture.
FINDINGS
Eye-Tracking Heat Map On Hyatt App Load Page
We tracked the participants’ visual focus as they opened the apps to see what they were looking at first and most
BEST BUY
OPEN APP
PIZZA PIZZA
OPEN APP
HYATT
OPEN APP

42. 42
The Results:
Taking a closer look, the Hyatt app
opened to a peak emotional response
of 80% where participants were
exposed to the opening image.
The select hotel phase, where
participants scrolled through a list of
hotels, also saw a jump in emotional
engagement, from 15% to 60%.
EmotionalEngagement(%)
User Journey
FINDINGS
Hyatt Mobile App: EEG Emotional Engagement
We monitored participants’ emotional engagement - or their positive and negative emotions - while using the Hyatt app
OPEN APP
BROWSE/FIND
HOTEL
SELECT HOTEL
BOOK KING
SIZE BED
CONFIRMATION
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%

43. 43
The Results:
The attentional engagement at the
opening of the Hyatt app was aligned
with the emotional trend of peaking,
at 55%.
Attentional activation also increased
at the selection phase where there
were images and price, from 14% to
25%.
The confirmation of the booking
elicited the lowest attentional activity.
EmotionalEngagement(%)
User Journey
FINDINGS
Hyatt Mobile App: EEG Attentional Activation
We monitored participants’ attentional activity - or level of interest - while using the Hyatt App
0%
10%
20%
30%
40%
50%
60%
70%
OPEN APP
BROWSE/FIND
HOTEL
SELECT HOTEL
BOOK KING
SIZE BED
CONFIRMATION

44. 44
The Results:
When comparing the three apps in
terms of emotional engagement; the
Hyatt app opens to the highest level of
positive emotional engagement, and
dips into the negative significantly
during the selection phase.
The Best Buy app also opens into the
emotional peak, and ends on the
lowest point barely lifting into the
positive during the selection phase.
The Pizza Pizza app starts off on low
emotion and steadily builds up to the
highest level of emotional engagement
at checkout.
EmotionalEngagement
User Journey
FINDINGS
EGG Emotional Engagement While Using App Images
We monitored participants’ emotional engagement - or their positive and negative emotions - while using the applications
-0.4
-0.3
-0.2
-0.1
0.0
0.2
0.3
0.1
0.4
OPEN APP FIND ITEM SELECT ITEM CHECKOUT ENTER INFO
P"##$%P"##$ & '()%& * + , +$))

45. Observation Recap
The study showed that images encourage positive emotional and attentional engagement. The Hyatt app opens to a nearly full screen image of
people, spiking a peak in both emotion and attention, at 80% and 55% respectively. When comparing the three apps phase by phase, the Hyatt
app elicited the highest emotional response upon opening. The emotional peak of the Best Buy app was also at the opening phase, which had
images,. The only other phase that the emotional activation ventured into the positive, for the Best Buy app, was during selection where the
product list included images as well. Furthermore, we observed that the highest level of emotional activation in the study, at 100%, was during
the checkout phase of the Pizza Pizza app. When compared to the other checkout processes, the Pizza Pizza checkout phase displayed the
most visual of the three and included images. There’s a clear correlation between the use of relevant and contextual images and positive
emotional activation.
Recommendations
The Hyatt app strategically placed the image of a father and son upon app launch, as it aligns with other research that indicates that women,
particularly moms who lead smartphone adoption in the U.S., generally make travel plans for their families. We recommend taking a page out of
Hyatt’s book and using images that appeal to your specific target audience and are relevant to your product or service. Use high fidelity imagery
that reflects your brand and resonates with the emotional experience your business promises to deliver. In this particular case, brands don’t
need to be conservative since the results suggest that bigger is better.
With product shots, allow users to see the products from various angles, and provide alternate views with the ability to zoom into the image and
zoom for details. Consider the placement of the images and the frequency of their appearance. For instance, a product shot should be front and
centre, and have a clear focal point. Then provide visual cues or icons in the upper lefthand corner for users to tap for more information and
detailed specifications.
45
IMPORTANCE OF IMAGES

46. 5. GET TO THE
POINT!

