Analysis of innovative and interactive advertising formats for smart TV through eye-tracking methods

POLITECNICO DI MILANO

School of Industrial and Information Engineering

Master of Science in Management Engineering

ANALYSIS OF INNOVATIVE AND INTERACTIVE ADVERTISING

FORMATS FOR SMART TV THROUGH EYE-TRACKING METHODS

Supervisor:

Prof. Lucio Lamberti

Co-Supervisor: Marco Mandolfo

Candidate:

Alberto Poli

878639

Abstract

A statistical approach, based on the comparative tests and multiple linear regressions, validated the outputs obtained. The analyses used Net Dwell Time, Fixation Time, Fixation Count and Revisits to study visual attention and the effort made to understand the different areas; while, the Net Entry Time was used to define the immediacy of the different regions.

Findings allow to define some useful recommendations for the realization of future banners. First of all, some common tendencies revealed the presence of Areas Of Interests (AOI) more attractive than others. Bottom Banner, the area located at the bottom of the screen, reported a higher capacity to attract viewers' visual attention compared to the Skyscraper, the area positioned to the side of the screen.

Secondly, the L-Shape banner disposed from left to bottom engage the viewers quickly compared to the banner oriented from right to bottom. Thirdly, within the different banner, there are AOIs' common attitudes. Informative messages, promotional messages and call to action covered the role of the more appealing elements.

Multiple linear regressions have found out the variables that suggest the types of graphic and content improvements to be made. Several variables have been adopted depending on the area of interest considered. The macro areas have been defined by White Space, Number of Elements, Square Elements, Number of Images and Text Impact. While the individual elements, which characterize the advertising banners, have been defined by AOI size, Element Contrasts, Position, Number of Words and Square Words.

Finally, on the base of results, some recommendations were proposed to make the banners more attractive considering the needs of the promoting companies.

Abstract (Versione Italiana)

L’esperimento è stato condotto su un gruppo di cinquanta persone, le quali sono state sottoposte alla riproduzione di un programma di intrattenimento durante il quale sono apparse sei pubblicità di sei diversi brand. Tre delle aziende hanno proposto due diversi tipi di banner (Banner-A e Banner-B), uguali per messaggio promozionale ma diverse per contenuto, forma e disposizione; mentre le rimanenti tre aziende sono state visualizzate con un unico formato.

Per questa ragione il campione è stato diviso in sei sottogruppi, ognuno dei quali ha riprodotto lo stesso programma televisivo ma con formati di banner pubblicitari differenti.

Questa tesi ha cercato di capire se fosse possibile, attraverso l’utilizzo di tecnologie di eye-tracking, identificare dei comportamenti comuni tra gli spettatori per aumentare la loro attenzione visiva verso le pubblicità, rendendole più attrattive.

Lo studio si è basato su test statistici e modelli di regressione lineari multipla che hanno consentito di dare una validità statistica ai risultati.

Diverse metriche sono state utilizzate, il Net Dwell Time, le Revisits, il Fixation Time e il Fixation Count hanno permesso di ottenere informazioni relative all’attenzione visiva degli spettatori e allo sforzo richiesto per la comprensione dei contenuti delle regioni. Il Net Entry Time invece ha dato informazioni relative all’immediatezza delle aree di interesse studiate.

I risultati ottenuti hanno permesso di ottenere delle informazioni importanti al fine di realizzare futuri banner. In primis, sono state identificate delle Aree di Interesse più attrattive di altre; il Bottom Banner, posizionato nella regione inferiore dello schermo si è rivelato più interessante della regione laterale, chiamata Skyscraper.

In secondo luogo, i banner che occupano l’area sinistra e inferiore sono risultati più immediati rispetto a quelli disposti nel senso opposto (area laterale destra e inferiore).

Infine, i messaggi promozionali ed informativi e le Call to Action, aree che richiamano ad un’interazione tra cliente e portale online dell’azienda, sono risultati gli elementi più interessanti per gli utenti.

Sono state inoltre condotte delle regressioni lineari multiple con il fine di determinare come l’attenzione visiva dello spettatore potesse aumentare al variare delle caratteristiche del banner.

Per le macro-aree, quali L-Shape, Bottom Banner e Skyscraper, i predittori utilizzati sono White

Space, Number of Element, Square Elements, Number of Images e Text Impact. Mentre per gli elementi che compongono i banner sono stati utilizzati i predittori AOI size, Element Contrasts, Position, Number of Words e Square Words.

Grazie ai risultati ottenuti da queste analisi, la ricerca ha permesso di fornire suggerimenti utili per la realizzazione di futuri banner pubblicitari.

Table of Contents

2.6COGNITIVE AND EMOTIONAL MECHANISMS ... 27

2.6.1 EYES ... 28

2.6.2 BRAIN ... 29

2.7ADVERTISEMENT ... 31

2.7.1 Storyboard of Advertisement ... 31

2.7.2 Advertisement in XXI ... 34

2.7.3 Influential Factors to Visual Attention ... 36

2.7.4 Television advertisement ... 39

2.7.5 Internet advertisement ... 39

2.7.6 Smart Tv ... 42

3. METHODOLOGY ... 43

3.1EXPERIMENTAL SESSIONS AND SAMPLE ... 43

3.1.1 Experimental Procedure ... 44 3.1.2 Employed Metrics ... 45 3.1.3 Instrumentation Used ... 45 3.1.4 Research Procedure ... 46 3.1.5 Data Extraction ... 47 3.1.6 Data Transformation ... 47 3.1.7 Data Rearrangement ... 47 3.1.8 Subset Creation ... 48 3.2ANALYSIS ... 49 3.2.1 Comparisons ... 49

3.2.2 Multiple Linear Regressions ... 51

3.3BANNER DESCRIPTION ... 53 3.3.1 Airbnb ... 53 3.3.2 Flixbus ... 54 3.3.3 Technogym ... 55 3.3.4 Mediaset ... 56 3.3.5 Volkswagen ... 56 3.3.6 Lancome ... 57 4. ANALYSIS ... 58 4.1COMMON TENDENCY ... 59

