The purpose of this study is to conceptualize the role of growth hacking, a data-driven iterative experimentation process, in minimizing the likelihood of innovation failure within firms. Drawing upon existing literature on innovation and growth hacking, we provide a conceptual background to frame our research. To investigate this phenomenon, we employ a qualitative approach that combines the Gioia method and phenomenography. Our primary data source consists of in-depth interviews conducted with managers and practitioners who possess extensive experience in innovation management and growth hacking. Through a systematic inductive concept development approach and a multilevel analysis, we develop a novel conceptualization that illustrates how growth hacking strategies can be effectively implemented across four levels of analysis: market, organization, project, and product. Our findings highlight the importance of adopting growth hacking practices to minimize the likelihood of innovation failure in each of these domains. From a practical perspective, we offer recommendations on the strategies that companies should employ to effectively learn from the challenges associated with innovation. By leveraging these insights, firms can enhance their ability to overcome potential obstacles and optimize their innovation processes.

本研究的目的是概念化增长黑客（一种数据驱动的迭代实验过程）在最大限度地减少公司内部创新失败的可能性方面的作用。借鉴有关创新和增长黑客的现有文献，我们提供了一个概念背景来框架我们的研究。为了研究这一现象，我们采用了一种结合了 Gioia 方法和现象学的定性方法。我们的主要数据来源包括对在创新管理和增长黑客方面拥有丰富经验的管理者和从业者进行的深入访谈。通过系统的归纳概念开发方法和多层次分析，我们开发了一种新颖的概念，说明了如何在四个分析层面有效实施增长黑客策略：市场、组织、项目和产品。我们的研究结果强调了采用增长黑客实践来最大限度地减少每个领域创新失败的可能性的重要性。从实践的角度来看，我们就企业应采取的策略提供建议，以有效地从创新相关的挑战中学习。通过利用这些见解，公司可以增强克服潜在障碍和优化创新流程的能力。