47. Longer load times in mobile apps can
cause frustration in users and risk app
abandonment.
47

48. 48
The Results:
The Hyatt app boasted the fastest load
time upon opening of app at 5.4
seconds. Though the selection stage
loaded slowly.
The Best Buy app also loads quickly
upon opening at 6.4 seconds.
The Pizza Pizza app had a slower load
time for first-time users, as it offers an
app usage guide, causing a delay in
opening of the full app experience.
FINDINGS
Eye-Tracking Heat Maps on App Loading Pages
We tracked the participants’ eye focus as they opened the apps
BEST BUY
OPEN APP
6.4s Time To Load
PIZZA PIZZA
OPEN APP
7.2s Time To Load 5.4s Time To Load
HYATT
OPEN APP

49. The Results:
The Hyatt app was the fastest to load at 5.4s,
and saw a peak emotional engagement of
80%.
The Best Buy app loaded quite quickly and
also opened at a peak emotional engagement
of 92%.
The Pizza Pizza app, however, had the
slowest load time at 7.2 seconds and opened
to a low emotional engagement of 20%.
49
EmotionalEngagement(%)
User Journey
FINDINGS
EEG Emotional Engagement While Using App - Load Times
We monitored participants’ emotional engagement - or their positive and negative emotions - while using the applications
OPEN APP BROWSE SELECT ADD TO CART CONFIRMATION
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
110%
P"##$%P"##$ & '()%& * + , +$))

50. Observation Recap
The Pizza Pizza app had the slowest load time at 7.2 seconds and opens to a low emotional engagement of 20%. The heat map shows that the
focus of users’ visual attention was concentrated on the loading icon while they waited for the app to launch. The Best Buy app loads quite
quickly and also opens to a peak emotional engagement of 92%. And, while the Hyatt app was the fastest to load at 5.4 seconds, and saw a
peak emotional engagement of 80% at the app launch, their loading of the Find Hotel function which correlated to the select item phase was
rather slow, eliciting a severe drop in emotional engagement from 80% to 15%.
Recommendations
Don’t underestimate the value of a first impression. Ensure that the best effort is made to load the mobile app quickly so users, who tend to have
less patience with mobile experiences than any other medium, aren’t kept waiting. Mobile smartphone users are likely on-the-go, with divided
attention between various environmental stimuli, and probably performing a multitude of conscious tasks. Therefore, their ability to stay
attentionally engaged while waiting for yet another task is greatly hindered.
It is found that variance in device capabilities paired with enhancements in rich mobile user experiences sometimes threaten load times. This
may be forgiven at the outset of an app experience as the Pizza Pizza results suggested, but once the app is up and running any delays or
inconsistencies will likely diminish user confidence. Other research suggests that the leading causes of app abandonment are crashing and
bugs. In the Hyatt application, mid-journey load times often out-timed the initial app loading times, and the drop in emotional engagement
(frustration) reflected those valleys. Ideally, load times for apps should be minimal (less than 5 seconds), with no delays throughout the purchase
path, especially at checkout. But if running rich content is necessary, choose the beginning and ensure that all content is ready for smooth
navigation once the app is running.
50
EFFECTIVE LOAD TIMES

51. 6. KEEP THEM
INTERESTED,
OR LOSE THEM
FOREVER

52. Maintaining user interest over the
course of a transaction is pertinent to
encouraging repeat usage of apps.
52

53. 53
The Results:
In the Best Buy and Hyatt apps, participants’
level of interest decreases over the course of
the five steps, finishing at a point of
disinterest.
While the Pizza Pizza app also saw a decrease
in attention, participants’ EEG level remained
above the median line suggesting maintained
interest.
Pizza Pizza and Best Buy apps elicit a similar
high point in interest at the select item phase,
at 56% and 46% respectively. The Hyatt app
sees a a drop to disinterest after the first step
and an ongoing decrease below median line
until the end of the user journey.
User Journey
AttentionActivation
FINDINGS
EEG Attentional Activation While Using App
We monitored participants’ attentional activation - or level of interest - while using the applications
-1.0
-0.5
0.0
1.0
0.5
1.5
OPEN APP FIND ITEM SELECT ITEM CHECKOUT ENTER INFO
P"##$%P"##$ & '()%& * + , +$))

