Towards Understanding Analytics in Software Startups
Usman Rafiq

TL;DR
This paper explores how software startups understand and utilize analytics, identifying key concepts like instrumentation, experimentation, diagnostics, and insights to guide data-driven decision-making in early-stage companies.
Contribution
It provides the first qualitative analysis of analytics understanding in software startups, highlighting core concepts and offering insights for setting up analytics in this context.
Findings
Identified four core concepts of analytics understanding in startups
Analyzed platform documentation and startup reports using content analysis
Provides foundational insights for future research and startup analytics setup
Abstract
Analytics plays a crucial role in the data-informed decision-making processes of modern businesses. Unlike established software companies, software startups are not seen utilizing the potential of analytics even though a startup process should be primarily data-driven. There has been little understanding in the literature about analytics for software startups. This study set out to address the knowledge gap by exploring how analytics is understood in the context of software startups. To this end, we collected the qualitative data of three analytics platforms that are mostly used by startups from multiple sources. We covered platform documentation as well as experience reports of the software startups using these platforms. The data was analyzed using content analysis techniques. Four high-level concepts were identified that encapsulate the real understanding of software startups on…
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