Growth hacking: A scientific approach for data-driven decision making

被引:3
|
作者
Cristofaro, Matteo [1 ]
Giardino, Pier Luigi [2 ]
Barboni, Luca [3 ]
机构
[1] Univ Roma Tor Vergata, Via Columbia,2, I-00133 Rome, Italy
[2] Univ Trento, Via V Inama, 5, I-38122 Trento, Italy
[3] Growthhackers com, Partner 247X Your Dedicated Growth Team Partner &, Via A Brisse,19, I-00149 Rome, Italy
关键词
Growth hacking; Decision making; Scientific management; Data-driven; Choice; BIG DATA; MANAGEMENT; RATIONALITY; TECHNOLOGY; STRATEGIES; MODELS; FIT;
D O I
10.1016/j.jbusres.2024.115030
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
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页数:13
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