A large number of data service platforms generated on the big ws number list data outlet mostly serve the mutual gold industry. Based on this, the role of customer groups should be greater in the mutual gold field than in other scenarios. Let's talk about how to segment customers. The customer group can be divided based on a single data dimension, or it can be divided based ws number list on multiple data dimensions. A single dimension can make a division similar to the aspect of the customer group, such as: occupation.
Age, income level, etc.; the division of multiple dimensions requires more business understanding, such as user value grouping, decision tree grouping, and clustering based ws number list on RFM. grouping, etc. Single-dimensional grouping is easy to understand. For ws number list example, we can divide customers into teenagers, youth, middle-aged, middle-aged and elderly, and the elderly based on the information of age. There are no strict and fixed requirements for the threshold, but generally minors under the age of 18 are Special groups, the elderly over the age of 65 are generally excluded from the mutual gold field.
This kind of continuous variable can be divided into categorical variables according to a certain meaning and used for grouping. There is also a class of discrete variables such as ws number list gender, education, and even city level, which are themselves very suitable as clustering variables. By focusing on these groups, we can deeply understand the customer group structure of the ws number list business, which can help us make macro-decisions.
