In digital marketing, display advertising has always been the largest revenue stream for publishers, and the biggest channel for advertisers to increase the traffic to their sites as well as getting better brand recognition. However, with the ever increasing spread of the smartphone and the continuously smarter machine learning of today, the industry has changed.    This study began with a hypothesis that since traditional display marketing evolved into programmatically bought display, the value of display advertising goes beyond branding and driving traffic to sites. Programmatic display advertising is intelligent display advertising that is bought programmatically based on algorithms and big data. The focus of this study was to analyze programmatic display campaigns, which are defined as marketing campaigns where the purchasing of publisher inventory is done by algorithms, with a set of conditions set up by the advertiser. The first step in answering the research question: “What value(s) in marketing does programmatic display campaigns bring in different stages of a company’s lifecycle and what should be expected from such campaigns in these different stages as well as in the different stages of the customer journey?” was to investigate how advertisers and experts value this type of advertisement. To reach the right customer, at the right time, with the right message, has long been the goal advertisers have with digital marketing. However, the way most advertisers go about doing this, is by using different channels to reach the customer at different stages of the customer journey. This study aims to prove that this way of doing digital marketing might not be the best one. In addition to using different channels for different purposes, could programmatic potentially be used in different ways in order to improve marketing? By compiling information and data from previous studies done in the research area, and real programmatic advertising campaigns, this study produced a framework of recommendations for how advertisers should segment their display campaigns in order to get more value from them. This research is done in collaboration with experts and advertisers in the Schibsted Media Group. My hopes are that advertisers in the group will either read this study or listen to my presentation and re-evaluate how the framework in this study could help them rethink the way they structure their display campaigns and also rethink how the channel should be valued. The findings of this study is that yes, it is possible to use programmatic for more than just branding or for the purpose of driving traffic. / Inom digital marknadsföring har displayannonsering alltid varit den största inkomstkällan för publicister, och den största kanalen för annonsörer att öka trafiken till sina webbplatser samt att få bättre varumärkesigenkänning. Med uppfinnandet av smarttelefonen och den ständigt smartare maskininlärningen, har branschen förändrats. Denna studie började med hypotesen att sedan displayaffären utvecklats till att bli programmatiskt köpt, har värdet av displayannonsering fått ett mervärde långt utöver varumärkeskännedom och för att driva trafik till webbplatsen. Programmatisk displayannonsering, programmatic, är intelligent displayannonsering där visningar köps programmatiskt i realtid baserat på algoritmer och en stor mängd data. Fokuset i den här studien ligger på att att analysera programmatiska displaykampanjer, det vill säga, kampanjer där köpdelen av utrymme på websidor hanteras av algoritmer baserade på kriterier uppsatta av annonsören. Det första steget i att svara på frågan: "Vad bidrar programmatic displayannonsering med när det gäller marknadsföring i olika steg i ett företags livscykel samt i de olika stegen i en kundresa?" var att undersöka hur annonsörer och experter värdesätter denna typ av annonsering. Att nå rätt kund, vid rätt tidpunkt, med rätt meddelande, har länge varit det mål annonsörer haft med digital marknadsföring. Det sätt på vilket de flesta annonsörer går tillväga för att uppnå detta är att använda olika marknadsföringskanaler för att nå kunden på olika stadier av kundresan. Denna studie syftar till att bevisa att detta sätt att göra digital marknadsföring kanske inte är den bästa. Förutom att använda olika kanaler för olika ändamål, skulle programmatic potentiellt kunna användas på olika sätt för att förbättra marknadsföringen? Genom att sammanställa information och data från tidigare studier gjorda i ämnet och verkliga programmatiska reklamkampanjer, har resulterat i ett ramverk av rekommendationer för hur annonsörer ska segmentera sina displaykampanjer för att få mer värde från dem. Denna forskning görs i samarbete med experter och annonsörer i Schibsted Media Group. Mina förhoppningar är att annonsörer i gruppen antingen läser avhandlingen eller lyssnar på min presentation och begrundar hur ramverket i denna studie skulle kunna hjälpa dem att ompröva hur de strukturerar sina displaykampanjer och således även ompröva hur kanalen värderas. Resultatet av denna studie är att ja, det är möjligt att använda programmatic för mer än bara varumärkeskännedom eller för att driva trafik.

Background: Researchers have investigated display advertising in the past several years from different perspectives but only in connection to traditional Web sites and not specifically for social networking sites. Facebook is the most prominent social networking site in terms of number of users and its main source of revenue is its online advertising business. Having display advertising in their virtual space is the reason why social networks are able to offer free service and as such the need to understand how users perceive it arises The most important way of understanding users’ perceptions about the advertis- ing messages is by studying attitudes. In order to understand the attitudes toward Facebook display advertising, it is necessary to examine the factors that affect the attitude-toward-the-ad. Ad perceptions, ad credibility, attitude toward advertisers, attitude toward advertising and mood have been identified by previous researchers as clearly influencing the attitude toward specific ads. Purpose: The purpose of this research is to investigate user’s attitude toward display advertising on Facebook by identifying the main factors that influence the formation of attitudes. Method: In order to fulfill the purpose and uncover the main factors that influence the attitude towards display advertising on Facebook, a qualitative research has been conducted. Both a primary and a secondary data search was per- formed. The primary data was collected by carrying out semistructured interviews with students at Jönköping University which resulted in a number of 20 respondents. The secondary data was gathered through the use of the resources available at the university library, both digital and paper based. Internet Web sites have also been reviewed when needed. Conclusions: The authors found that users display an accepting, positive attitude toward display advertising on Facebook. There have been identified five main fac- tors influencing Facebook users’ attitude and these are ad credibility, ad perceptions, attitude toward the advertiser, informativeness and lack of irritation. Moreover, the informativeness factor was found to have the greatest influence in terms of the behavior Facebook users have toward display advertising.