54. 54
The Results:
In the post-study survey, majority of the participants suggested they
would be interested in using the Pizza Pizza and Best Buy apps
again.
However, a significant group of 38% of the participants suggested
they would not use the Hyatt app again (refer to Appendix).
FINDINGS
Mobile Application Pre-Study Survey
Will you use this app again?
79%
14%
4% 3%
48%
17%
11%
24%

55. Observation Recap
The Pizza Pizza app was the only one of the three to consistently maintain users interest above the median line throughout the course of the
transaction. Best Buy saw a decrease in attentional engagement, but spiked from disinterest to interest during the select item phase. When
asked in the post-study survey, 79% of Pizza Pizza app users and 48% of Best Buy users suggested they would definitely use the two apps
again in the distant future.
Recommendations
There is, of course, more to an app than just how aesthetically pleasing it is to the user. A part of keeping users “interested” is ensuring that you
have an engaging user experience that maintains a user’s interest over the course of the mobile purchasing journey. Despite the product or
service a brand is offering for purchase on mobile, ensuring that the user’s attention is engaged during each phase of the process is essential to
closing the commerce loop. For example, something the Pizza Pizza and Best Buy apps have in common is the use of high fidelity imagery of
the products and services during the selection process, thereby keeping the user’s attention on the task of making their selection. Also, using
visual cues to guide users through the journey and preventing confusion as to the next steps is critical to creating a frictionless purchasing
experience. Ensure that the cues are visual, simple, and easy to interpret, yet interesting and engaging. A user shouldn’t have to decipher
anything more than a word to move to the next step. If anything, no words are preferable. People can process signs and visual cues instinctively,
whereas reading is a cognitive function that takes more conscious effort to process. So use signs and images where possible. When a user can
successfully complete a new task, a sense of accomplishment is created and they’re more likely to want to repeat the experience.
55
MAINTAINING USER INTEREST

56. 7. IF THEY LIKE IT,
THEY’LL TELL THEIR
FRIENDS

57. The brands that saw an increase in
emotional engagement towards the
brand logo were also the brands that
users said they would recommend to
others.
57

58. 58
The Results:
Pizza Pizza saw a 15% increase in
emotional engagement towards the logo
after participants used the mobile
application, going up from 28% to 43%.
Best Buy saw a 58% increase in emotional
engagement, going up from 8% to 66%.
Hyatt saw a 3% decrease in emotional
engagement towards the logo after using
the application, going from 41% down to
38%.
User Journey
EmotionalEngagement(%)
FINDINGS
EEG Response to Logo Before and After Using the App
While monitoring EEG activity, we showed participants the brand logo before and after thy journeyed the purchase path

59. 59
The Results:
When asked if they would recommend the app to
others, the participants’ responses changed from the
pre- to post-study surveys.
Pizza Pizza saw a 39% increase in the number of
people who would recommend the app after using it.
Best Buy saw a 16% increase in favour of the app after
using it.
Pizza Pizza Recommendation
Best Buy Recommendation
NumberofPeopleNumberofPeople
FINDINGS
Mobile Application Pre & Post-Study Surveys
Would you recommend this app to others?
0
5
10
15
STRONGLY
DISAGREE
DISAGREE NEITHER
STRONGLY
AGREE
AGREE
0
4
8
14
2
6
10
12
16
18
STRONGLY
DISAGREE
DISAGREE NEITHER
STRONGLY
AGREE
AGREE
!"#$%&'"(#) !*+,$%&'"(#)
P"#$%&'"(#) P*+,$%&'"(#)

