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Implementering av programmatisk internet-annonsering
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media.
2016 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Differences between traditional and programmatic online advertising

Artificial intelligence is a vast concept with application areas from cutting edge robotics to understanding our daily habits in purchasing groceries. According to George Luger the fields of application for this created intelligence will be limited only by our imagination, but for this thesis the limitation is its current use in online advertising. Machine learning is a branch of artificial intelligence based on analysing vast amounts of data to draw a conclusion based on the performed analysis. In marketing this is used in a technique called programmatic marketing, in this field we are faced with the task of extracting large amounts of data, making assumptions from it and creating advertisement based on those assumptions. Then we must find in which context to best place these advertisements, on which device and at which time to gain the users attention and influence them to take action. Programmatic marketing is much based on machine learning and constitutes a way to solve these tasks for each individual user.

The purpose of this thesis is to compare the traditional with programmatic advertising. To accomplish this, two companies are interviewed and reviewed, Scandinavian Airlines (SAS) and the global cell phone operator Telia. Both companies have marketing areas for traditional online-advertising and programmatic advertising. These companies way of marketing makes up a solid ground for comparison together with literature and articles from each field. 

Place, publisher, year, edition, pages
2016. , 54 p.
National Category
Information Systems
URN: urn:nbn:se:uu:diva-298275OAI: diva2:945338
2016-06-07, 10:45 (Swedish)
Available from: 2016-07-01 Created: 2016-07-01 Last updated: 2016-07-01Bibliographically approved

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Heiding, Fredrik
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Department of Informatics and Media
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