  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 analytics, including instrumentation of
analytics, experimentation, diagnostic analysis, and getting insights. The
first concept describes how startups set up analytics and the latter three
illustrate the usage scenarios of analytics. This study is the first step
toward understanding analytics in the software startup context. The identified
concepts can guide further investigation of analytics in this context. It also
provides some insights for software startups to set up analytics for
data-informed decisions. Given the limitation of the data used in the study,
the immediate next step is to ground as well as validate the acquired
understanding using the primary data, by directly interacting with software
startups.
