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. 2022 Jun 14:13:875310.
doi: 10.3389/fpsyg.2022.875310. eCollection 2022.

Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP

Tinggui Chen  1   2 , Chu Zhang  1 , Jianjun Yang  3 , Guodong Cong  4
Affiliations

Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP

Tinggui Chen et al. Front Psychol. .

Abstract

Software development is an iterative process from designing to implementation, and to testing, in which product development staff should be closely integrated with users. Satisfying user needs effectively is often the pain point for developers. In order to alleviate this, this paper manages to establish the quantitative connection between users' online reviews and APP (Application Program) downloads. By analyzing user online comments, companies can dig out user needs and preferences. This could benefit them by making accurate market positioning of their APP products, and therefore iteratively innovating products based on user needs, which hopefully will increase the volume of APP downloads. This paper regards WeChat APP during 47 updates periods as the research object. Based on Grounded Theory, user needs are extracted after data cleaning. Next, by using semantic analysis and word frequency analysis, we are able to obtain the implicit feedbacks such as emotion tendency, satisfaction and requirements lie under online reviews. Then, we construct a quantile regression model to study the impact of users' online reviews on downloads based on the influencing factors we extracted so as to provide a decision basis for enterprises to iteratively update their products. Results show that: (1) Generally speaking, needs of WeChat users mainly focus on performance, reliability, usability, functional deficiency, functional insufficiency, and system adaptability; (2) For those APP versions with relatively fewer downloads, user needs are mostly about functional deficiency, followed by functional insufficiency, performance, usability, and system adaptability. At this stage, it is found out that users' emotion tendency and user satisfaction significantly affect the volume of downloads; (3) When the volume of APP downloads is moderate, the user needs are functional deficiency, functional insufficiency, and system adaptability. While under this circumstances, users' star ratings have a significant impact on downloads; (4) In addition, when the volume of App downloads is high, user needs are performance, usability, and system adaptability. Our methods effectively extract users' requirements from online reviews and then successfully build up the quantitative connection between the implicit feedbacks from those requirements and APP downloads.

Keywords: APP downloads; Grounded Theory; online reviews; quantile regression; user demand mining.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Research framework.
Figure 2
Figure 2
Functions deficiency on WeChat.
Figure 3
Figure 3
Functional insufficiency in WeChat.
Figure 4
Figure 4
Function needs of WeChat.
Figure 5
Figure 5
Availability of WeChat.
Figure 6
Figure 6
Different requirements of WeChat on different operating system.
See this image and copyright information in PMC

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