Growth hacking: A scientific approach for data-driven decision making
将科学方法与泰勒管理原则结合，提出增长黑客作为组织数据驱动决策的科学方法，通过分析、构思、优先级排序、测试和评估的迭代循环，帮助企业应对不确定性并抓住机遇。
• We present Growth Hacking as a scientific approach for data-driven decision making. • We combined the scientific method and management principles with academic and practical insights in Growth Hacking. • We outline the prerequisites, steps, and facilitators for adopting Growth Hacking as a method for data-driven decision-making. • We point out tools for the real-world business applications of Growth Hacking. Today’s businesses necessitate data-driven decisions to continuously adapt (and even shape) their environment to stay competitive. Growth hacking, with its emphasis on experimentation and data analysis, offers a promising approach to meet this need. Even though interest in growth hacking is increasing, the literature on the topic is still developing, and notclear guidance in how to implement it has yet been provided. Combining the scientific method and Taylor’s scientific management principles with growth hacking insights from academic research and practice, we present growth hacking as a scientific approach for data-driven decision making in organisations. Through its iterative cycle of analysis, ideation, prioritisation, testing, and evaluation of prerequisites and facilitators, growth hacking empowers companies to make data-driven decisions, enabling them to navigate uncertainty, identify and seize opportunities, and transform their operations to adapt to or shape their environment. We also provide point out tools for the real-world business applications of growth hacking.