TY - GEN
T1 - Findings of a user study of automatically generated personas
AU - Salminen, Joni
AU - Jung, Soon Gyo
AU - An, Jisun
AU - Kwak, Haewoon
AU - Jansen, Bernard J.
N1 - Publisher Copyright:
© 2018 Copyright is held by the owner/author(s).
PY - 2018/4/20
Y1 - 2018/4/20
N2 - We report findings and implications from a semi-naturalistic user study of a system for Automatic Persona Generation (APG) using large-scale audience data of an organization’s social media channels conducted at the workplace of a major international corporation. Thirteen participants from a range of positions within the company engaged with the system in a use case scenario. We employed a variety of data collection methods, including mouse tracking and survey data, analyzing the data with a mixed method approach. Results show that having an interactive system may aid in keeping personas at the forefront while making customer-centric decisions and indicate that data-driven personas fulfill information needs of decision makers by mixing personas and numerical data. The findings have implications for the design of persona systems and the use of online analytics data to better understand users and customers.
AB - We report findings and implications from a semi-naturalistic user study of a system for Automatic Persona Generation (APG) using large-scale audience data of an organization’s social media channels conducted at the workplace of a major international corporation. Thirteen participants from a range of positions within the company engaged with the system in a use case scenario. We employed a variety of data collection methods, including mouse tracking and survey data, analyzing the data with a mixed method approach. Results show that having an interactive system may aid in keeping personas at the forefront while making customer-centric decisions and indicate that data-driven personas fulfill information needs of decision makers by mixing personas and numerical data. The findings have implications for the design of persona systems and the use of online analytics data to better understand users and customers.
UR - http://www.scopus.com/inward/record.url?scp=85052025884&partnerID=8YFLogxK
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U2 - 10.1145/3170427.3188470
DO - 10.1145/3170427.3188470
M3 - Conference contribution
AN - SCOPUS:85052025884
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2018 CHI Conference on Human Factors in Computing Systems, CHI EA 2018
Y2 - 21 April 2018 through 26 April 2018
ER -