What should big data marketing do?

1. Data layer: collect and process data.

The traditional data collection process is generally limited, conscious and structured, such as questionnaire survey. The data you can collect must be what you can imagine. The data structure is good. The general database Mysql or even Excel can meet the data processing flow.

2. Business layer: modeling and analyzing data.

manufacture

The data analysis models used, such as basic statistics, machine learning, classification, clustering, association, prediction and other algorithms, such as data mining, have little difference between traditional data and big data, such as banks, communication operators and retailers.

Merchants have long been mature in using consumer attributes and behavior data to identify risks and payment possibilities. However, due to the huge expansion of data, the algorithm has also gained great room for optimization and improvement.

3. Application layer: Interpreting data

The most important thing in data-oriented marketing is interpretation.

Traditionally, after defining the marketing problem, we collect the corresponding data, and then analyze the data according to the established modeling or analysis framework, verify the hypothesis and interpret it. The space for explanation is limited.

And big data provides a possibility, which can be based on marketing problems, closed mining corresponding data for verification, or open exploration, and draw some conclusions that may be completely different from common sense or empirical judgment. Explanatory points become very rich.