4.1.1 Primary Content vs L-Shape ... 59

4.1.2 Bottom Banner vs Skyscraper ... 60

4.1.3 Brand compared with Common Tendency ... 61

4.2.1 Macro A/B Tests ... 64

4.2.2 Macro AOIs ... 68

4.3ANALYSES ON ELEMENTS ... 76

4.3.1 Elements’ Analysis Intra-banner ... 78

4.3.2 Elements’ A/B Testing ... 99

4.4MULTIPLE LINEAR REGRESSIONS ... 107

4.4.1 L-Shape ... 107

4.4.2 Skyscraper and Bottom Banner ... 112

4.4.3 L-Shape Elements ... 116

5. LIMITATION ... 123

6. CONCLUSIONS ... 124

6.1COMPARISONS ... 125

6.2MULTIPLE LINEAR REGRESSIONS ... 131

7. MANAGERIAL IMPLICATIONS ... 133

8. REFERENCES ... 136

List of Figures

Figure 1. Anatomy & Structure of the Eye _______________________________________________________________ 19 Figure 2. Brain parts; Kandel, Schwartz and Jessell 1991 _________________________________________________ 29 Figure 3. Airbnb Banner-A _____________________________________________________________________________ 141 Figure 4. Airbnb Banner-B ____________________________________________________________________________ 141 Figure 5. Flixbus Banner-A ____________________________________________________________________________ 142 Figure 6. Flixbus Banner-B ____________________________________________________________________________ 142 Figure 7. Technogym Banner-A _______________________________________________________________________ 143 Figure 8. Technogym Banner-B _______________________________________________________________________ 143 Figure 9. Mediaset Banner ____________________________________________________________________________ 144 Figure 10. Volkswagen Banner ________________________________________________________________________ 144 Figure 11. Lancome Banner ____________________________________________________________________________ 145

List of Tables

Table 1. Sample size represented by gender and generation _____________________________________________ 43 Table 2. Timeline of the banner visualized by the viewers ________________________________________________ 44 Table 3. Banners visualized for each Schema ____________________________________________________________ 46 Table 4. Identification of the Text Impact’s classes for the L-Shape ______________________________________ 51 Table 5. Identification of the Text Impact’s classes for Bottom Banner & Skyscraper ______________________ 52 Table 6. Comparison of general trends on Primary Content and L-Shape ________________________________ 59 Table 7. Comparison of general trends on Bottom Banner and Skyscraper ______________________________ 60 Table 8. Comparisons on Macro AOI between Airbnb banner observations and general observations ____ 61 Table 9. Comparisons on Macro AOI between Flixbus banner observations and general observations ____ 62 Table 10. Comparisons on Macro AOI between Technogym banner observations and general observations ________________________________________________________________________________________________________ 62 Table 11. Comparisons on Macro AOI between Mediaset banner observations and general observations __ 62 Table 12. Comparisons on Macro AOI between Volkswagen banner observations and general observations ________________________________________________________________________________________________________ 62 Table 13. Comparisons on Macro AOI between Lancome banner observations and general observations _ 62 Table 14. A/B Tests - Comparisons conducted on Primary Content, L-Shape, Bottom Banner and Skyscraper of different Airbnb banners. ____________________________________________________________________________ 64 Table 15. A/B Tests - Comparisons conducted on Primary Content, L-Shape, Bottom Banner and Skyscraper of different Flixbus banners. ____________________________________________________________________________ 65 Table 16. A/B Tests - Comparisons conducted on Primary Content, L-Shape, Bottom Banner and Skyscraper of different Technogym banners. _______________________________________________________________________ 66 Table 17. Comparisons between the Bottom Banner and L-Shape of the Airbnb Banner-A _______________ 68 Table 18. Comparisons between the Bottom Banner and L-Shape of the Airbnb Banner-B _______________ 68 Table 19. Comparisons between the Bottom Banner and L-Shape of the Flixbus Banner-A _______________ 70 Table 20. Comparisons between the Bottom Banner and L-Shape of the Flixbus Banner-B ______________ 70 Table 21. Comparisons between the Bottom Banner and L-Shape of the Technogym Banner-A __________ 72 Table 22. Comparisons between the Bottom Banner and L-Shape of the Technogym Banner-B _________ 72 Table 23. Comparisons between the Bottom Banner and L-Shape of the Mediaset Banner _______________ 73 Table 24. Comparisons between the Bottom Banner and L-Shape of the Volkswagen Banner ___________ 74 Table 25.Comparisons between the Bottom Banner and L-Shape of the Lancome Banner _______________ 74 Table 26. Comparisons Between Elements one and nine of Mediaset Banner ____________________________ 79

Table 27. Comparisons Between Elements two and eight of Mediaset Banner ___________________________ 79 Table 28. Comparisons Between Elements one and eight of Mediaset Banner ___________________________ 79 Table 29. Comparisons Between Elements three and nine of Volkswagen Banner _______________________ 80 Table 30. Comparisons Between Elements one, two, four, five, six and eight of Volkswagen Banner ______ 81 Table 31. Comparisons Between Elements three, nine and two of Volkswagen Banner ___________________ 81 Table 32. Comparisons Between Elements one and two of Lancome Banner ____________________________ 83 Table 33. Comparisons Between Elements three, nine and eight of Lancome Banner ____________________ 83 Table 34. Comparisons Between Elements one, two and eight of Lancome Banner ______________________ 83 Table 35. Comparisons Between Elements two and eight of Airbnb Banner-A ___________________________ 85 Table 36. Comparisons Between Elements three and nine of Airbnb Banner-A __________________________ 85 Table 37. Element one Airbnb Banner-A ________________________________________________________________ 85 Table 38. Comparisons Between Elements one, two and eight of Airbnb Banner-A ______________________ 85 Table 39. Comparisons Between Elements one, three and nine of Airbnb Banner-A _____________________ 86 Table 40. Comparisons Between Elements eight, three and nine of Airbnb Banner-A ____________________ 86 Table 41. Element two Airbnb Banner-B ________________________________________________________________ 87 Table 42. Comparisons Between Elements eight and nine of Airbnb Banner-B __________________________ 88 Table 43. Comparisons Between Elements two, eight and nine of Airbnb Banner-B _____________________ 88 Table 44. Comparisons Between Elements one and three of Airbnb Banner-B ___________________________ 88 Table 45. Comparisons Between Elements one, three and eight of Airbnb Banner-B ____________________ 88 Table 46. Element 4 Flixbus Banner-A __________________________________________________________________ 90 Table 47. Comparisons Between Elements one and nine of Flixbus Banner-A ___________________________ 90

Table 48. Comparisons Between Elements two, three, five, six and seven of Flixbus Banner-A _ 90 Table 49. Element eight Flixbus Banner-A ___________________________________________________ 90 Table 50. Comparisons Between Elements two, one and nine of Flixbus Banner-A _____________ 91 Table 51. Comparisons Between Elements four, one and nine of Flixbus Banner-A _____________ 91 Table 52. Comparisons Between Elements two, three, five, six, seven and eight of Flixbus Banner-A ____________________________________________________________________________________________ 91 Table 53. Comparisons Between Elements two, three, five, six, seven and four of Flixbus Banner-A ______________________________________________________________________________________________ 91 Table 54. Comparisons Between Elements four, eight and nine of Flixbus Banner-A ___________ 91 Table 55. Comparisons Between Elements one and four of Flixbus Banner-B _________________ 93

