Data analytics in software startups: Understanding key concepts and critical challenges

IF 3.8 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information and Software Technology Pub Date : 2024-12-30 DOI:10.1016/j.infsof.2024.107652

Usman Rafiq, Xiaofeng Wang, Eduardo Guerra

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引用次数: 0

Abstract

Context:

The continuous proliferation of data nowadays has inspired companies to make data-informed decisions. Despite the acknowledged benefits of analytics, there is a persistent question about how companies, especially software startup companies with distinguishing characteristics, can effectively create value from it. In the startup context, analytics refers to the use of startup data and insights to inform strategies and tactics across startup business, product, team, sales, and marketing dimensions.

Objective:

In this study, we aim to bridge the knowledge gap by eliciting an understanding of the analytics that software startup companies hold and identifying critical challenges they face in the realm of analytics.

Method:

We conducted a multiple-case study with eight software startups at different startup stages. In addition to the data collected through semi-structured interviews, we considered other data sources such as analytics dashboards and online data about the startups, including websites and social media platforms. We analyzed the data using thematic analysis.

Results:

Our results firstly revealed a divergent understanding of analytics by software startups, based on which we reported essential characteristics of analytics perceived by them. Then we identified 22 analytics challenges classified into six main themes. The themes encompass data capture and access challenges, data interpretation and bias, communication challenges, cultural challenges, external influences and constraints, and analytics implementation challenges.

Conclusions:

Our findings contribute to a conceptual understanding of analytics in software startups and the identification of critical challenges faced by these startups across different stages. The conceptual understanding lays the foundation for comprehending what constitutes analytics for software startups, while the identification of challenges anticipates critical barriers to the adoption and implementation of analytics. We also provide practical implications to both researchers and practitioners.

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来源期刊

Information and Software Technology 工程技术-计算机：软件工程

CiteScore

9.10

自引率

7.70%

发文量

164

审稿时长

9.6 weeks

期刊介绍： Information and Software Technology is the international archival journal focusing on research and experience that contributes to the improvement of software development practices. The journal''s scope includes methods and techniques to better engineer software and manage its development. Articles submitted for review should have a clear component of software engineering or address ways to improve the engineering and management of software development. Areas covered by the journal include: • Software management, quality and metrics, • Software processes, • Software architecture, modelling, specification, design and programming • Functional and non-functional software requirements • Software testing and verification & validation • Empirical studies of all aspects of engineering and managing software development Short Communications is a new section dedicated to short papers addressing new ideas, controversial opinions, "Negative" results and much more. Read the Guide for authors for more information. The journal encourages and welcomes submissions of systematic literature studies (reviews and maps) within the scope of the journal. Information and Software Technology is the premiere outlet for systematic literature studies in software engineering.