60. Observation Recap
According to our findings, both Best Buy and Pizza Pizza saw an increase in emotional engagement towards the brand logo directly after using
the application. Hyatt, on the other hand, saw a slight decrease. The application that saw the highest increase in referrals after using the app,
with a rise of 39%, was Pizza Pizza. As the brand maintained attention activation above the median line, indicating consistent interest
throughout the experience, as well as an increase in emotional engagement over the course of the journey, ending at an emotional peak,
participants’ responses showed they would refer Pizza Pizza to a friend the most, out of all three apps.
Recommendations
It’s obvious that a positive app experience will encourage users to talk about it, since we see how vocal both happy and unhappy users can be
in the app stores and on their social media platforms. Every brand has a unique set of usability requirements that must be defined by way of a
mobile-first strategy at the outset of designing the appropriate mobile experience for the brand. By adhering to usability guidelines of 1)
streamlining the in-app checkout process, 2) aiming to end the mobile commerce experience on an emotionally high positive note and, 3) further
enhancing the checkout with a fun coupon feature; an enhanced perception of a brand and its offering will be recognized. Thus, repeat usage
and recommending of a brand’s mobile app is more likely to occur.
60
MAKING IT RECOMMENDABLE

61. CONCLUSION

62. Knowing what users are actually
seeing, feeling and paying attention to
can help brands and businesses design
a stellar mobile user experience.
62

63. Conclusion
The results of the study have illustrated that mobile usability and
design are critical to mobile user experience and that
neuromarketing techniques provide deeper insights on user behavior
and their emotional response to various stages of the mobile path to
purchase. By pairing portable EEG technology with eye-tracking
technology, we garnered a deeper understanding of what users were
responding to in mobile app journeys. Knowing what mobile users
were seeing, feeling and paying attention to while using a brand’s
mobile app can ultimately help IT personnel and marketers design
an intuitive and engaging mobile user experience.
According to the results of the study, a user’s attention and
engagement hinges heavily on the use of relevant imagery to
optimize screen real estate, intuitive visual cues that nudge users
along navigation, and quick load times. Firstly, marketers must
optimize screen real estate with high-quality imagery that is relevant
to the brand and caters to the user’s specific need. Moreover, using
visual cues, in place of instructive language, to guide users along
removes the necessity of conscious processing, therefore allowing a
frictionless interpretation of navigation. This in turn maintains a
steady level of attention and is less likely to create frustration. Lastly,
the digital savvy, urban professional millennials (who made up the
majority of the sample) expect quick load times and instantaneous
responsiveness. Including these elements in a mobile app will help
them feel that sense of accomplishment as they move through the
stages of the mobile user journey.
63
CONCLUSION

64. Although these recommended tactics will maintain user interest and
attention throughout the mobile user journey, it’s imperative that the
journey should end on a positive emotion, specifically at and
throughout the checkout phase. Making it easy and engaging for
customers to purchase products or services is likely to lead to
repeat usage. Also, by creating incentives, like a fun scratch and win
game at checkout, brands can leverage interaction on mobile to
yield loyalty behavior. Collectively, the insights and
recommendations from the study aim to ensure the user’s utmost
engagement with the overall app experience, which can enhance
brand perception and lead to a higher likelihood of user
recommendations.
This study has given us the opportunity to move from speculations
on usability and design practices to measurable results. This will
shape the way we, in the new realm of mobile marketing, look at the
user experience and design of transactional mobile applications. It
would be of significant interest for both the neuromarketing and
mobile industries to expand on these learnings, and reach beyond
mobile commerce into other elements in comprehensive mobile
applications including gaming, utilities, and location-based services.
64
CONCLUSION

65. APPENDIX:
FULL REPORT DATA

66. SURVEY DATA

67. The following is summary of the survey
data used to create this report.
67

68. FREQUENTLY USED APPS
68
13%
12%
9%
7%
7%7%
7%
7%
6%
4%
4%
4%
4%
3%
3%
2% SOCIAL NETWORKING
MAPS
GAMES
ENTERTAINMENT
WEATHER
UTILITIES
PRODUCTIVITY
FINANCE
NEWS
SHOPPING
FOOD ORDERING
RECIPE
LOYALTY
SPORTS
LIFESTYLE/CATALOGUE
TRAVEL
PASSBOOK
SURVEY DATA

