TY - GEN
T1 - Creating More Personas Improves Representation of Demographically Diverse Populations
T2 - 12th Nordic Conference on Human-Computer Interaction: Participative Computing for Sustainable Futures, NordiCHI 2022
AU - Salminen, Joni
AU - Jung, Soon Gyo
AU - Nielsen, Lene
AU - Jansen, Bernard
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/10/8
Y1 - 2022/10/8
N2 - Personas represent distinct user types. However, while online user data can be demographically and behaviorally heterogeneous, most studies generate less than ten personas, regardless of how heterogeneous the data is. Because all persona creation efforts need to assign a number of personas to create, assigning this number evokes a fundamental question, How many personas to create?. To address this question, we apply data-driven persona creation in a dataset with 250 million YouTube views from a global news and media organization. We focus on a statistically optimal number of personas, namely, how the distribution of demographic persona attributes deviates from the baseline user data. Altering the number of generated personas, ranging from 5 to 160 personas per set, we find that more personas cover more age groups and countries, thus improving the statistical correspondence with the raw user data, and increasing the representation of demographic diversity by including more fringe user segments. While the user representation continuously improved with more personas, the relative diversity gain was maximal with 40 personas, implying that, using our data, one ought to create more than 4 times more personas than generally advocated. The results imply that organizations with heterogeneous online audiences benefit from many personas in terms of more inclusive user representation. We further demonstrate how an interactive persona system can help stakeholders navigate many personas with possibly smaller cognitive effort.
AB - Personas represent distinct user types. However, while online user data can be demographically and behaviorally heterogeneous, most studies generate less than ten personas, regardless of how heterogeneous the data is. Because all persona creation efforts need to assign a number of personas to create, assigning this number evokes a fundamental question, How many personas to create?. To address this question, we apply data-driven persona creation in a dataset with 250 million YouTube views from a global news and media organization. We focus on a statistically optimal number of personas, namely, how the distribution of demographic persona attributes deviates from the baseline user data. Altering the number of generated personas, ranging from 5 to 160 personas per set, we find that more personas cover more age groups and countries, thus improving the statistical correspondence with the raw user data, and increasing the representation of demographic diversity by including more fringe user segments. While the user representation continuously improved with more personas, the relative diversity gain was maximal with 40 personas, implying that, using our data, one ought to create more than 4 times more personas than generally advocated. The results imply that organizations with heterogeneous online audiences benefit from many personas in terms of more inclusive user representation. We further demonstrate how an interactive persona system can help stakeholders navigate many personas with possibly smaller cognitive effort.
KW - Data-driven personas
KW - number of personas
KW - user segmentation
UR - http://www.scopus.com/inward/record.url?scp=85140885783&partnerID=8YFLogxK
U2 - 10.1145/3546155.3546654
DO - 10.1145/3546155.3546654
M3 - Conference contribution
AN - SCOPUS:85140885783
T3 - ACM International Conference Proceeding Series
BT - Participative Computing for Sustainable Futures - Proceedings of the 12th Nordic Conference on Human-Computer Interaction, NordiCHI 2022
PB - Association for Computing Machinery
Y2 - 8 October 2022 through 12 October 2022
ER -