Because of the adaptation to technological and social changes, the advertising environment is constantly evolving and today the central part of online advertising is called Programmatic advertising. It’s an automated media buying technique that involves targeting individual consumers in real-time. However, previous research shows that high frequency is one of the most important issues within programmatic advertising and not all ads bought programmatically is in frame of a good frequency. Furthermore, theories indicate that frequency influences consumers’ attitudes towards advertising, which lead to our research question: “How does high frequency exposure affect consumers’ attitudes towards programmatic advertising?” The purpose of this research is therefore to get a deeper understanding of how highly frequent exposure of programmatic advertising affect consumers’ attitudes towards it. We found that Irritation, Invasiveness, Likeability of relevance and Recognition are terms examined in previous studies related to individually targeted advertising or frequently exposed advertising. In order to carry out an explanatory research, we measured these variables including frequency with a quantitative survey and made statistical calculations such as correlation and regression analyses to see if our hypotheses were supported. The analyses indicated average causal relationships between Frequency and Irritation as well as between Frequency and Likeability of relevance whereas the causal relationships between Frequency and the other two variables were weak. We concluded based on our study that highly frequent exposed programmatic advertising is affecting consumer attitudes both positively with relevance, and negatively causing irritation. However, the relevance that comes with programmatic advertising generates a stronger feeling of likeability than of irritation. / Annonsering utvecklas ständigt, främst genom anpassning till tekniska och sociala förändringar, och idag kallas den centrala delen av onlineannonsering för Programmatisk annonsering. Det är en automatiserad metod för att köpa individuellt riktade annonser i realtid. Tidigare forskning visar dock att hög frekvens är ett av de viktigaste problemen inom programmatisk annonsering. Vidare indikerar tidigare teorier att frekvens influerar konsumenters attityder gentemot annonsering vilket ledde fram till vår problemformulering: “Hur påverkar hög frekvens av programmatisk annonsering konsumenters attityder?”. Vårt syfte med uppsatsen var därmed att få en djupare förståelse för hur frekvent exponering av programmatisk annonsering påverkar konsumenters attityder mot det. Vi konstaterade att Irritation, Inkräktande, Relevans och Igenkännande är termer som är granskade i tidigare forskning relaterat till individuell riktning av annonsering eller frekvent annonsering. För att kunna genomföra en förklarande undersökning mätte vi dessa variabler samt Frekvens i ett kvantitativt frågeformulär och gjorde statistiska uträkningar som korrelation - och regressionsanalyser för att se om vi har stöd för våra hypoteser. Analyserna indikerade ett medelstarkt kausalt samband mellan Frekvens och Irritation samt mellan Frekvens och Relevans medan de kausala sambanden mellan Frekvens och de två andra variablerna var svagt. Baserat på vår studie kunde vi dra slutsatsen att frekvent exponering av programmatisk annonsering påverkar konsumenters attityder både positivt genom relevans och negativt genom skapandet av irritation. Relevansen som kommer med programmatisk annonsering genererade dock högre uppskattning än känslan av irritation.

The thesis presents RTB as a new way of buying media. The theoretical part defines the display advertising market, compares different ways of buying media and deeper describes functions of individual entities within the RTB ecosystem. In the application part are used methods such as the deep interviewing, the primary data analysis from the Adform DSP platform and the content analysis, to characterize the Czech market which is also compared with selected markets of Central and Eastern Europe. A future development of RTB on the Czech market is outlined by means of expert interviews. Shortcomings of the current solution are identified based on comparison and analysis of results of retargeting campaigns for the selected subject. Furthermore, an appropriate modification of a retargeting strategy is proposed with support of experts.