69. Facts
• 30% of participants stated there is no limit to how
much they would spend in a mobile app transaction
• 45% stated they frequently spend more than $25
• 59% stated that the main deterrent in mobile
purchasing is the lack of “user friendliness”
• 14% were deterred by incompatibility with their
device
• 10% were deterred by the failure to deliver on the
brand promise by not accurately reflecting the brand
values
• 7% were deterred by the aesthetics of the experience
My Purchase limit through App
I am discouraged to shop if
69
59%7%%
14%
10%
%ageofParticipants
Purchase Limit Amount ($)
SURVEY DATA
!"
#"
$!"
$#"
%!"
%#"
&!"
&#"
'!"
'#"
(%# (#! ($!! ) * +,-. -/(#!!
APP IS NOT USER FRIENDTLY
APP IS NOT AESTHETICALLY PLEASING
APP IS NOT AVAILABLE FOR MY DEVICE
APP DOES NOT DELIVER ON THE BRAND PROMISE

70. 72%
55%
45%
34%
34%
24%
21%
10%
70
SURVEY DATA
!"# $"# %"# "#&"#
' (b*+,-.//0-01(2+3-b,-.4-
,56,46*(4-(7-.-b8.4390-: ,b0*6,
;-61*4<-61,-m (b*+,-/1(4,-*0-.-/,80(4.+-
>(m m 24*>.6(8?-+*<,3-b@-m (06-/,(/+,
;-8,A2+.8+@-20,-m (b*+,-.//+*>.6*(40-
78(m -b8.430
B (: 4+(.3,3-.//0-A,4,8.++@-m ,,6-m @-
,5/,>6.6*(40-(7-61,-b8.43
;-1.C,-/28>1.0,3-.-/8(32>6-D0,8C*>,
-618(2A1-.-m (b*+,-.//
' (b*+,-.//0-01(2+3-(77,8-3*77,8,46-
0,8C*>,0-61.4-61,-: ,b0*6,
' (b*+,-.//0-78(m -8,>(A4*z.b+,-b8.430-
+,.C,-m (8,-6(-b,-3,0*8,3
;-20,-b8.43,3-.//0-,C,4-61(2A1-
61,@-3(496-.+: .@0-: (8<

71. We asked the same questions
pertaining to brand perception before
and after using the mobile applications.
Overall, participants’ responses resulted
in a more positive perception after using
the app.
71

72. Participants were asked to respond to some of the
same questions before and after using the Best Buy
mobile app. As seen in the graphs to the left,
participants’ explicit opinions, suggested that using the
Best Buy app increases the justification of a price
premium and the recommendation to others.
Does Best Buy justify a price premium?
67% increase
Will you recommend this app to others:
16% increase
72
Does Best Buy justify a price premium?
NumberofParticipantsNumberofParticipants
Will you recommend this to others?
SURVEY DATA
Best Buy Mobile App: Survey
0
4
8
14
2
6
10
12
16
STRONGLY
DISAGREE
DISAGREE NEITHER
STRONGLY
AGREE
AGREE
0
4
8
14
2
6
10
12
16
18
STRONGLY
DISAGREE
DISAGREE NEITHER
STRONGLY
AGREE
AGREE
!"#$%&'"(#) !*+,$%&'"(#)
!"#$%&'"(#) !*+,$%&'"(#)

73. Before using the app, the brand was described as:
After using the app, the brand was described as:
73
BEST BUY BRAND PERCEPTION

74. When asked the same set of questions before using
the Pizza Pizza mobile app, and then again
afterwards, the Pizza Pizza brand was seen to be
more innovative and participants would be more
likely to recommend it to others.
Pizza Pizza is innovative:
54% increase
They will recommend to others:
39% increase
74
NumberofParticipantsNumberofParticipants
Will you recommend this to others?
Is Pizza Pizza innovative?
SURVEY DATA
Pizza Pizza Mobile App: Survey Says
0
5
10
15
STRONGLY
DISAGREE
DISAGREE NEITHER
STRONGLY
AGREE
AGREE
0
5
10
15
20
STRONGLY
DISAGREE
DISAGREE NEITHER
STRONGLY
AGREE
AGREE
!"#$%&'"(#û !)*t $%&'"(#û
!"#$%&'"(#û !)*t $%&'"(#û

75. Before using the app, the brand was described as:
After using the app, the brand was described as:
75
PIZZA PIZZA BRAND PERCEPTION

