Chapter One — 1.1 Background to the Study

Data-Driven Product Decision Making has increasingly attracted the attention of researchers, regulators, and practitioners concerned with product-market fit. This growing interest reflects the recognition that data-driven product decision making does not operate in isolation, but interacts with a wider set of institutional and market conditions found within the Nigerian Capital Market.

the Nigerian Capital Market presents a useful setting for examining this relationship precisely because the conditions there — structural, regulatory, and behavioural — differ from those typically assumed in the broader literature, most of which draws on evidence from more developed economies.

1.2 Statement of the Problem

Despite a growing body of literature on data-driven product decision making, there remains limited consensus on the precise nature of its relationship with product-market fit, particularly within the Nigerian Capital Market. Many organizations continue to make decisions about data-driven product decision making without a clear, evidence-based understanding of how those decisions ultimately affect product-market fit. This gap between practice and empirical understanding is the central problem this study seeks to address.

1.3 Objectives of the Study

1. To examine the effect of Data-Driven Product Decision Making on product-market fit in the Nigerian Capital Market.
2. To assess the extent to which data-driven product decision making influences product-market fit within the study area.
3. To identify the challenges associated with data-driven product decision making in relation to product-market fit.
4. To recommend strategies for optimizing data-driven product decision making in order to improve product-market fit.

1.4 Research Questions

1. What is the effect of data-driven product decision making on product-market fit in the Nigerian Capital Market?
2. To what extent does data-driven product decision making influence product-market fit within the study area?
3. What challenges are associated with data-driven product decision making in relation to product-market fit?
4. What strategies can be adopted to optimize data-driven product decision making in order to improve product-market fit?

1.5 Significance of the Study

This study is significant to a range of stakeholders. For policymakers and regulators, the findings offer evidence to guide the design of frameworks that support healthier outcomes around product-market fit. For managers and practitioners within the Nigerian Capital Market, the study provides practical insight into how data-driven product decision making can be better managed. Finally, it contributes to the academic literature on product management by extending existing knowledge into a specific empirical context, and offers a reference point for future researchers.

1.6 Scope of the Study

In terms of scope, this study confines itself to the Nigerian Capital Market, focusing specifically on how data-driven product decision making relates to product-market fit within that setting. Findings are interpreted within these boundaries rather than as universal claims applicable to every organization or market.