Table 56. Element nine Flixbus Banner-B ____________________________________________________ 93 Table 57. Comparisons Between Elements two, three and eight of Flixbus Banner-B _________ 93 Table 58. Comparisons Between Elements one, four and nine of Flixbus Banner-B ____________ 93 Table 59. Comparisons Between Elements two, three, eight and nine of Flixbus Banner-B ____ 93 Table 60. Comparisons Between Elements two, three, eight and one of Flixbus Banner-B ____ 94 Table 61. Element nine Technogym Banner-A ________________________________________________ 95 Table 62. Comparisons Between Elements one and eight of Technogym Banner-A ___________ 95 Table 63. Comparisons Between Elements one, eight and nine of Technogym Banner-A ______ 96 Table 64. Comparisons Between Elements one, eight and nine of Technogym Banner-B _____ 97 Table 65. Comparison of the elements one, two, three, eight and nine among the Airbnb Banners _____________________________________________________________________________________________ 99 Table 66. Comparison between Banner-A element two and Banner-B element nine for the Airbnb Brand ______________________________________________________________________________________ 100 Table 67. Comparison between Banner-A element nine and Banner-B element two for the Airbnb Brand ______________________________________________________________________________________ 100 Table 68. Comparison of the elements one, three, eight and nine among the Flixbus Banners 102 Table 69. Comparison between Banner-A element two and Banner-B element nine for the Flixbus Brand ______________________________________________________________________________________ 103 Table 70. Comparison between Banner-A element nine and Banner-B element four for the Flixbus Brand ______________________________________________________________________________ 104 Table 71. Comparison of the elements one, eight and nine among the Technogym Banners _ 105 Table 72. Multiple Linear Regressions for the L-shape AOIs __________________________________ 109 Table 73. Multiple Linear Regressions for the Bottom Banner AOIs ___________________________ 114 Table 74. Multiple Linear Regressions for the Skyscraper AOIs ________________________________ 114 Table 75. Multiple Linear Regressions for the Brands AOIs ____________________________________ 118 Table 76. Multiple Linear Regressions for the Call To Action AOIs _____________________________ 119 Table 77. Multiple Linear Regressions for the Elements AOIs _________________________________ 121

Executive Summary

In an increasingly connected world where people are always subjected to new stimuli, advertising has undergone radical changes. Not only the contents have changed but also the way in which they are transmitted. New communication channels have been born and with them new strategies, new methods and new tools have been developed.

With the advent of smart technologies, always connected to the network, advertising has integrated traditional advertising (such as billboards, TV commercials and newspaper advertisements) with what are called digital advertising. The advertisements spread on websites, applications, emails and social networks are constantly evolving and in 2018 the global expenses for this type of promotion reached 283.350 billion dollars.

This study focused on digital advertising, analyzing those temporary banners (15 seconds) that appear during the broadcast a television program on smart TV.

Smart TVs allow the viewer to interact with the network, for example it is possible to enter the official portal of the advertising promoter through a simple click.

In this study a group of fifty people was employed during the reproduction of a famous Italian reality show. During the reproduction of the program six pop-up advertising banners of six different brands were reproduced. These occupied the lateral area and the underlying area going to reduce the dimensions of the main content during the reproduction. Through an eye tracking device, the eye movements of the different users were monitored.

Literature Review

The first chapter dealt first with the history of eye tracking, trying to create a timeline of technological discoveries that allowed the birth and development of this field.

Subsequently, in the second chapter the technologies currently in use have been listed and described, highlighting the characteristics of each of them.

Then the applications and the various application fields of the technologies in use were studied and they have highlighted the utility and employment of these devices for monitoring eye movement. After that the study went in deep with the analysis of indicators commonly used, providing for each of them a description.

The chapter Cognitive and Emotional Mechanisms dealt with processes that characterize the movements of the human eye and neuronal signals during the acquisition of information from external

stimuli. It was therefore necessary to explain how these technologies can be used in order to give practical and applicable results in a managerial context.

The last section of literature dealt with advertising; first of all, analyzing its history and then focusing on advertising in the 21st century.

Successively, it was studied how the visual attention of the viewer could be attracted more effectively. Numerous studies about the habits and trends of users have been considered, including researches on banners, images and content displayed on the screen.

The experiment reported a big difference compared to the cases studied in the literature. This is due to the fact that the television program analyzed was reproduced on a smart-tv, while the studies reported in the literature review were focused on different type of communication medium, such as TV or web pages. Indeed, it is difficult to find out advertising researches based only on Smart TV. For this reason, the analyzed studies have taken into account both categories, advertising on TV and on the web.

Methodology

In the first section it was explained how the data used for the analyses were obtained through a previous experiment carried out in the PHEEL laboratory of the Politecnico di Milano.

The metrics employed identified and described the variables used to study the visual behavior of the viewers.

Instrumental Used described the devices adopted during the experimental phase, indicating those that were necessary for the purpose of the research.

The paragraphs Data Transformation, Data Rearrangement and Subset Creation explained the treatment of the data before the analysis phases.

Parametric and non-parametric tests have been implemented in order to verify differences and similarities between observations on the different AOIs. In this way the results were validated by the statistical value of the tests.

Multiple linear regressions, through predictors, were implemented to forecast the viewers’ behaviors, defined by dependent variables. These predictors were the independent variables of the regressions and they were chosen according to the type of AOI considered.

Analysis

This chapter contains all the analyses conducted during the research.

In the first section, comparisons were made at the macro level of the larger areas of the banner (Primary Content, L-Shape, Skyscraper and Bottom Banner) over the entire group of observations, except Technogym banner B which reported an opposite arrangement with respect to all other banners.

The trends of each individual banner were then compared with the average ones.

At a macro level, comparisons were made between different areas of the same banner and between banners of the same brand (A / B Tests).

Finally, comparative analyses were carried out between elements within the same banner and between similar elements of different banners (A / B Tests).

The last section of the analysis reported the results of multiple linear regressions conducted on L-Shape, Skyscraper, Bottom Banner and on three different classes of AOIs: Elements, Call to Action and Brands.

Conclusions

The final phase reported a summary of the results obtained, identifying common trends and the dissimilar ones that could give a clearer reading of the advertising banners effectiveness.

Managerial Implication

Finally, the results obtained were used to provide suggestions to banner creators. The intent is to apply the recommendations coming from this research in order to be more effective and to attract advertisements for promotional purposes.

