ID3P: Iterative Data-Driven Development of Personas to Improve Business Goals, Strategies, and Measurements accepted at Journal of Information Science and Engineering (SCIE, Scopus, DBLP indexed)


Yasuhiro Watanabe, Hironori Washizaki, Kiyoshi Honda, Yuki Noyori, Yoshiaki Fukazawa, Aoi Morizuki, Hiroyuki Shibata, Kentaro Ogawa, Mikako Ishigaki, Sachiyo Shiizaki, Teppei Yamaguchi and Tomoaki Yagi, “ID3P: Iterative Data-Driven Development of Personas to Improve Business Goals, Strategies, and Measurements,” Journal of Information Science and Engineering, Special Issue on Interdisciplinary Study on Software Engineering and Data Science, 2018. (to appear)

Personas are fictional characters used to understand users’ requirements. Many researchers have proposed persona development methods from quantitative data (data-driven
personas development). These works do not assume that personas are used continuously or that they can reflect on changes in users, making it difficult to plan reliable strategies in a web service due to dynamic changes in users’ preference. Generally, measuring the effect of strategies is challenging. Personas, which do not reflect on actual current users, prevent effective measurements of business strategies and suitable decision-making. To develop more suitable personas for decision-making in a web service, we previously proposed Iterative Data-Driven Development of Personas (ID3P). To detect changes in users’ characteristics, our proposal includes an iterative process where personas are quantitatively evaluated and revised. Moreover, it provides a quantitative evaluation of business strategies based on GQM+Strategies and personas to improve business strategies and goals. This paper is an extension of our previous work. ID3P can verify personas and strategies even when changes in personas are not drastic. We employed additional case study involving Yahoo! JAPAN’s web service called Netallica to verify it.