Neuroscience and mobile app desing

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Information about Neuroscience and mobile app desing
Mobile

Published on May 30, 2014

Author: marketing4ecommerce

Source: slideshare.net

THE SCIENCE BEHIND MOBILE DESIGN

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

ABSTRACT

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

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

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

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

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

BACKGROUND

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

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

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

METHODOLOGY

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 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.

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 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

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

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

FINDINGS & INSIGHTS

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

1. TO BROWSE OR TO CHECKOUT

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

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 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 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 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

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

2. LIKE THE APP, LIKE THE BRAND

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

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 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 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

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

3. USE SCREEN REAL ESTATE WISELY

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

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

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

4. IMAGES ARE MORE THAN JUST PRETTY PICTURES

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

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 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 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 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"##$%P"##$ & '()%& * + , +$))

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

5. GET TO THE POINT!

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

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

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"##$%P"##$ & '()%& * + , +$))

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

6. KEEP THEM INTERESTED, OR LOSE THEM FOREVER

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

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 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%

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

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

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 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 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"#$%&'"(#) P*+,$%&'"(#)

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

CONCLUSION

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

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

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

APPENDIX: FULL REPORT DATA

SURVEY DATA

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

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

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

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<

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

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 !"#$%&'"(#) !*+,$%&'"(#) !"#$%&'"(#) !*+,$%&'"(#)

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

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

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

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

EEG & EYE-TRACKING DATA

PIZZA PIZZA MOBILE APP

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

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

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 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%

BEST BUY MOBILE APP

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

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

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 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%

HYATT MOBILE APP

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

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 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 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

AT A GLANCE

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)

REFERENCES

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

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