A study on developing a data-based new and returning user persona model for web services
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Data-driven design based on actual usage data is becoming more important in the field of userexperience design. The goal-oriented design process based on a persona is a typical process in UXdesign. Persona has traditionally focused on generating rich user backgrounds, contexts, andscenarios based on qualitative data from individual user interviews. However, traditional qualitativeresearch-based personas are costly, time consuming, and lack reliable data, so there is a growingdemand for data complements with log analysis. This paper proposed a persona modeling methodbased on data-analysis software and a case study presented the value and application of the data–based persona with expert evaluation. Specifically, this study used data analysis tools such asGoogle Analytics, which is a representative data analysis tool, and Beusable, which is newlydeveloped data visualization analysis software in the page, to define the data types used inpersonas. The Beusable homepage was selected as a case study subject and new visitor and returnvisitor data-based personas were modeled. In addition, data-based personas were evaluated byexperts. Data-based personas for new and returning visitors were found to be useful in identifyinguser behavior patterns, confusing factors, and design problems for the website. The perceived valueof a two-page persona was higher than the perceived value of a one-page persona model.
Abstract
Data-driven design based on actual usage data is becoming more important in the field of userexperience design. The goal-oriented design process based on a persona is a typical process in UXdesign. Persona has traditionally focused on generating rich user backgrounds, contexts, andscenarios based on qualitative data from individual user interviews. However, traditional qualitativeresearch-based personas are costly, time consuming, and lack reliable data, so there is a growingdemand for data complements with log analysis. This paper proposed a persona modeling methodbased on data-analysis software and a case study presented the value and application of the data–based persona with expert evaluation. Specifically, this study used data analysis tools such asGoogle Analytics, which is a representative data analysis tool, and Beusable, which is newlydeveloped data visualization analysis software in the page, to define the data types used inpersonas. The Beusable homepage was selected as a case study subject and new visitor and returnvisitor data-based personas were modeled. In addition, data-based personas were evaluated byexperts. Data-based personas for new and returning visitors were found to be useful in identifyinguser behavior patterns, confusing factors, and design problems for the website. The perceived valueof a two-page persona was higher than the perceived value of a one-page persona model.
참고문헌 (14)
- Chapman, Christopher N, "The Personas' New Clothes: Methodological and Practical Arguments against a Popular Method", ~ (2014)
- Chapman, CN, "The Personas' New Clothes", Human Factors and Ergonomics Society (2006)
- Cooper, Alan, "About Face 14: The Essentials of Interaction Design" (2014), Wiley
- Cooper, Alan, "The Inmates Are Running the Asylum: Why High-Tech Products Drive Us Crazy and How to Restore the Sanity" (1999), Sams – Pearson Education
- 이지현, "A Study on the developing data-based referrer persona for web service", 디지털디자인학연구, 17(2), pp.71~80 (2017), 한국디지털디자인학회
- Lidwell, William, "Universal Principles of Design", Rockport Publishers
- Mozyrko, Bartosz, "Visual Analytics: uncovering the why in your data", UX Camp Europe 2016, ~ (2016)
- Pruitt, John, "The Persona Lifecycle: Keeping People in Mind Throughout Product Design (Interactive Technologies)" (2006), Morgan Kaufmann
- How Design Personas Differ from Typical Customer Segmentation Models, "Dorsey, Miora", Forrester Research, ~ (2006)
- Zang, Xiang, "Data-driven Personas: Constructing Archetypal Users with Clickstreams and User Telemetry", Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (2016)