Optimizing budget for online marketing through analyzing chains of customer journey using data mining techniques

Mekonnen Mussie, 2015

Master Thesis
Betreuende Dozierende: Hans Friedrich Witschel
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One of the main challenges for current advertisers and marketers is to identify which online marketing channel is creating the highest value and where a firm should invest ist resources in order to increase the return on investment. For the past years the budget for digital marketing has been increasing, for instance according to Gartner (2014), itwas 3.2% of the revenue in the year 2013 which increased by 20% from the previous year.But this comes with a dilemma to marketers, on how to allocate their online marketing budgets and identify places to consider redistributing resources. The goal of this study is to provide marketers with budget allocation recommendation approach that might support them with their managerial decision. The study intends to address one of the main challenges for current marketers in identifying which marketing channel is creating the highest value in relation to the budget allocated to it and in return provide insight to optimally reallocate the budget.In this study, budget optimisation algorithm was proposed that would provide marketers with budget change recommendations. The proposed solution was developed based on Markov model attribution and predicted the change in channels contribution on certainbudget change constrains. Evaluation of the proposed approach was done on the datasetsof online user behaviour before and after budget change. The data was collected from a firm, for November 2013 and November 2014, based on the budget allocated for eachmarketing channel before and after budget change. The result of the proposed approach was compared with practical experts decisions regarding reallocation of budget. On the basis of the results of this research, it can be concluded that the experts decisions on budget reallocation resulted in reduced return on investment. In contrast, the proposedalgorithm recommendations suggested that the budget could have been redistributeddifferently in a way that could have created higher return on investment.
Studiengang: Business Information Systems (Master)
Fachbereich der Arbeit: Wirtschaftsinformatik & IT-Management
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Mekonnen Mussie
Betreuende Dozierende
Hans Friedrich Witschel
Sprache der Arbeit
Business Information Systems (Master)
Standort Studiengang