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.

The thesis Trends of media sales techniques on Czech online media market with focus on programmatic buying describes functioning of automated (programmatic) advertising inventory trading on the Czech market. The text focuses on the penetration of this new method, the mechanics of its functioning and its current and future role within the Czech online advertising market. The first part describes a theoretical framework of programmatic advertising and its main principles and functions. In this chapter, programmatic buying method is defined and established within the different types of methods of advertising inventory trading. In addition, the roles of individual market entities in programmatic trading are defined, as well as the technological platforms, which secure the functionality and operation of automated buying. At the end of the theoretical part, the different types of programmatic transactional methods are defined, the practical use of which is then further explored within the research chapter. The thesis also includes methodological part, which concentrates on methodological framework and relevant research method, followed by the description of the selected methods: data analysis, qualitative research and research of professional and specialized materials. In the methodological chapter are...

While the problem of automatic brand detection has already been studied for in-the-wild image inputs, its resolution in the context of online display advertising remains unexplored. Following the existing works that have successfully applied logo detection techniques to photographs of the real world, this thesis builds upon modern object detection models to perform brand-agnostic logo detection in images of online advertisements. Inference with the resulting convolutional neural network allows the development of image-based brand recognition pipelines that scale to a large number of identifiable brands. Furthermore, to train and evaluate such a network, a logo detection dataset composed of captures of online advertisements is created. Each sample image is annotated with bounding boxes and brand labels. Finally, with the aim of introducing a different approach to the problem, we also design and analyze the performance of a brand detection algorithm based on the extraction and filtering of domain names from the HTML code underlying online advertisements. / Trots att automatisk identifiering av varumärken är ett problem som redan studerats för bilder av verkliga miljöer, återstår det att undersöka lösningar till problemet inom onlineannonsering. Med inspiration från tidigare arbeten som framgångsrikt tillämpat logotypigenkänningsmetoder på fotografier av verkliga miljöer, bygger detta examensarbete på moderna objektigenkänningsmodeller för att utföra logotypigenkänning på bilder av onlineannonser på ett agnostiskt sätt med avseende på varumärke. Inferens med det resulterande neurala faltningsnätverket tillåter utveckling av bildbaserade varumärkesigenkänningspipelines som kan hantera ett stort antal igenkännliga värumärken. För att nätverket ska kunna tränas och senare evalueras, skapas dessutom en datamängd för logotypigenkänning som består av skärmdumpar av online-annonser. Varje bild i datamängden annoteras med boxar runt logotyperna som den innehåller samt etiketter som beskriver vilka varumärken dessa logotyper motsvarar. Slutligen presenteras en ny synvinkel på problemet där vi designar och utvärderar en algoritm för varumärkesigenkänning i onlineannonserna som baseras på att få fram och filtrera domännamn ur den bakomliggande HTML-koden.

I slutet av år 2022 introducerades det nya AI-verktyget ChatGPT, en AI-modell som använder maskininlärning för att generera människoliknande svar i stor skala. ChatGPT:s snabba framväxt medför en ovisshet kring hur AI-verktyget kommer påverka praxis för digital marknadsföring. Denna studie utreder därför vilken roll ChatGPT kommer spela inom olika praxis för digital marknadsföring och ämnar därmed att utreda forskningsfrågan: Hur kommer ChatGPT att påverka praxis för digital marknadsföring? Den valda forskningsstrategin för denna studie är en kartläggning där ansikte-mot-ansikte kartläggning tillämpas. Detta stöds med hjälp av intervjuer som datainsamlingsmetod och vidare appliceras en tematisk analys för att analysera insamlad data. Fem marknadsföringsexperter intervjuades i denna studie och samtliga menade att ChatGPT på något vis påverkar praxis inom digital marknadsföring. Slutsatsen pekar därför mot att ChatGPT, trots dess nya upptäckt, redan börjat påverka processer inom praxis för digital marknadsföring och att det troligtvis i bredare utsträckning kommer fortsätta göra det på olika vis, genom att fortsätta inspirera, effektivisera och optimera. Vidare hade alla respondenter en positiv inställning till att se ChatGPT som ett komplement till dagens marknadsföringspraxis, dock en mer negativ inställning till att se det som ett substitut. / In late 2022, the new AI tool, ChatGPT, was introduced. It is an AI-model that uses machine learning to generate human-like responses on a large scale. The rapid rise of ChatGPT has resulted in a lack of sufficient knowledge about the effect that ChatGPT will have on digital marketing practices. Therefore, this study investigates the role of ChatGPT in different digital marketing practices and aims to address the research question: How will ChatGPT af ect digital marketing practices? The chosen research strategy for this study is a survey strategy, as well as the application of the face-to-face survey. This is supported by the data collection method interviews and then a thematic analysis is applied to analyse the collected data. Five marketing experts were interviewed in this thesis and all believed that ChatGPT will, and already has, in some way influenced digital marketing practices. The conclusion therefore points to the fact that ChatGPT, despite its recent discovery, has already begun to influence processes within the practice of digital marketing. Furthermore ChatGPT will most likely continue to enhance digital marketing in a variety of ways on a wider scale, through continuing to inspire as well as contribute with efficiency and optimisation. In addition, all respondents had a positive attitude towards seeing ChatGPT as a complement to current marketing practices, however a more negative attitude towards seeing it as a substitute.

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...

This thesis provides comprehensive insight into the internet marketing used by the eshop. The aim of this thesis is to analyse the eshop and internet marketing tools used by the eshop to promote its products. The result of the analysis is an evaluation of effective Internet marketing channels. Proposals and recommendations that will lead to the optimization of eshop and internet marketing are drawn up based on the results of the analysis.