1. Introduction

The advent of the internet has revolutionized not only the way people interact but also the deeper aspects of society. A report1 _{of “We are social”, reported a population of Internet users of 4.388}

million, about 57% of the world population.

In an increasingly connected world, internet and advanced technologies have enabled the development of smart devices. People can always be connected to the network and often do it with more than one device at the same time. Smartphones, computers, tablets and cars are some of the examples of devices that are always connected.

In this context, smart TVs are born. There are several types the specific term refers to TV able to connect to the network in such a way as to make the user enjoy different services from streaming reproduction to the use of interactive applications. Of these devices, there are models already with integrated software and hardware technology, and devices to which it is possible to add externally the tools that allow them to be connected.

Smart TVs are also sometimes referred to as downloadable applications on smartphones and laptops to display streaming content.

We will focus our attention on the first two categories. In 2018 the size of the Smart TV market reached $157 billion with an expected CAGR of around 10% in the period 2019-2024 and an expected market value of $278 billion in 2024.2

Internet and its communication channels have outperformed traditional media such as radio and TVs. Advertising has also undergone a radical change. New approaches, based on internet advertising, have been integrated with traditional methods, such as billboards, newspaper advertisements, TV commercials and commercials.

Smart TVs are part of the new communication methods and adopt a type of advertising based on information generated, shared and received by the Internet, similar to advertising on websites. In this way it is possible to offer personalized content based on user targeting and smart devices allow a more dynamic and interactive type of advertising, directly reaching the companies' direct communication channels.

1_{https://wearesocial.com/blog/2019/01/digital-2019-global-internet-use-accelerates}

https://www.prnewswire.com/news-releases/smart-tv-market-value-is-further-expected-to-reach-us-278-billion-by-In 2018 investments in digital advertising amounted to 283.35 billion dollars, with an expected increase for 2019 of 17.6%, thus reaching 333.25 billion dollars.3

In this context, characterized by new habits and trends, the thesis conducts exploratory research on the pop-up banner ads broadcast on smart-TVs while playing entertainment programs.

The goal is to determine if any recommendations can be made to develop more attractive future advertisements and therefore make them more effective for the commercial purposes of the sponsoring company. This type of analysis will be carried out on advertising banners that appear during the reproduction of a famous Italian reality show.

The question that arises this research is whether it is possible, through a study of eye movements, to identify common tendencies on the visual attention of the viewer in such a way as to determine which features can have an impact on the banner's level of attraction and improve them.

The return of significant results to the research question would allow to identify some useful insights and propose recommendations for the creation of advertising banners. It would, therefore, be possible to identify the managerial implications of the analyzes carried out and transform this study into a practical application of the outputs obtained.

This research has the originality of focusing the analysis on apparel advertising banners displayed on smart-tv. In the literature, still, no study has been carried out on this topic in an integrated manner. Size, positions, colors and the same areas of advertising have been studied separately, without having an idea of how these factors worked together as a whole.

2. Literature Review

Eye tracking is a method that has evolved over the years and through the development of new technologies. Today different types of devices are used and there are many fields of application. Through these tools it is possible to study how people interact with the environment and how they react to stimuli. Several metrics have been introduced, each with its own characteristics and purpose. The neuromarketing studies through these and other technologies the deepest signals of the human being and tries to make them applicable in more commercial and promotional environments.

From this context it is clear that advertising has undergone a radical change not only for the contents but also for the types of communication channels introduced over the last decade; thanks also to the advent of the internet.

Today, online advertising on web pages and smart devices is becoming more widespread and companies are aiming to increase user engagement more and more by improving the effectiveness of their promotional messages.

In this context, numerous studies have been carried out on the level of attraction of TV and web page advertisements, trying to analyze some common patterns among viewers.

2.1 Eye Tracking

Eye tracking is the process through which information about gaze movements are gathered to be analyzed in the meanwhile a user is performing some activities or tasks. Origins of this technique date back to 1879 when the ophthalmologist Louis Émile Javal noticed, for the first time, that readers’ eyes do not skim fluently through the text while reading. Javal recognized that quick movements (saccades) are mixed with short pauses (fixations) and he coined the term “saccades”, a French word that identify a rapid movement of a horse during dressage. (Wade, 2010)

In 1908 Edmund Huey developed the first eye tracking device, which was intrusive and invasive, it was composed by a contact lens attached to a pointer which change with the movement of the eyes. In 1920 a two-dimensional device allows the recording of horizontal movements on one eye and the vertical movements on the other eye.

In 1930 Miles Tinker applied the photographic techniques to the eye tracking study on reading movements. Typeface, print size, page layout, amongst others were varied to determine their effects on reading speed and eye movement patterns. (Webster & Tinker, 1935).

Between 1935 and 1937 the methodology advancement and the application of Guy Thomas Buswell technique allowed the first eye movement recording. It used light beams which were reflected on reader’s eyes and recorded them on film (monocularly reflected beam could, for instance, be split to measure and re-combine its horizontal and vertical components as a fixation dot recorded on a film reel.)4_.

In 1939 Jung developed an electro-oculography (EOG) method through which was possible to measure both horizontal and vertical directions simultaneously.

In 1948 Hartridge and Thompson realized the first head-mounted eye tracker. This advancement was the first step to try to fix the limitation of the head movement.

In the years ahead, many improvements were made on camera-based methods, eye features tracked, and the light intensity.

Between 1970 and 1980, eye tracking technologies rapidly improved, the equipment became less intrusive and more effective due to the technology enhancement. One of the main results was the application of the eye tracking data and information to analyze and understand Cognitive process. In 1990s some companies used eye tracking methodologies to study the interactions and reactions of users to internet contents. The object was to get more insights about the user experience to empower

the page effectiveness, to increase the consistency of the contents and to grow up the potential of the online products and services market.

From 2000 till today the eye tracking methodologies and technologies are still improving and also its application spread among different fields such as Psychology and Neuroscience, Healthcare and Clinical research, Education, User Experience and Interaction, Professional Performances and Marketing and Customer Research.

2.2 Eye Structure

The human eye is formed by an external protective layer called sclera; it is a fibrous tissue composed by connective tissues that allow the connection of extraocular muscle for the eye movement. It covers all the eye.

The cornea is the outer layer which occupy the center of the external part and it lets the light to come in and to bends the rays. The iris is appointed to regulate how much light is let into the eye.

Behind the iris, the lens changes its shape to bring the image of an object to a sharp focus in the retina, a layer positioned in the back of the eye which contains photosensitive cells. The retina contains a small region called fovea composed by color sensitive cells that allow the perception of the scene’s fine details.

