This study investigates how sport-tech entrepreneurs make sense of heterogeneous lead-user signals in new product development under conditions of uncertainty. While prior research has widely emphasized the role of lead users as sources of valuable and actionable knowledge, it often assumes that user inputs reduce uncertainty by providing clear guidance for innovation. Challenging this assumption, this study draws on sensemaking theory, signaling theory, and paradox theory to conceptualize lead-user feedback as a set of ambiguous and potentially conflicting signals that require interpretation rather than direct translation into product decisions.
An exploratory sequential research design was adopted. In the first phase, survey data from 97 elite and professional athletes were analyzed using k-means cluster analysis to identify distinct configurations of lead-user signals. The analysis revealed two main profiles: (i) cautious/ambivalent users, characterized by moderate perceived usefulness combined with concerns related to usability, comfort, adaptability, and willingness to engage in co-creation; and (ii) receptive/engaged users, characterized by consistently positive evaluations across all dimensions, including performance value, usability, data reliability, and collaborative intent. These findings highlight that lead-user input is not homogeneous, but instead structured in differentiated and sometimes contradictory configurations.
In the second phase, semi-structured interviews with three sport-tech entrepreneurs were conducted to explore how these configurations are interpreted in practice. The qualitative findings show that ambivalent signals are subject to divergent interpretations: they may be framed either as remediable design issues requiring iterative refinement or as indications of deeper misalignment between the product and its target users. Conversely, positive signals are generally interpreted as validation of the product concept, although they do not eliminate uncertainty and are not always associated with immediate readiness for scaling. Across cases, decision-making emerges as an iterative and interpretive process shaped by entrepreneurs’ assumptions, strategic priorities, and technical constraints.
By integrating quantitative and qualitative evidence, this study contributes to lead-user research by reframing user inputs as signals that generate both insight and ambiguity. It also advances research on entrepreneurial decision-making by highlighting the central role of sensemaking in constructing coherence among heterogeneous evaluations. From a managerial perspective, the findings suggest that the key challenge is not merely to collect user feedback, but to develop capabilities to interpret and prioritize conflicting signals in technology-driven innovation contexts.