Dans cette thèse, nous étudions deux applications des processus stochastiques au marketing internet. Le premier chapitre s’intéresse au scoring d’internautes pour les enchères en temps réel. Ce problème consiste à trouver la probabilité qu’un internaute donné réalise une action d’intérêt, appelée conversion, dans les quelques jours suivant l’affichage d’une bannière publicitaire. Nous montrons que les processus de Hawkes constituent une modélisation naturelle de ce phénomène mais que les algorithmes de l’état de l’art ne sont pas applicables à la taille des données typiquement à l’œuvre dans des applications industrielles. Nous développons donc deux nouveaux algorithmes d’inférence non-paramétrique qui sont plusieurs ordres de grandeurs plus rapides que les méthodes précédentes. Nous montrons empiriquement que le premier a de meilleures performances que les compétiteurs de l’état de l’art, et que le second permet une application à des jeux de données encore plus importants sans payer un prix trop important en terme de pouvoir de prédiction. Les algorithmes qui en découlent ont été implémentés avec de très bonnes performances depuis plusieurs années à 1000 mercis, l’agence marketing d’avant-garde étant le partenaire industriel de cette thèse CIFRE, où ils sont devenus un actif important pour la production. Le deuxième chapitre s’intéresse aux processus diffusifs sur les graphes qui constituent un outil important pour modéliser la propagation d’une opération de marketing viral sur les réseaux sociaux. Nous établissons les premières bornes théoriques sur le nombre total de nœuds atteint par une contagion dans le cadre de graphes et dynamiques de diffusion quelconques, et montrons l’existence de deux régimes bien distincts : le régime sous-critique où au maximum $O(sqrt{n})$ nœuds seront infectés, où $n$ est la taille du réseau, et le régime sur-critique ou $O(n)$ nœuds peuvent être infectés. Nous étudions également le comportement par rapport au temps d’observation $T$ et mettons en lumière l’existence de temps critiques en-dessous desquels une diffusion, même sur-critique sur le long terme, se comporte de manière sous-critique. Enfin, nous étendons nos travaux à la percolation et l’épidémiologie, où nous améliorons les résultats existants. / In this thesis, we study two applications of stochastic processes in internet marketing. The first chapter focuses on internet user scoring for real-time bidding. This problem consists in finding the probability for a given user to perform an action of interest, called conversion, in the next few days. We show that Hawkes processes are well suited for modelizing this phenomena but that state-of-the-art algorithms are not applicable to the size of datasets involved. We therefore develop two new algorithms able to perform nonparametric multivariate Hawkes process inference orders of magnitude faster than previous methods. We show empirically that the first one outperforms state-of-the-art competitors, and the second one scales to very large datasets while keeping very high prediction power. The resulting algorithms have been implemented with very good performances for several years in 1000mercis, a pioneering marketing agency being the industrial partner of this CIFRE PhD, where they became an important business asset. The second chapter focuses on diffusion processes graphs, an important tool for modelizing the spread of a viral marketing operation over social networks. We derive the first theoretical bounds for the total number of nodes reached by a contagion for general graphs and diffusion dynamics, and show the existence of two well distinct regimes: the sub-critical one where at most $O(sqrt{n})$ nodes are infected, where $n$ is the size of the network, and the super-critical one where $O(n)$ nodes can be infected. We also study the behavior wrt to the observation time $T$ and reveals the existence of critical times under which a long-term super-critical diffusion process behaves sub-critically. Finally, we extend our works to different application fields, and improve state-of-the-art results in percolation and epidemiology.

With the help of Programmatic Advertising and the resulting personalized content, consumers can be targeted precisely and with the help of Artificial Intelligence. The associated use of customer data creates ethical conflicts. Therefore, the research question is asked: How does Programmatic Advertising influence consumer's data security and diversity of opinion and what effect does this have on the further development of the technology? For the purpose of elaborating the research problem a literature analysis and expert interviews are carried out. The analysis shows that Programmatic Advertising has already taken up the majority of digital advertising activities. This results in advantages for advertisers, since consumers can be addressed in a targeted manner. Nevertheless, this provokes data law issues and the demand for more data security for the individual customer, which, among other things, is given more attention by big tech companies. Due to the constant change within this trend, new possibilities arise, such as contextual targeting, in order to continue to do an efficient display of advertising. Nonetheless, this work calls for more regulations to be able to give customers a better overview and control of their used data and to avoid restricted diversities of opinion, which can be promoted through microtargeting and therefore the addressed display of content. The prospects of Programmatic Advertising, however, are predicted with a steady increase because other areas within the media landscape will be pervaded by this technology in the future. / Med hjälp av programmatisk reklam och artificiell intelligens får kunder och individer reklam som är specifikt utformade för just dem. Användningen av underliggande användardata ger upphov till etiska dilemman. Således, har vi följande problemformulering: Hur påverkar programmatisk reklam användarnas data och åsikter, och vilken effekt har detta på den fortsatta utvecklingen av området? Med avsikt att vidareutveckla problemformuleringen utfördes expertintervjuer samt en litteraturstudie. Analysen visar att programmatisk reklam utgör majoriteten av all digital marknadsföring. Detta har resulterat i fördelar för marknadsförare, ty användarna kan bli bemötta mer precist. Icke desto mindre, medför detta legala problem relaterat till användardata och ett ökat kraf av dataskydd för användaren, vilket är något som får stort fokus av stora tech företag. På grund av den konstanta utvecklingen av denna metod, föds nya möjligheter, exempelvis "kontextuell riktad marknadsföring", för att fortsätta vara en effektiv marknadsföringsmetod. Därmed, redogör denna rapport för en mer reglerad spelplan där användarna får en bättre överblick och kontroll över hur deras användardata utnyttjas, samt en mindre inskränkt åsiktspåverkan, vilket är något som skulle kunna ske genom knappnålsfin riktad marknadsföring. Dock är utvecklingen för programmatisk reklam förutspådd ljus, då andra områden inom medielandskapet kommer att genomsyras av denna teknologi i framtiden

Diploma thesis deals with complex view on the current online advertising form in the context of continuous technological development of contemporary society. Internet advertising and its range is viewed from a marketing perspective and in the context of media studies. Together with online advertising history, diploma thesis represents the development of the internet market and in this context it is pointed at reach of online advertising industry. Readers are acquainted with basic types of online advertisements, payment models and online advertising buying ways. Thesis in detail deals with modern trends such as programmatic buying of online advertising, behavioral targeting, retargeting, and many others that are examined from the perspective of advertisers, online content publishers and users whose privacy is from some perspective disrupted by these trends. To show the complexity of the issue, the thesis also contains deeper information about technology. At the end of the theoretical part, the thesis deals with intensively discussed topic of ad-blockers. To create a wider conclusion about the topic, there is also a part of the work that contains interpretation of survey focused on standard users and presentation on findings from structured questionnaire that has been designated to leading Czech...

