Recommendation Systems in Digital Marketing Evaluating the Role of User Interaction Data
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| Dokumentumtípus: | Diplomadolgozat |
| Kulcsszavak: | adatfeldolgozás adatgyűjtés ajánlási technikák digitális felületek online marketing preferenciák |
| Online Access: | http://dolgozattar.uni-bge.hu/53896 |
MARC
| LEADER | 00000nta a2200000 i 4500 | ||
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| 005 | 20240322125721.0 | ||
| 008 | 240322suuuu hu o 000 eng d | ||
| 040 | |a BGE Dolgozattár Repozitórium |b hun | ||
| 041 | |a en | ||
| 100 | 1 | |a Garay Lilla Anna | |
| 245 | 1 | 0 | |a Recommendation Systems in Digital Marketing |b Evaluating the Role of User Interaction Data |c Garay Lilla Anna |h [elektronikus dokumentum] |
| 520 | 3 | |a In my research paper, I explore the role and potential of recommendation engines in digital marketing. I investigate whether there is a measurable and significant difference in their performance, considering the variability of data sources these systems rely on. To illustrate this, I analyze the performance of two recommendation systems using a real-life example of a service company's recommended services on their website. These systems are based on user search history and previous clicks and user interactions. To assess the performance difference, I employed SPSS Data Modeller- which uses different machine learning systems- and introduced different variables like the day of the week, time of the day, campaigns, campaign creatives, to determine what factors influence users' choices in clicking on specific offers. When comparing the search-based and click-based engines, I used this as a foundation and conducted further calculations in Excel, utilizing the Solver extension. The results of my paper are supported by prior research in this and related fields. The key finding of the paper reveals that there is a demonstrable difference in the performance of recommendation systems, with systems based on previous user interactions outperforming those relying on previous search data. | |
| 695 | |a adatfeldolgozás | ||
| 695 | |a adatgyűjtés | ||
| 695 | |a ajánlási technikák | ||
| 695 | |a digitális felületek | ||
| 695 | |a online marketing | ||
| 695 | |a preferenciák | ||
| 700 | 1 | |a Bánhalmi Dr. Árpád |e ths | |
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