Abstract: At present, the dairy brand loyalty evaluation model is not perfect, and the dairy brand loyalty measurement model for the consumer-oriented industry needs to be further studied. Through machine learning methods, online consumer brand product purchase behaviors are clustered to achieve clustering of users with similar loyalty and to measure online dairy brand loyalty. This study has the advantages of applying machine learning to processing online consumer big data, that is, it has advantages when processing high-dimensional data, when processing data in multiple ways, and when analyzing data with high complexity algorithms. The independent variables, dependent variables, and adjusted variables in the model are measured in the form of a Likert five-level scale. Moreover, this study combines with actual cases to make adjustments to the measurement of dairy brand loyalty and verifies the model performance through simulation experiments. The research results show that the validity of the scale structure is good, and the research model has certain practical effects.
Keywords: Machine learning, clustering algorithm, dairy brand loyalty, simulation model
