Impact of Streaming Analytics on Independent Label A&R Practices in Lagos, Nigeria

Thesis Abstract

Streaming platforms and their analytics increasingly shape how independent music labels in Lagos, Nigeria identify, recruit, and develop talent. Yet, there is limited empirical understanding of how A&R practices within such labels adapt to data-driven insights from streaming ecosystems, and what this implies for creative autonomy, market reach, and artist development. This study aims to examine the impact of streaming analytics on A&R decision-making in Lagos-based independent labels, with specific objectives to (i) map the analytics tools and metrics most influential in talent scouting and portfolio management, (ii) assess the relationship between streaming-derived indicators and A&R outcomes such as signings, releases, and commercial performance, (iii) evaluate how label managers interpret data within local industry constraints, including promotion channels, cultural relevance, and distributor relationships, (iv) identify perceived risks and ethical considerations in data-driven A&R, and (v) propose a framework for integrating streaming analytics with qualitative expert judgment to optimize artist development. A convergent parallel mixed-methods design will be employed. The study will target Lagos-based independent labels active in digital distribution and streaming platforms, with a population comprising A&R managers, label executives, and senior talent scouts. A purposive sample of 12–15 labels will be selected, and within each, 2–3 key informants will be interviewed (total n ? 30–45) alongside a survey of 120–180 label staff and A&R practitioners to capture varied roles and experiences. Data collection will combine semi-structured interviews (guided by an interview protocol grounded in streaming analytics literature and local industry practices) and a structured questionnaire capturing metrics usage, decision timelines, perceived reliability of data, and outcomes. Additional archival data will be gathered from label release logs, artist rosters, and publicly available streaming dashboards for triangulation. Quantitative data will be analyzed using descriptive statistics, factor analysis to identify latent constructs in analytics adoption, and multiple regression to test the relationship between streaming metrics (e.g., spins, unique listeners, playlist adds, engagement rate) and A&R outcomes (signings, first-year streaming performance, and release scheduling). Moderation and mediation analyses will explore how organizational factors (size, resource availability, and collaboration with distributors) influence these relationships. Qualitative data from interviews will undergo thematic analysis, with coding guided by constructs from the Resource-Based View and Technology-Organization-Environment framework, enabling the formulation of a nuanced interpretation of how analytics shape strategic choices, risk assessment, and creative risk-taking. A cross-methods integration will compare and synthesize quantitative results with qualitative themes to derive a robust understanding of practice. Expected findings include (i) identification of a core set of streaming metrics that predict successful A&R outcomes in Lagos’ independent label context, (ii) evidence that data-driven signings are more diversified in genre and geographic reach but may be constrained by local market dynamics and distribution networks, (iii) insights into governance challenges, including data privacy, equity in access to analytics, and potential bias in algorithmic recommendations, and (iv) a pragmatic framework for integrating streaming analytics with expert evaluation to support strategic talent development without undermining artistic agency. The study will contribute to knowledge by advancing understanding of how streaming-era data shapes grassroots label practices in a rapidly developing music market, offering transferable insights for similar urban ecosystems in Africa and beyond. It will also extend theoretical debate on data-driven decision-making in creative industries by applying the Technology-Organization-Environment perspective to a specific, under-researched setting and by bridging quantitative indicators with qualitative experiential insight. The main conclusion is anticipated to be that streaming analytics substantially influence A&R practices in Lagos’ independent labels, but their optimal use depends on institutional capability, local market comprehension, and a deliberate alignment of data insights with human judgment and artistic vision. Recommendations include the adoption of a hybrid decision framework that integrates dashboards and predictive models with regular creative review sessions; capacity-building programs to improve data literacy among A&R staff; development of ethical guidelines for data use and artist consent; and a set of policy and industry practices to foster sustainable collaboration among labels, distributors, and streaming platforms to enhance artist development and market success.