76. According to the explicit opinions of the participants
of the pre- and post-study surveys, participants
viewed Hyatt as more innovative and of superior
quality after they had used the app.
Hyatt provides superior quality:
31% increase
Hyatt is innovative:
78% increase
76
NumberofParticipantsNumberofParticipants
Does Hyatt provide superior quality?
Is Hyatt innovative?
SURVEY DATA
Hyatt Mobile App: Survey
0
4
8
14
2
6
10
12
STRONGLY
DISAGREE
DISAGREE NEITHER
STRONGLY
AGREE
AGREE
0
4
8
14
2
6
10
12
16
18
20
STRONGLY
DISAGREE
DISAGREE NEITHER
STRONGLY
AGREE
AGREE
!"#$%&'"(#) !*+,$%&'"(#)
!"#$%&'"(#) !*+,$%&'"(#)

77. 77
Before using the app, the brand was described as:
After using the app, the brand was described as:
HYATT BRAND PERCEPTION

78. EEG &
EYE-TRACKING
DATA

79. PIZZA PIZZA
MOBILE APP

80. Loading time was slow as a text box pops up when launching the
app for the first time.
The pizza combos which included soft drinks were mostly visited
by men and seldom by women.
The prices and combos featured in the home screen were first to be
noticed by both women and men.
The large images of the featured specials were effective in
attracting visual attention, with many of the participants scrolling
through, looking at image first, and then price.
80
Free Navigation Pizza Pizza
PIZZA PIZZA

81. Eye Tracking Pizza Pizza
81
The eye-tracking tracking component used heat maps to identify the areas of visual focus.
The top performing phases of the user journey were the home page, pizza creation phase, and the checkout
phase.
• Average navigation time per stage: 27 seconds
• Average total navigation time: 2 minutes and 26 seconds
7.2s. 35.2s. 27.8s. 45s.20.8s.
OPEN APP CREATE PIZZA CHECKOUT
PIZZA PIZZA

82. In contrast to the other applications, the emotional engagement moved
consistently upwards, and peaked at the checkout phase remaining high
throughout the create account phase.
Selecting the size and toppings and creating the pizza elicited a lower
level of emotional engagement. However, once users began to select
and add toppings to their pizzas the emotional activation rose slightly.
Although attention drops slightly, it remains well above median average.
The overall attention scores are much higher when compared to the
other apps, with every step registering an attention score greater than
the median line of 0 in z-score normalization scheme.
This app maintains users’ attention at an elevated state throughout the
experience.
82
EEG Results Pizza Pizza
PIZZA PIZZA
EmotionalEngagementAttentionActivation

83. 83
Although emotional engagement was lower at app launch, the attention was
relatively high as the app was loading.
The participants stated that they preferred the selection phase, out of the five
identified phases. While we noted a slight increase in emotional engagement at
the selection phase, it was minute in comparison to the checkout phase.
Additionally, although users stated that checkout is the least interesting phase of
the user journey, the emotional and attentional engagement as recorded by the
EEG clearly suggested otherwise.
According to the post-study survey, 79% said they will definitely use the app
again soon.
Overall Observations Pizza Pizza
EEGScaleNumberofParticipants
User Journey
User Journey
PIZZA PIZZA
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
OPEN APP
CREATE
PIZZA
SIZE/
TOPPINGS
CHECKOUT
CREATE NEW
ACCOUNT
Q " #$%#& '$$(&$%#&
0
5
10
15
20
25
DISCOVERY
open & create
SELECTION
size & toppings
CHECKOUT
create new account
!"#$% & "'("#$%
79%
14%
4% 3%

84. BEST BUY
MOBILE APP

85. In the free navigation and first exposure to the app, loading time
was quick. The eye-tracking device showed that the first items
noticed were front banner, which showcased a laptop or TV
promotion, followed by the “What’s on Sale” banner.
Upon clicking on items, participants scanned the description
briefly and focused mainly on the photo and price.
The weekly ad was also amongst the most viewed banners, with
the majority of users browsing computers, TVs, iPods and
headphones in the app.
85
Free Navigation Best Buy
BEST BUY

