A Survey of 15 Years of Data-Driven Persona Development

<p>Data-driven persona development unifies methodologies for creating robust personas from the behaviors and demographics of user segments. Data-driven personas have gained popularity in human-computer interaction due to digital trends such as personified big data, online analytics, and the evolution of data science algorithms. Even with its increasing popularity, there is a lack of a systematic understanding of the research on the topic. To address this gap, we review 77 data-driven persona research articles from 2005–2020. The results indicate three periods: <em>(1)</em> <em>Quantification</em> (2005–2008), which consists of the first experiments with data-driven methods,<em> (2)</em> <em>Diversification</em> (2009–2014), which involves more pluralistic use of data and algorithms, and <em>(3)</em> <em>Digitalization</em> (2015–present), marked by the abundance of online user data and the rapid development of data science algorithms and software. Despite consistent work on data-driven personas, there remain many research gaps concerning (a) shared resources, (b) evaluation methods, (c) standardization, (d) consideration for inclusivity, and (e) risk of losing in-depth user insights. We encourage organizations to realistically assess their data-driven persona development readiness to gain value from data-driven personas.</p> <h2>Other Information</h2> <p>Published in: International Journal of Human–Computer Interaction<br> License: <a href="http://creativecommons.org/licenses/by-nc-nd/4.0/" target="_blank">http://creativecommons.org/licenses/by-nc-nd/4.0/</a><br> See article on publisher's website: <a href="https://dx.doi.org/10.1080/10447318.2021.1908670" target="_blank">https://dx.doi.org/10.1080/10447318.2021.1908670</a></p>