What should business intelligence data marketing do?

Now people are talking about the advent of the big data age, but often it's just a distant view and less touching. For enterprises, the new era of business mode of change, the transformation of the market model, how to use data to guide marketing, or foggy.

Some people say that China has only BAT has huge amounts of data that can play big data. But not much data is big data, big data is more in the precise description of individual individuals, based on the description of individual individuals to determine the movement of the group. For enterprises, the data directly linked to the profit is still from the internal enterprises, so do a good job of internal data analysis is the first way to achieve data marketing.

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as a mature application in the background of big data, business intelligence has been widely used in various industries, using business intelligence from most enterprises . Finebi 's experience, business intelligence to guide enterprise marketing needs more and more.

at the technical level, According to Baidu's best wishes, the marketing process based on data is no different from the basic process of data analysis in the past, and requires three dimensions, such as collecting and processing data, modeling and analyzing data, and interpreting data after defining business problems.

Data layer: The traditional process of collecting and processing data is generally limited, conscious, structured, and can be captured in situations that you can imagine. For business intelligence, data acquisition process can be unrestricted, is the unconscious unstructured data collection. All production and operation process information can be transformed into structured or unstructured data.

Business layer: data analysis models used by modeling and analyzing data, leveraging business intelligence OLAP (on-Line Analytical Processing) technology for complex data analysis operations, rapid and flexible large data volume of complex query processing. For example, banks, communications operators, and retailers have matured to use consumer attributes and behavioral data to identify risks and payment possibilities.

Application layer: The most important part of data-guided marketing is interpretation. Traditionally, it is the definition of marketing problems, the acquisition of corresponding data, and then modeling analysis, validation hypothesis, interpretation, interpretation of the space is limited. And business intelligence provides a possibility, can not only according to marketing problems to explore the corresponding data to verify, but also open to use the external environment data and internal data facts combined exploration, to obtain some predictive conclusions.

On the application implementation level, business intelligence is focused on the following points to achieve precise marketing:

Analysis of user behavior characteristics

based on a large number of factual data, we can analyze the user's preferences and habits in the dimensions of age, occupation, education and income , and set " label " , do more than users know themselves.

Accurate message push

Relying on the support of data analysis results, in the analysis of user behavior and characteristics, we subdivide the user group, by mail, SMS, client recommendation, or even the combination of traditional store products listed, paired with sales to specific customers to recommend specific products, to achieve accurate positioning.

Mining key Customers

28 theory tells us that 80% profit from the less loyal old users, and the cost of developing a new user is much higher, so to maintain the old users, mining key users become the most important. Also through the analysis of user behavior, we to determine which users are with the enterprise's products and services to match, is the most valuable users. The most direct is the visit of the site, you can determine whether the user is concerned about what is related to the enterprise. Of course, the use of external social media information, from the countless links to the total mining of the corresponding information, integrated to help enterprises to screen key users.

in summary, the key to leveraging business intelligence data marketing is " Small " , make full use of the data inside the enterprise, build a reasonable system, and " Think Big " , combined with external environmental data, to form more layers of analysis, and gradually outward expansion into a large network.

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What should business intelligence data marketing do?