86. Eye Tracking Best Buy
86
The eye-tracking component of the study used heat maps to identify the areas of visual focus.
The top performing phases for the Best Buy mobile app were the home screen, the camera
selection, and the first checkout screen.
• Average navigation time per stage: 30 seconds
• Average total navigation time: 2 minutes and 30 seconds
6.4s 36.4s 22.8s 10.4s 74s
OPEN APP SELECT CAMERA ADD TO CART/CHECKOUT
BEST BUY

87. According to the results, both the emotional and attentional
engagement decreased throughout the user journey.
The participants’ emotional peak was at the opening of app with a a
significant drop in attention when browsing cameras. Emotional
engagement dropped significantly into the negative, indicating
frustration during the selection of a camera. Furthermore, the
attentional activation when users reached the checkout stage also
declined drastically.
The EEG results found that the purchase journey doesn’t continually
engage the users’ attention, resulting in a progressive declining trend
throughout the user experience.
87
EEG Results - Best Buy
BEST BUY
0.1
0.2
0.3
0.4
-0.3
-0.2
-0.1
0.0
-0.4
-0.2
0.0
0.2
0.4
0.6
-0.8
-0.6
-0.10
0.3
0.2
-0.2
0.1
-0.1
OPEN APP
BROWSE
CAMERAS
SELECT
ADD TO
CART
CHECKOUT
EmotionalEngagementAttentionActivation

88. 88
According to the EEG results, both emotional and attentional engagement
fell dramatically over the course of the purchase journey, even though they
began on a positive and engaged high note.
The participants explicitly stated that the selection phase was what they
were most interested, out of the 5 identified phases of the purchase path.
However, it elicited the lowest emotional point.
The checkout step was the longest phase in terms of time; 74 seconds, and
it is also where attention saw the most significant drop, indicating boredom.
According to the post-study survey, 48% will probably use the app again in
the distant future.
Overall Observations - Best Buy
EEGScaleNumberofParticipants
User Journey
User Journey
BEST BUY
-1.0
-0.8
-0.6
-0.4
-0.2
0.2
0.4
0.0
0.6
OPEN APP
BROWSE
CAMERAS
SELECT
ADD TO
CART
CHECKOUT
0
5
10
15
20
DISCOVERY
open & browse
SELECTION
select & add to cart
CHECKOUT
Liked Disliked
Emotion Attention
48%
17%
11%
24%

89. HYATT
MOBILE APP

90. The first image of the father and son triggered prolonged
attentional activation.
The homepage was the most visually engaging screen, with focus
on Find Hotel, Reservations and Gold Passport tabs positioned in
the lower portion of the screen.
24% of all users used the map function to find the hotel, and all
looked at images first and then proceeded to check rates and
availability.
90
Free Navigation Hyatt
HYATT

91. Eye-Tracking Hyatt
91
The eye-tracking tracking component used heat maps to identify the areas of visual focus.
The top performing stages were the home page and the hotel selection.
• Average navigation time per stage: 43 seconds
• Average total navigation time: 3 minutes and 55 seconds
54s. 38s. 44.4s. 82.4s.43.2s.
OPEN APP SELECT HOTEL BOOK ROOM
HYATT

92. 92
The Hyatt app loaded quickly and the first image of father and
son triggered a high emotional engagement. While it elicited
the highest emotional activation point, a sharp decline
followed in attention activation for the rest of the phases.
Browsing for hotels significantly lowered the emotional
engagement and attentional activation of the users, indicating
either boredom or frustration. The downward trend continues
until the checkout phase, which becomes the lowest point.
According to the EEG results, both the emotional and
attentional engagement decreased throughout the user
journey.
EEG Results - Hyatt
HYATT
-0.2
-0.1
0.0
0.1
0.2
0.3
-0.4
-0.3
-0.3
-0.2
-0.1
0.0
0.1
0.2
-0.5
-0.4
-0.7
-0.6
OPEN APP
BROWSE
FIND HOTEL
SELECT
BOOK
ROOM
CHECKOUT
EmotionalEngagementAttentionActivation

