  In this paper, I present churn prediction techniques that have been released
so far. Churn prediction is used in the fields of Internet services, games,
insurance, and management. However, since it has been used intensively to
increase the predictability of various industry/academic fields, there is a big
difference in its definition and utilization. In this paper, I collected the
definitions of churn used in the fields of business administration, marketing,
IT, telecommunications, newspapers, insurance and psychology, and described
their differences. Based on this, I classified and explained churn loss,
feature engineering, and prediction models. Our study can be used to select the
definition of churn and its associated models suitable for the service field
that researchers are most interested in by integrating fragmented churn studies
in industry/academic fields.