Figure 1. Anatomy & Structure of the Eye - http://data.allenai.org/tqa/vision_and_the_eye_L_1063/

Other two factor to consider are the optical axis also called Line of Gaze (LoG) and the Line of Sight (LoS) that is the line from the fovea to the center of the pupil which determine the visual attention. (Morimoto et al., 2005).

2.3 Technologies

Nowadays there are a wide range of eye trackers which differ for technology adopted, structure of the equipment and performances. Two macro categories grouped the different devices: Tradition eye tracker and Remote eye gaze system.

Traditional eye tracker: They are typically defined as intrusive devices. There is some invasive

equipment to be fixed on the head of the user.

Remote eye gaze system: Also known as Non-intrusive devices, composed by a set of camera and

sensors and able to detect the gaze movement without wearable tools. (Morimoto et al., 2005).

Looking at these two groups it is possible to go in depth with the classification and determine four methods to track the motion of the eyes:

Electro-Oculography: It is based on sensors applied around the skin of the eyes; they measure an

electric field during the eye rotation. Recording small potential variation, it’s possible to track and memorize the horizontal and vertical movements. The main advantage is the possibility to detect movement also when eyes are close. It is cheap, easy to use and precise for movement detecting. Despite these advantages it is invasive and hard to be wear for a long time.

Scleral Search Coils: Small coils of wire, embedded in special contact lens, that move into a

magnetic field. This field induce a voltage in the coil through which it is possible to detect the eye movement. Another technique is detecting the orientation in a magnetic field. The main problem is the invasive technologies which require the application of contact lens. On the other hand, this method has a great accuracy and a nearly unlimited resolution in time.

Infrared Oculography: An infrared light radiates eye which is reflected by the sclera. The intensity

of reflected infrared light carries out the information about the eye position. It is an invasive method allowed by the employment of spherical glasses. The Infrared Oculography is less vulnerable to noise than electro-oculography but it is more sensitive to the external light conditions. It allows the eye tracking also in darkness conditions.

Video Oculography: The fast growth of eye tracking methodology has spread out the technology’s

application beyond the laboratory research boundaries. Video-based trackers are the most used devices and they can be distinguished on the basis of the technical features. They can be both intrusive or non-intrusive and they can adopt single camera or multiple camera systems. Furthermore, the type of light used to detect the movement identify the typology of tool.

The “Video based remote eye trackers” capture the image of the eye through a camera; this image will change when an eye rotation or translation in 3D space occurred.

Remote Video Oculography system can be distinguish in Single-Camera or Multi-Camera technology. (Chennamma & Yuan, 2013).

2.3.1 Single-camera system

In the last years several single camera remote devices have been realized for academic or commercial application. Some practical and theoretical academicals research have been conducted. (Guestrin et al., 2006), (Hennessey et al. 2006), (Bohme et al. 2006).

Furthermore, Ohno developed an innovative system based on single camera, two points of light emission, the result is a more suitable device for a daily usage with a lower calibration effort needed. (Ohno et al., 2002).

Tomono realized a gaze tracker with a single camera system, two light sources and three CCDs devices (a technology to move an electrical charge from a device to an area in which the charge can be manipulated and converted) to allow a real time imaging acquisition. (Tomono et al., 1990). The technology cited is an ordinary resolution camera system supported by four infrared light sources. The result is a real-time intelligent control scheme based on a non-intrusive tool. (Yang et al., 2010).

2.3.2 Multi-camera system

There are several reasons to develop multi-camera systems, they allow to increase head motion and to improve the high-resolution image gathering in order to provide more reliable and precise gaze estimations. Across the years many systems have been developed: Zhu presented a double camera system made up of two cameras applied under the screen and an IR illuminator source to produce a glint in the eye image (pupil). A glint vector can be detected, and the two calibrated cameras allow to obtain a stereo vision system which provide a 3D pupil center coordination. (Zhu et al., 2006). Baymer and Flickner realized a four-camera system, two narrow field cameras for head motion and two wide angle systems to obtain a stereo vision. (Beymer & Flickner, 2003).

Ke Zhang simplified 3D eye tracking technology adopting two stereo cameras and two-point light sources system. (Zhang et al., 2010). Hung and Yin developed a two-camera system through which is possible to detect the face using a wide-angle camera that estimates the eye region. A second direct pan-tilt-zoom camera gather information focusing on the eye region. (Yoo & Chung, 2005), (Chennamma & Yuan, 2013).

2.4 Application

Eye gaze tracking applications can be grouped into two categories: diagnostic and interactive

Diagnostic Application: “the eye tracker provides objective and quantitative evidence of the user’s

visual and overt attentional processes. In this capacity, eye movements are generally recorded to ascertain the user’s attentional patterns over a given stimulus. The eye tracker is used to record eye movements for post-trial, off-line assessment of the viewer’s gaze during the experiment”. (Duchowski, 2002).

Some studies, such as the “Identification of Real-Time Diagnostic Measures of Visual Distraction with an Automatic Eye-Tracking System”, demonstrated how the correlation between performance variables and several eye glance measures proves the possibility to use some glance measures as diagnostics of visual distraction in a real-time adaptive automation system. (Zhang et al., 2006).

Interactive Application: “These systems must respond to or interact with the user on the basis of

observed eye movements. There are two different subgroups of interactive systems: selective and gaze-contingent. Selective systems use the point of gaze analogously to a pointing device (such as the mouse), whereas gaze-contingent systems exploit knowledge of the user’s gaze to facilitate the rapid rendering of complex displays”. (Duchowski, 2002).

2.4.1 Application Fields

Initially developed to gather information about reading patterns, text & picture comprehension and problem solving, the eye tracking mythologies have extended their utility going in depth with the study of multimedia learning and visual attention thanks to the integration of cognitive and psychological studies.

The Remote Eye Gaze Tracking systems are employed in different application fields. They are broadly involved in academic and scientific research; the intent is to study cognitive models based on the psychology and neuroscience to obtain practical applications.

Market research have been improved through the implementation of these technology. A wide range

of information about customers’ (or users’) behaviors can be gather and exploited for marketing and business activities. Some example could be the realization of interactive environment, e.g. grocery shop, in which a structured system is able to track the customers interest during the grocery shopping. There are different types of devices that allow this kind of research: glasses, cameras. Through this application it is possible to take data about the type of customer, his or her preferences, which are the main interest factors, how is the shopping path, if there is a common pattern among different experience in time or among different customers. The results allow the company to find solutions in order to improve the experience of the customers and rising the effectiveness of the shop. E.g. the arrangement of the products on the shelf, the position of promotion products. (Morin, 2011).