93. 93
The implicit opinion as per the EEG results show both attention and emotional
activation trending downwards for the Hyatt app.
When participants were asked what their most preferred phase of the user
journey was, a strong majority chose the selection phase, which is in alignment
with the emotional and attentional spike elicited during that phase.
Both the Booking and checkout phases saw a drop in both emotion and
attention, as users attempted to navigate numerous options and lengthy
processes.
The greatest response to repeat use was the 38% who stated that they will never
use the app again, and 31% who will probably use it again in the distant future.
Overall Observations - Hyatt
EEGScale
User Journey
User Journey
NumberofParticipants
HYATT
Emotion Attention
0
5
10
15
20
DISCOVERY
open & browse
SELECTION
select & book room
CHECKOUT
! "#$"%&'("%&'
31%
14%
38%
17%
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
1.0
1.1
0.0
1.2
OPEN APP
BROWSE
FIND HOTEL
SELECT
BOOK
ROOM
CHECKOUT

94. AT A GLANCE

95. EYE TRACKING EEG REVIEWSURVEY
95
43s average navigation
time per stage.
3.33 mins average total
navigation time.
Most viewed (time &
visits): Homepage,
selecting hotel.
Low emotional scores for
Browse/Find hotel due to
overwhelming interface.
Attention fell throughout,
indicating increased
boredom and less
engagement.
Checkout step required
excessive user input,
causing drop in attention
and engagement.
Favorite: Selection
Least Favorite: Selection.
38% will never use
the app again.
30s average navigation
time per stage.
2.30mins average of total
navigation time.
Most viewed (time &
visits): home page,
selecting camera, first
checkout screen.
Most users excited to
shop for electronics.
Selection step was least
emotionally engaging,
with too many options
and unpleasant/
overwhelming interface.
Large drop in attention
(boredom) by the time
checkout was reached.
Favorite: Selection
Least Favorite: Checkout
48%will probably use
app again in distant
future.
V2.3.1
Last updated:
March 14,2013
1199 ratings, 3 stars
(all versions)
6 ratings, 3.5 stars
(current version)
27s average navigation
time per stage.
2.26mins average total
navigation time.
Most viewed (time &
visits): home page, create
pizza, checkout screen.
Absolute attention scores
were much higher overall
compared to the other
apps.
Selection step perceived
as ‘work’.
Checkout step most
preferred, due to built up
anticipation.
Favourite : Selection
Least Favorite: Checkout
79% will definitely use app
again.
V1.7
Last updated:
March 13, 2013
6651 ratings, 4.5 stars
(all versions)
68 ratings, 4.5 stars
(current verison)
V1.5
Last updated:
March 5, 2013
3 ratings, 3.5stars
(all versions)
N/A
(current version)

96. REFERENCES

97. References
1. Astolfi, L., Babilona, F., Bez, F., Cincotti, F., De Vico Fallani, F., Mattia, D., Toppi, J., Vecchiato, G., 2011, Spectral EEG frontal asymmetries
correlate with the experienced pleasantness of TV commercial advertisements, Medical & Biological Engineering & Computing, v. 49, p. 579-583
2. Ravaja, N., Somervuori, O., and Salminen, M., 2013, Predicting Purchase Decision: The Role of Hemispheric Asymmetry Over the Frontal
Cortex, Journal of Neuroscience, Psychology, and Economics, v. 6, p. 1-13
3. Velasco, M., Velasco, F., Machado, J., and Olvera, A., 1973, Effects of Novelty, Habituation, Attention and Distraction on the Amplitude of the
Various Components of the Somatic Evoked Responses, International Journal of Neuroscience, v. 5, p. 101-111
4. Liu, Y., Sourina, O., and Nguyen, M., K., 2011, Real-time EEG-based Emotion Recognition and its Applications, Transactions on Computational
Science XII, v. 6670, p. 256-277
5. Marosi, E., Rodriguez, H., Yanez, G., Bernal, J., Rodriguez, M., Fernandez, T., Silva, J., Reyes, A., Guerrero, V., 2008, Broad band spectral
measurements of EEG during emotional tasks, International Journal of Neuroscience, v. 108, p. 251-279
97
RESOURCES