Online marketing has resulted in a paradigm shift in the advertisement industry. Programmatic buying is an emerging business model that is very promising for online advertising. In online advertising, revenue maximization is always a key matter for publishers. The purpose of this report is to examine whether programmatic buying can be used in conjunction with other parameters such as Google Adwords or Google Trends to increase profit. This research will provide valuable information regarding how to obtain site visitors at a cheap price while maximizing profit on advertisement shown to those users. We investigate a revenue maximization model that calculates the popularity of a set of news in different countries and compares it to the CPM, Cost-Per-Mille, of the corresponding country. To calculate the popularity, the program uses an API from Google Trends and the CPM data is obtained from the company Adform. Furthermore, we originally planned to also include Google Adwords to estimate the price of traffic acquisition. However, since we found several problems with achieving reasonable estimates for our purpose this parameter has therefore been excluded from the final product. The final product can therefore be seen as a soft indicator of how popular different news are in different countries and what revenue can be expected from corresponding countries. / Digital marknadsföring har resulterat i ett paradigmskifte inom reklambranschen. Programmatisk handel är en mycket lovande affärsmodell för automatisk annonsering online och är under stark tillväxt. Inom digital marknadsföring är vinstmaximering alltid en nyckelfråga för utgivare av annonsplatser. Denna rapport ämnar undersöka huruvida programmatisk handel kan användas tillsammans med andra parametrar som Google Adwords eller Google Trends för att öka vinsten från video-reklamannonser. Den grundläggande idén är att skapa trafik till en specifik hemsida för ett så lågt pris som möjligt samtidigt som vi vill att reklamvisningarna ska ge så höga intäkter som möjligt. Rapporten utreder parametrar som videopris för programmatisk handel i olika länder, Bounce Rate, Cost Per Click och Google Trends Score. Dessa parametrar används för att skapa en sammanvägning för att indikera i vilka länder och för vilka sökord den ekonomiska vinsten potentiellt är störst.        Arbetet har resulterat i ett program som beräknar populariteten för ett antal nyheter i olika länder och jämför med CPM, Cost-Per-Mille, priset för motsvarande land. För att beräkna populariteten används ett API från Google Trends och CPM datan kommer från företaget Adform. Från början var tanken att även väga in Google Adwords för att skapa en prisbild över kostnaden att inbringa trafik. Begränsningar som behövt genomföras under arbetets gång är att exkludera Google Adwords prissättning i det färdiga programmet, då det finns svårigheter i att utröna exakta prisuppgifter från Google Adwords. Slutprodukten är därmed en indikator på vilka nyheter som är populära i olika länder och intäkterna som kan förväntas därifrån.

The diploma thesis is focused on the area of Internet media, namely the monetization of advertising, which Internet provides through the programmatic purchase of an internet advertisements that are focused on Real Time Bidding (RTB). The theoretical part deals with a brief analysis of the US media landscape, especially the phenomenon of the programmatic way of buying online advertisements in connection with technological development and optimization strategies in the Internet environment. It represents the emergence of the programmatic purchase, deals with the various forms of online advertising and its development. There is an introduction to two different online media strategies of banking institutions, which are further explored within the exploratory comparative technique - experiment in the practical part. This section focuses on changing technical settings, along with changing ad buying when changing key settings as a part of the ad serving campaign. The aim of the diploma thesis is to introduce the possibilities offered by programmatic advertising within online media in the Czech Republic. It summarizes knowledge in the context of the development of electronic advertising in the application of the two online media strategies of the banking institution.

The diploma thesis is focused on the area of Internet media, namely the monetization of advertising, which Internet provides through the programmatic purchase of an internet advertisements that are focused on Real Time Bidding (RTB). The theoretical part deals with a brief analysis of the US media landscape, especially the phenomenon of the programmatic way of buying online advertisements in connection with technological development and optimization strategies in the Internet environment. It represents the emergence of the programmatic purchase, deals with the various forms of online advertising and its development. There is an introduction to two different online media strategies of banking institutions, which are further explored within the exploratory comparative technique - experiment in the practical part. This section focuses on changing technical settings, along with changing ad buying when changing key settings as a part of the ad serving campaign. The aim of the diploma thesis is to introduce the possibilities offered by programmatic advertising within online media in the Czech Republic. It summarizes knowledge in the context of the development of electronic advertising in the application of the two online media strategies of the banking institution.