Usability Research are conducted to track the user experience and usability level of some current

services. The most common application is the web site testing; the aim is to analyze the user experience and to assess the usability. Through this activity the owner or a company find out indicators that allow the evaluation of the platform performances, highlighting the strengths and the weaknesses. E.g. typical user path point of major interest, area of higher interest. (Schiessl, 2003).

Medical Research, Biometric sensors and eye tracking systems allow to diagnose diseases such as

Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Obsessive Compulsive Disorder (OCD), Schizophrenia, Parkinson’s and Alzheimer’s disease.

Some studies used Eye gaze tracking systems to analyze the strategy adopted by individuals affected by high-functioning autism during the processing of social information. The results highlight how individuals with autism look at social stimuli differently; some researches show that they tend to fixate the mouth and typically avoid the eye region. The eye trackers allow the analysis of fixation

path to evaluate the information which are available to the brain. Other potential use in behavioral and neuroimaging fields can be done, it can be used to investigate the mechanisms underlying abnormal brain activity, and reduced task performance (Corden et al., 2007) in individuals with autism. (Boraston & Blakemore, 2007).

Psychologic Research, A wide number of applications are carried out to analyze human processing

of visual information under different fields. Neuroscience, experimental psychology, computer science and human factors are just some of the disciplines in which Eye tracking systems have positive impacts.

Eye movements are defined by the interaction between cognitive and perceptual processes, these powerful tools allowed to acquire knowledge about psychological processes such as language processing, image processing, auditory processing, memory, social cognition and decision-making in an unobtrusive and accurate way. (Mele & Federici, 2012).

Neuromarketing

The term is the result of the merger of two different words Neuro and Marketing and, how suggested by the name, it is referred to the application of neuroscience to the marketing. It is an innovative marketing approach, in which the customer behaviors are analyzed from a brain perspective with a deeper attention to cognitive and emotional response.

The first academical neuromarketing research was carried out by Read Montague, Professor of Neuroscience at Baylor College of Medicine in 2003 and published in Neuron in 2004.

From 2002 till today this trend is growing and the number of studies and research has increased. Despite it is still in a seed stage, it is clearly understood and accepted that the usefulness of brain-based tools (such as eye tracking, EEG, or fMRI) can help to better achieve a clear comprehension of market insights. (Morin, 2011).

2.5 Indicators

Eye tracking systems allow to gather a wide range of information about cognitive user response to visual stimuli. The advancement of this technology requires to be updated also with the metrics, which are used to assess the usability issues and results.

Eye movements patterns and eye scan observations highlight objective behavioral data that are not measurable through a verbal protocols or tests.

Eye-tracking metrics might be applied to different aspects of oculomotor behavior, depending on the type of analysis. The two main categories are: Fixation-based metrics and Saccade-based metrics. (Borys & Plechawska-Wójcik, 2017).

2.5.1 Fixation-based metrics

Generally, it seems to have not a tight relation between fixation duration and cognitive effort because of the different natures of the user tasks and utilities. Indeed, they affect the intensity of the cognitive process. Nevertheless, according to Rayner and Findlay & Kapoula studies, the duration of fixations in scanning is directly influenced by the cognitive load imposed by the scanned item. (Rayner, 1998), (Findlay & Kapoula, 1992). A fixation is defined as a relatively eye gaze motionless lasted 200-300 milliseconds. In this period the visual attention is oriented to a specific Area or region of interest (AOI).

AOI refers to Area of Interest and it indicates the specific target region gazed by the user.

The assessment of fixation, a human natural activity, allows to detect some of the most used metrics (Moacdieh & Sarter, 2012), (Pan et al., 2004):

Mean fixation duration (Rayner, 1998), frequently used as an indication of information complexity

and task difficulty. The fixation duration is a term to define the complexity and difficulty of visual display.

Total Fixation number (Beck, 2010), related to the attraction of the user attention to some additional

information.

Number of fixations in target AOI (Goldberg & Kotval, 1999), It defines the number of times in

which a user looks toward a specific Area of Interest. There are different types of meaning associated with this measure and these depend on the type of analysis. Frequent transitions from one region of a display to another indicates inefficient scanning with extensive search.

The fixation frequency in an Area of Interests (AOIs) defins as an important value that highlight how the eyes are attracted to the region with more information because of its distinctive and informative contents (Rayner 1998).

Gazing time (Nakayama et al., 2002) it is defined as the rate of gazing across the total observation

period, which is negatively linked to the task difficulty. It is also calculated as the percent of time that a subject spends on fixations instead of saccades (Pan et al., 2004)

Mean gaze duration in target AOI (Rayner, 1998) is the average gaze duration within that target

region. It may be longer if the user has difficulty to extract information.

2.5.2 Saccades-based metric

Saccades are continuously micro-movements of the eyes, with a velocity of 500 degrees or more, to direct the individual's visual attention toward a target. Eye

fixation process is characterized by three different steps: encoding of a visual stimulus, sampling of the peripheral field, and planning for the next saccade. (Borys & Plechawska-Wójcik, 2017), (Moacdieh & Sarter, 2012), (Pan et al., 2004).

Saccade rate, the number of saccades per second, defines the difficulty level or mental load. (Lee,

Bahn, Kim & Yun, 2010). Higher is the is the mental effort required lower will be this metric. (Nakayama et al., 2002), (Pan et al., 2004).

Saccade Amplitude, the longer are the eye movements (with larger saccade amplitudes), the larger

will be the un-fixated areas of the image. In crowding conditions, the average saccade amplitude decrease, and this is related with the reduction of area inspected during fixation. (Vlaskamp & Hooge 2006)

Scanpath length, Scanpath is defined as a sequence of saccade-fixation-saccade on a display. The

object is tracking the sequence during the user’s gazing. According to (Josephson and Holmes 2002) a scanpath is defined as a sequence of Areas of Interest (AOIs) and they used a string-editing method to calculate the differences between any two scanpaths. The total length, in pixels, is calculated from the first to the last fixation (Lee, Bahn, Kim & Yun, 2010). A shorter scanpath may indicate more efficient search and it allows to evaluate the interface effectiveness (Goldberg & Kotval, 1999).

2.6 Cognitive and Emotional mechanisms

The study of cognitive psychology has had a strong increase over the last decades. The term, coined in 1967 by the psychologist Ulric Neisesr, indicates a series of researches and theorizations related to the study of mental processes. They are based on the principle that the mind is an "information processing" system capable of constructing and executing finalized action programs. This branch of psychology has as its objective the analysis of those mental processes through which information is acquired, processed and stored. The theory of this science does not coincide with the year in which the name was coined. Numerous studies, of which Ulric had the merit of collecting and arranging, had a history prior to that date. In the last decades there has been an explosion of scientific and psychological studies, allowed, above all, by continuous technological development. Among the various tools used, researchers and experts have also relied on eye tracking systems but there have been numerous cases of combined use of other human body monitoring technologies. Among these technologies there is the use of systems for medical diagnosis, including EEG and ECG.

