# Constructing Data-Driven Personas through an Analysis of Mobile Application Store Data
## 5 Discussion of Creating Personas Using Mobile Application Store Data  
To validate the resultant personas created, we used the expert interview method based on the method used in [PERSON], [PERSON] and [PERSON]'s study [25] and [PERSON] et al. 's study [34]. We conducted expert interviews with eight experts involved in smartphone development and marketing (mean age: 43, six males and two females). The recruited experts have more than 10 years' experience in the UX and lifestyle research area. Expert interviews were generally conducted as semi-structured interviews. Interview questions were generally presented verbally. In addition, the explanations behind the created personas were presented through a slideshow. Interviews were recorded and analysed by the experimenters to find insights. In general, expert interviews were conducted to identify the application usage trends' change between before COVID-19 and during COVID-19. In addition, we revealed our new method to create a persona using smartphone store data. We identified the advantages and disadvantages of the new method through expert interviews. Table 2 presents the questions list for the expert interview. Initially, we reviewed two lists between January and August to observe lifestyle changes arising from the COVID-19 pandemic (Figures 4 and 5 and Table 1). First, all experts agreed that the created persona could reflect the impact of the COVID-19 pandemic effectively. It is self-evident that the severity of the COVID-19 pandemic led people to spend more time at home to maintain social distancing or to work remotely, so people used more video-related applications, such as YouTube, Netflix and Disney+. In addition, they agreed that remote working was preferred during the pandemic lockdown, so people used collaborative tools, such as Microsoft Teams or Zoom, more often. All experts suggested that an approach that uses mobile application store data to create personas has advantages as well as disadvantages. In terms of advantages, experts agreed that this approach could see the complete picture of lifestyle change through mobile phone usage. Mobile phones \begin{table}
\begin{tabular}{p{142.3 pt}} \hline What were the mobile phone usage trends before COVID-19? \\ What were the mobile phone usage trends during COVID-19? \\ Describe the traditional method to create personas for mobile phone developers. \\ We propose the new method to create personas using application store data for the smartphone developers, designers, and marketers. Give us your impressions of it. \\ Tell us if the generated personas from this new method are consistent with the current application usage trends under COVID-19. \\ Describe the advantages and disadvantages of the new method in creating personas. \\ \end{tabular}
\end{table} 
Table 2: Questions list for the expert interview. Figure 6: Four different types of personas in August 2020 constructed through analysis of data from January and August 2020.  
are the most important device for daily life, so the changing trends of application usage reflect the change in user characteristics and user behaviours. In addition, using mobile application data is a good way to create quantitative persona creations. It can support the designer's ideas with a large amount of data. Thus, it can provide powerful evidence for design-related decisions. However, several weaknesses were also suggested by experts. First, this approach cannot create personas automatically. When data collection is completed by the system, the designer needs to calculate the ranking and extract the insights, after which the designer can create the persona. This process is complex and not easy for the average designer. In the future, an automatic persona creation [26] function based on the data should be developed to support designers. Second, the designer cannot understand the reason for the trends change. The system only provides data while the designer needs to calculate a ranking. Consequently, extracting insights depend on the designer's ability.