@inproceedings{ead86e3b857e49d0a67c4485409ea88c,
title = "Creating manageable persona sets from large user populations",
abstract = "Creating personas from actual online user information is an advantage of the data-driven persona approach. However, modern online systems often provide big data from millions of users that display vastly different behaviors, resulting in possibly thousands of personas representing the entire user population. We present a technique for reducing the number of personas to a smaller number that efficiently represents the complete user population, while being more manageable for end users of personas. We first isolate the key user behaviors and demographical attributes, creating thin personas, and we then apply an algorithmic cost function to collapse the set to the minimum needed to represent the whole population. We evaluate our approach on 26 million user records of a major international airline, isolating 1593 personas. Applying our approach, we collapse this number to 493, a 69% decrease in the number of personas. Our research findings have implications for organizations that have a large user population and desire to employ personas.",
keywords = "Big Data, Personas, User segmentation, Web analytics",
author = "Jansen, {Bernard J.} and Joni Salminen and Jung, {Soon Gyo}",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s).; 2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019 ; Conference date: 04-05-2019 Through 09-05-2019",
year = "2019",
month = may,
day = "2",
doi = "10.1145/3290607.3313006",
language = "English",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems",
address = "United States",
}