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In today’s hyper-connected digital economy, firms face an unprecedented volume of real-time market signals generated by social media, online platforms, IoT sensors, and competitor-tracking systems. Digital market intelligence has evolved from static reporting tools into dynamic systems that enable continuous monitoring and rapid strategic adjustment. This managerial perspective article examines how organizations interpret these signals and translate them into coordinated responses. Drawing on established research in big data analytics, market sensing, and competitive intelligence, the analysis highlights the core strategic challenge: distinguishing meaningful signals from noise while aligning analytics outputs with managerial judgment and organizational processes. Key barriers include information overload, cognitive biases in interpretation, and integration difficulties across functional silos. The article proposes a conceptual cycle linking signal capture, analytics-driven interpretation, decision integration, and adaptive response, supported by feedback loops that enable organizational learning. By synthesizing insights from recent studies on data-driven capabilities and real-time responsiveness, it demonstrates that effective digital market intelligence enhances agility, innovation, and competitive positioning. Managers are provided with actionable guidance on building the necessary interpretive and responsive capabilities. The framework underscores that success depends not only on technological infrastructure but on the human and organizational capacity to act decisively on real-time insights. Ultimately, firms that master this cycle achieve superior strategic flexibility in volatile markets.

In the data-rich digital economy, organizations face unprecedented volumes of market signals that demand rapid interpretation and strategic action. Traditional competitive intelligence approaches, rooted in periodic environmental scanning, are increasingly inadequate for capturing real-time digital signals and converting them into sustainable advantage. This paper synthesizes recent advances in market sensing capabilities and data-driven competitive intelligence to address a critical gap: the lack of an integrated conceptual architecture that links digital signal capture, intelligence interpretation, and strategic decision-making in continuous feedback loops. The analysis reveals how big data analytics, dynamic capabilities, and real-time monitoring systems reshape organizational sensing processes. The paper introduces the Adaptive Market Sensing Intelligence Framework—a novel conceptual model comprising six interlocking layers that enable firms to transform raw digital signals into actionable strategic insights. The framework advances theory by bridging market sensing and competitive intelligence literatures and offers practical guidance for managers seeking to build resilient intelligence systems in volatile, data-saturated environments. Implications for strategic management and information systems research are discussed, emphasizing the need for continuous, adaptive sensing mechanisms.