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      Data-driven UX를 위한 데이터 분석 도구 활용 방안 = How to leverage data analytics tools for data-driven UX

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      https://www.riss.kr/link?id=A109522993

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      다국어 초록 (Multilingual Abstract)

      With the advancement of big data, data utilization has become an essential component in the field of UX design, requiring UX designers to develop strong data analysis skills. Data analysis provides opportunities to predict user behavior and deliver better user experiences, elevating data-driven decision-making as a critical responsibility for UX designers. However, many UX designers face challenges in adopting data-driven approaches in practice, underscoring the growing need for practical tool enhancements to address these difficulties.
      This study aims to explore how UX designers utilize data analysis tools in practice for data-driven UX design, identify the challenges they encounter in the process, and propose solutions to address these issues. First, in-depth interviews were conducted with UX designers to investigate the purposes, processes, and key pain points of data utilization. The findings revealed that UX designers frequently perform user journey analyses and highlighted both the advantages and difficulties of data usage. Subsequently, workshops were conducted to generate ideas for tool improvements that enable designers to analyze and utilize data more effectively. By proposing solutions to address practical challenges in data utilization, this study is expected to contribute to both the advancement of UX design practices and academic discussions.
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      With the advancement of big data, data utilization has become an essential component in the field of UX design, requiring UX designers to develop strong data analysis skills. Data analysis provides opportunities to predict user behavior and deliver be...

      With the advancement of big data, data utilization has become an essential component in the field of UX design, requiring UX designers to develop strong data analysis skills. Data analysis provides opportunities to predict user behavior and deliver better user experiences, elevating data-driven decision-making as a critical responsibility for UX designers. However, many UX designers face challenges in adopting data-driven approaches in practice, underscoring the growing need for practical tool enhancements to address these difficulties.
      This study aims to explore how UX designers utilize data analysis tools in practice for data-driven UX design, identify the challenges they encounter in the process, and propose solutions to address these issues. First, in-depth interviews were conducted with UX designers to investigate the purposes, processes, and key pain points of data utilization. The findings revealed that UX designers frequently perform user journey analyses and highlighted both the advantages and difficulties of data usage. Subsequently, workshops were conducted to generate ideas for tool improvements that enable designers to analyze and utilize data more effectively. By proposing solutions to address practical challenges in data utilization, this study is expected to contribute to both the advancement of UX design practices and academic discussions.

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