Precision marketing is based on precise positioning and relies on modern information technology to establish a personalized customer communication service system to achieve more accurate, measurable and high return on investment marketing communications for enterprises. It can Deliver products and services to target customers in a targeted manner to increase the success rate of transactions, rather than casting a wide net like traditional marketing behaviors.
To a certain extent, precision marketing can be achieved through the definition of user attributes.
User attributes can determine the user's consumption direction. Different users have different attributes. We must have a certain understanding of user attributes in order to stereotype and characterize your users.
The user attributes mentioned here are attributes in a broad sense, that is, attributes such as the user's age and gender, or they can also be attributes defined for the user by the analysis model. The classification method of user attributes is as follows:
Qualitative is reflected in the enterprise's division of user value. For example, for a text file named "Diary", which document should we put it in? Operators with good computer habits may put this document in a special directory for easy search. But if we put frequently used documents into a deeper directory, it will be more troublesome for us to find it or even forget or delete it. The same is true when we classify users' attributes. Don't forget or delete important users. It's neglect.
When classifying user attributes, you can build a "user attribute classification tree" by imitating the above file storage classification method. It can start from the first root node and continuously refine and discover new users. The root node refines several child nodes, and the child nodes are endlessly refined to more grandchild nodes. Each different node is the user attribute category we divide. When it can no longer be subdivided, the node at this time becomes a "leaf node" in this "tree".
The nodes of this "tree" represent the divided user attributes. For example, items purchased across long distances are divided into long-distance structures and long-distance habits. Then, the long-distance structure is further divided into long-distance items of category A and long-distance items of type B. Class items are long-distanced so that they do not need to be refined further.
Then the long-distance structure is the "category" of user attributes, and why is type A long-distance called "attribute"? If you analyze for a long time, you will find that although "long-distance within a" does not currently have a tendency to be further subdivided, it does not mean that it will not be subdivided in the future. For example, in the future, the transportation route of products will be lengthened, from the east to the west, etc. This attribute is not refined now because there is no new long-distance demand, but if there is such a demand, enterprises will not feel trouble. Then the attribute of "long distance within a" is divided into many categories.
It can be seen that this attribute classification is different from the classification of files and books. The classification discussed here is based on the type and spatial distance of the products purchased by users. If the company classifies these attributes, these attributes will be gradually refined over time in the near future. Books and documents are things that people have a clear concept of, but "user attributes" are things that do not exist in people's concepts.