2.6.1 EYES

The eye is the organ of the visual system responsible for acquiring information on the external environment. It is a complex optical system composed of a set of functional parts for the acquisition process. The diaphragm, also known as the iris, is set up for the gathering of light and the regulation of its intensity. Focusing occurs through a group of adjustable lenses to form an image. The image is then translated into a series of electrical signals and transmitted to the brain through complex neural pathways. The optic nerve deals with the connection between the eye and the brain, including the visual cortex.

Emotions

A wide number of studies have been carried out on the visual system, among these, Onorati et al. (2013) pointed out that the dynamics of pupillarity is linked to affective states. Thanks to studies carried out on the Automatic Nervous System (ANS) he shown that there is a correlation between emotional states and visual images.

The peripheral nervous system is primarily concerned with innervating the smooth muscles of all the organs, heart and glands. It mediates the neuronal regulation of the internal environment and maintains a correct balance; a process in general not under direct voluntary control.

The existence of specific patterns of peripheral activity as performed by emotional stimuli has been demonstrated.

The relation between ANS and emotional events is still a subject of research, but it is clear how ANS and cognitive processing are linked.

“One of the most recent related ANS introduced in scientific literature is Pupil Dilation (PD). The pupillary response, whose neural pathways are mediated by the ANS, is determined by the activity of two smooth iris muscles: PNS innervates the sphincter pupil and controls the pupil constriction, whereas SNS causes the excitation of the dilator pupil. Different pupillary responses were observed with respect to different cognitive stimuli.”

The mentioned studies report a change in pupillary dilation in the presence of affective processes. According to Onorati et al. (2013), the Pupillarity Dilatation indices variation have confirmed the possibility to detect a correlated variation between a baseline state and the emotional events. It supports the theory through which autonomous direct control on the PD reflects the ANS response to emotional trigger events.

2.6.2 BRAIN

“Neuroscientists have, in modern times, been especially concerned with the neural basis of cognitive processes such as perception and memory. They have for the most part ignored the brain’s role in emotion.”

LeDoux

Brain analysis for memorization and elaboration of emotional events.

Figure 2. Brain parts; Kandel, Schwartz and Jessell 1991

Cognitive behaviors and action planning are managed by the "upper frontal lobes" also known as "prefrontal association cortex". The lower parts "limbic association cortex", cingulate gyrus and hippocampus deal with the emotional and memory activities.

The amygdala and the hippocampus manage the initial registration, the processing of emotional experiences and the pathways to and from long-term memory. Recent research has found out how different parts in the posterior righthand side are involved during the emotionally salient stimuli. These stimuli and their memorization depend on a distributed system composed of key critical areas close to the anterior and posterior ends of Cingulate.

Prefrontal cortex, located in the anterior cerebral cortex, groups different parties which are involved in different cognitive and emotional processes. It is composed by dorsal and lateral areas (Walker areas 9, 46, and 9/46), ventrolateral areas (47/12 and 45), medial areas (32 and 24) and orbitofrontal areas (10, 11, 13, 14, and 47/12).

Prefrontal Cortex neurons could codify a wide variety of variables in a complex structure, reflecting the difficulties to determine possible behavioral and cognition outputs.

The prefrontal cortex receives different inputs related to external and internal variables, concerning both cognitive and emotional stimuli. For this reason, cognitive processes influence emotional ones and vice versa.

“The amygdala is a structurally and functionally heterogeneous collection of nuclei lying in the anterior medial portion of each temporal lobe. Sensory information enters the amygdala from advanced levels of visual, auditory, and somatosensory cortices, from the olfactory system, and from polysensory brain areas such as the perirhinal cortex and the para-hippocampal gyrus “

(Salzman, 2010)

The amygdala is strictly linked to the Prefrontal Cortex, in particular with the posterior orbitofrontal cortex (OFC), and the anterior cingulate cortex (ACC). The recipients of the amygdala outputs could be: Prefrontal Cortex, the striatum, sensory, the hippocampus, the perirhinal cortex, the entorhinal cortex, and the basal forebrain, and to subcortical structures responsible. The subcortical structures are involved for physiological activities, for example emotional evaluation, autonomic responses, hormonal responses, and startle.

According to Phelps & LeDoux (2005), the amygdala impacts on the emotional processes due to its interconnections with the prefrontal cortex.

The traditional path that allows the brain to process stimuli, also called the “high road”, gather information from the environment (e.g. visual stimuli). It starts from the retina, pass through the thalamus and then through the primary visual cortex up to the dorsal and ventral streams of cortical visual processing. In the temporal lobe the information is elaborated and transmitted to the amygdala for the emotional activation.

During the recent years, many studies have been carried out about the role of the human amygdala. They found out that, in some conditions, the cortical processing is not mandatory to activate the amygdala.

Indeed, LeDoux pointed out how, under fear conditions the amygdala activities are stronger correlated with other subcortical activities, thalamic and collicular. This result reinforces the importance of thalamao-amygdala pathway in the human brain, a “low road” counterpoised to the “high road”. (Öhman, 2005).

2.7 Advertisement

Today, people are subjected to a high number of stimuli, ten times greater than they were ten years ago. The brain reacts to these stimuli in just a few seconds: before we can express ourselves verbally, the thoughts and opinions that influence our buying behavior have already been worked out in our unconscious.

In this context neuroscience finds its application in neuromarketing. Advertising has adapted to current trends and new communication channels; the way to inform and reach potential customers has changed and the same promotional messages have changed their form.

Engagement has become an important driver in order to evaluate the effectiveness of an advertising campaign and the study of emotions and reactions to stimuli has enabled them to improve.

But what is engagement? it seems that man has always tried to promote and convince others. The same advertisements developed over the years, without scientific tools to analyze the real effects on the individual, aimed to attract the attention of potential customers.

2.7.1 Storyboard of Advertisement

Advertising is a communication tool through which a company presents and promotes its products, its services, or its culture. Across the last two centuries, the communication channels speed up a bit, and advertising has changed with them. It is tough to trace back to the origins of modern advertising. Back in 1600, it has been possible to find out some forms of newspaper advertisements in England. Around 1800 this form of advertisement allowed the newspapers to reach a broader mass of people. In 1836 the Paris newspapers La Presse and Le Siècle adopted innovative strategies based on paid advertising and the increasing of audience loyalty. The results were the halving of the price and the spreading out of the number of copies sold.

In 1840 Volney B. Palmer established the first advertising agency, he bought newspapers' spaces at a lower price, due to quantity discounts, to resold them to the companies.

