Tailored, more than ever.
dc.contributor.advisor | Wetzels, Ruud | |
dc.contributor.author | Peters, Chaz | |
dc.date.issued | 2024-07-04 | |
dc.description.abstract | opic intrigue. This thesis explores the impact of personalized generative artificial intelligence (AI) on consumer cognition and behavior within the marketing domain. The advent of AI and its integration into personalized marketing strategies has revolutionized how businesses interact with consumers, enabling the delivery of customized content tailored to individual preferences. Despite the rapid growth of AI technologies since 2020, there remains a need for in-depth research to understand its effectiveness fully. The research focuses on how personalized AI solutions influence consumer behavior and cognition, particularly through initial intrigue. Initial intrigue, an essential factor in consumer engagement, was hypothesized to moderate the relationship between personalized AI and consumer behavior. A mixed-method approach was employed, involving a survey and an experiment conducted on 200 participants from Radboud University, with 117 valid responses due to technological limitations. The survey assessed participants' initial interest in financial literacy, while the experiment measured cognitive responses using eye-tracking technology and the decision to take a flyer as a behavior indicator. Key findings revealed no significant relationship between personalization and consumer behavior, challenging prevailing assumptions about AI's effectiveness in marketing. While there was some evidence suggesting a positive relationship between pupil dilation and desired behavior, overall results did not support the hypothesis that personalization leads to enhanced cognitive and behavioral responses. Despite the limitations, including the restricted level of personalization and generalizability, this research provides valuable insights into the nuanced impact of personalized generative AI in marketing. It underscores the necessity for ongoing refinement and a deeper understanding of consumer preferences to develop more effective marketing strategies. | |
dc.identifier.uri | https://theses.ubn.ru.nl/handle/123456789/17165 | |
dc.language.iso | en | |
dc.thesis.faculty | Faculteit der Managementwetenschappen | |
dc.thesis.specialisation | specialisations::Faculteit der Managementwetenschappen::Master Business Administration::Innovation and Entrepreneurship | |
dc.thesis.studyprogramme | studyprogrammes::Faculteit der Managementwetenschappen::Master Business Administration | |
dc.thesis.type | Master | |
dc.title | Tailored, more than ever. |
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