This study aimed to explore the organizational resources, competencies, and capabilities needed for the successful implementation of machine learning development projects for digital marketing operations in marketing organizations. The structure of the machine learning development project was investigated via the Agile-Stage-Gate model to identify the workflow, tasks, and roles of the marketing management and development teams during the project. With the accomplished project illustration, the necessary resources, competencies, and capabilities were identified. The findings suggest that marketing organizations’ capability to understand and refine data by taking into the notion the impact of the marketing environment is the most crucial competence of machine learning development projects because it forms a solid base for algorithm execution and successful project implementation for marketing purposes. Marketing organizations must develop rigorous business processes and management procedures to support data governance and thus provide suitable data for machine learning purposes. Personnel’s understanding of the data’s characteristics and capabilities for running successful machine learning projects were also seen as key competencies for marketing organizations.

本研究旨在探索成功实施营销组织数字营销运营机器学习开发项目所需的组织资源、能力和能力。通过 Agile-Stage-Gate 模型调查了机器学习开发项目的结构，以确定项目期间营销管理和开发团队的工作流程、任务和角色。通过完成的项目说明，确定了必要的资源、能力和能力。研究结果表明，营销组织通过考虑营销环境的影响来理解和提炼数据的能力是机器学习开发项目最关键的能力，因为它为算法执行和营销目的的成功项目实施奠定了坚实的基础. 营销组织必须制定严格的业务流程和管理程序来支持数据治理，从而为机器学习目的提供合适的数据。人员对数据特征的理解以及成功运行机器学习项目的能力也被视为营销组织的关键能力。营销组织必须制定严格的业务流程和管理程序来支持数据治理，从而为机器学习目的提供合适的数据。人员对数据特征的理解以及成功运行机器学习项目的能力也被视为营销组织的关键能力。营销组织必须制定严格的业务流程和管理程序来支持数据治理，从而为机器学习目的提供合适的数据。人员对数据特征的理解以及成功运行机器学习项目的能力也被视为营销组织的关键能力。