Up to the end of the 19th, the companies prepared the contents and the design of their advertisement. In the 90th, advertising agencies started to deal with the realization of the entire campaign, providing

Cross the 90th new devices have changed the communication, and even if the newspapers have adopted and integrated other channels to reach the customers, the strategy at the base is still the same. The primary source of income is the paid advertisement, which allows the low prices.

In 1914 the United States government established the Federal Trade Commission to prevent and protect companies and businesses by the illegal behavior of some actors.

During World War I, the advertisement was involved in arousing the public regarding war-related issues and in persuading the mass.

Around 1920, the radio, previously established as a communication device, became a means of mass communication, creating a community of people located thousands of miles away. Soon, the advertisement changed, adapting to the radio. In 1922 the first radio program sponsored by "Everyday" showed the potential of radio advertising.

World War II introduced the War Advertising Council; the aim was to recruit civil help and raise the consensus to mobilize the nation for war through propaganda.

In the 1950s, several US television networks began to rely on selling advertising space to different sponsors. A common practice was the submission of an agreement with a single sponsor; the consequence was the rise of the sponsor's control over the contents and the shows' direction.

In 1960 the companies began to invest in advertisements across different channels (television, radio, magazine ads, billboards, promotional events) to reach a larger group of customers. The agencies increase their focus on the development of efficiency campaigns. They improved messages, meaning, and symbols. The object was to trigger mental associations to enhance the memorization of the brands and their products or services.

From the last decades of 20th, the advertising campaigns have assumed an even more critical role within a company strategy. The latest trends have been the development a new specific Business Units, the Marketing function was introduced. It has gradually increased its relevance to the business dynamics. It has facilitated the companies to reach outstanding results in terms of sales and communication.

From 1980, more and more companies have adopted an internationalization strategy; the aim was to reach customers in different markets, raising the profits and overcome competitors. The result was the diversification of the company's portfolio and the consequent reduction of risks. In this context,

some of the most significant worldwide companies have achieved a broad mass through the adoption of intensive marketing campaigns.

The 1990s were the years of internet advent. It represented the future, the channel whereby people of different cultures and coming from different regions would have been in contact with no constraints of Time and Space.

The diffusion among different people and countries took advertisement agencies and companies to jump all over this new opportunity. E-commerce has finally destroyed the geographic limitation of the market, establishing markets for niche products. It has grabbed new customers, getting a direct control on the final market.

The internet has represented the medium that mostly affected the changing of advertisement strategies. The need to reach and suit a wider audience, spreading out different types of messages, has brought the companies to switch toward an ever more personalized advertisement.

The advancements of the last three decades allow the gathering and collection of billions of data. Big Data, Servitization, Digitalization, and Cloud computing are some of the megatrends which characterize today's world.

The introduction of new technologies and the employment of sensors and portable devices permits to collect information about the users. Today it is possible to get data from different sources such as vehicles, computers, watches, houses, wearable devices, smartphones. More information means more know-how about current and potential customers with a consequent opportunity to realize precise and efficient communication campaigns towards potential customers. New mediums and megatrends set new standards: more and more customize and personalize product/service, more segmented markets, and the companies' adoption of multichannel strategies.

2.7.2 Advertisement in XXI

As previously introduced, today, the advertisement plays a fundamental role within a company; it is at the base of the success or failure of a business. The massive investments aim to define the best strategies to outperform competitors and attempt to reach the customers.

There are different types of advertisement and communication messages that a company may wish to convey. They could reach multiple audiences (clients, distributors, shareholders, suppliers, public institutions and authorities, employees, stakeholders), and they could have different types of objectives: Institutional communication, Commercial communication, Internal communication. The studies have been carried out to determines: the best practices to increase the efficiency of the messages (as marketing ROI), the more efficient methodologies to gather information about the market, the tactics to better achieve the customer's needs improving the communication and arising the willingness to buy. At the base of this researches, there is a wide range of disciplines.

In the last 20 years, the advent of Web and Smartphone advertisement, the adoption of new systems like smart-tv and streaming applications, and the ever more connected world due to the introduction of social media and (real-time) interactive devices lead to a rapid change of the marketing strategies. The main object of the online-interactive adv is to enhance the company's effectiveness to get more value.

Advertising value was usually measured as the effects of its message on the recipient but new form of marketing on the basis of the latest technology as internet, implied new and difficult challenges concerning the measurement of its value.

Today advertising value is a measure used to evaluate advertising effectiveness. Generally, it is defined as the ability of a banner to catch the attention of the users and turn it into interactive activities. For example, an attractive banner able to convince the user to click on the link and then keep him/her to surf in the company’s website.

“Advertising value may be influenced by and influence both media and media vehicle context. For advertisers, this implies that by carefully selecting media that fit the communication task at hand and media vehicles that accurately target the most interested potential customers, they can enhance the value of their advertising”.

The advent of internet allows to deliver advertisements more and more targeted and personalized to the customers.

Kimefeld & Watt‘s (2001) study compare promotional campaign in print and Web portals. They found out a tendency of Web advertisements to improve attitude toward the ad and in purchase intention than print ads.

The value and consequently, the KPIs choose to track the performances depend on the company's targets, typology, and strategy. E.g., if the goal is to increase the fame of the brand or products, more visitors are needed, and the KPIs employed could be new visitors, brand awareness or brand/direct visits; If the target is to increase the sales that means more customers or higher-order value. The KPIs involved could be the Average Order Value, Revenue per visit or Click-through rate.

According to L. Ha (2008) there are a wide literature about the effectiveness of online advertising. Following these studies, a research pointed out how the process of online advertising emerges with attitudes toward advertising, media context, product involvement, product types, execution, brand familiarity and Internet experience. Advertising effectiveness is evaluated on the base of one or more variables, both coming from offline media advertising measures such as attitude toward the ad, behavioral intention, recall and recognition and Internet-related measures such as click-through rate and repeat visitor rate.

Precisely in this context, the neurosciences have started to play an important role also in the field of marketing, giving life to Neuromarketing.

"Neuromarketing promotes the value of looking at consumer behavior from a brain perspective." In other words, it is the approach used by the advertising agencies to analyze and predict the effectiveness of campaigns by using brain-based tools such as eye-tracking, EEG, or fMRI.

Today it often happens to come across the advertisement banners while surfing the web, watching smart-tv, using smartphone applications.

This study has the objective to analyze the strategy ad campaign for what concerns the smart-tv, it tries to extrapolate information and data to define the optimal layout to capture the user's attention and push him or her to act. The final target is to get the main insights to realize and design the most efficient banner trying to find out the most compelling features.