Shulou(Shulou.com)06/03 Report--

I believe that when doing data analysis, many people will often encounter these problems: I do not know where to start the analysis; the content and indicators of the analysis are often questioned whether it is reasonable and complete, and I cannot tell why.

Therefore, there must be a clear logical goal when doing data analysis.

The three major functions of data analysis are: current situation analysis, cause analysis and predictive analysis. When and what kind of data analysis should be carried out needs to be determined according to our needs and objectives.

General steps for data analysis:

Answer the puzzle:

The clearer the purpose of data analysis, the more valuable it is. After clarifying the purpose, it is necessary to sort out the train of thought, build the analysis framework, decompose the analysis purpose into several different analysis points, and then determine the analysis methods and specific analysis indicators for each analysis point; finally, ensure the systematization of the analysis framework (that is, what is analyzed first, and then what is analyzed, so that there is a logical relationship between the various analysis points), so that the analysis results are persuasive.

So, how to ensure the systematization of the analysis framework?

Under the guidance of marketing, management and other theories, combined with the actual business situation, build an analysis framework, so as to ensure the integrity of the data analysis dimension, the validity and correctness of the results.

The theoretical models of marketing are: 4p, user behavior, STP theory, SWOT and so on.

The theoretical models of management are: PEST, 5W2H, time management, life cycle, logic tree, pyramid, SMART principle and so on.

Here mainly explains: PEST, 5W2H, logical tree, 4p, user behavior of these five more classical and practical theory, to understand how to build a data analysis framework to use them as a guide.

(1) PEST: mainly used for industry analysis

PEST, that is, Political, Economic, Social and Technological

P: the key indicators that constitute the political environment are political system, economic system, fiscal policy, tax policy, industrial policy, investment policy, level of national defense expenditure, government subsidy level, public participation in politics, and so on.

E: the key indicators that constitute the economic environment are GDP and growth rate, total import and export volume and growth rate, interest rate, exchange rate, inflation rate, consumer price index, disposable income of residents, unemployment rate, labor productivity and so on.

S: the key indicators that constitute the socio-cultural environment are: population size, sex ratio, age structure, birth rate, mortality rate, ethnic structure, women's fertility rate, lifestyle, purchasing habits, education, urban characteristics, religious belief and other factors.

T: the key indicators that constitute the technological environment are as follows: the invention and progress of new technologies, the speed of depreciation and scrapping, the speed of technology renewal, the speed of technology dissemination, the speed of technology commercialization, the key projects supported by the state, the R & D expenditure invested by the state, the number of patents, patent protection and other factors.

Eg: just to give an example does not mean that only these factors are considered.

(2) 5W2H: it has a relatively wide range of applications, such as user behavior analysis, business problem thematic analysis, marketing activities, etc.

5W2H, i.e. Why, What, Who, When, Where, How, How much

This method is widely used in enterprise marketing and management activities, which is very helpful for decision-making and executive activities, and also helps to make up for the omissions in consideration.

Eg: just to give an example does not mean that only these factors are considered.

(3) logical tree: it can be used for thematic analysis of business problems.

Logical tree, also known as problem tree, deductive tree or decomposition tree and so on.

It is a hierarchical list of all the sub-problems of the problem, starting at the highest level and gradually expanding downward.

The main function of the logical tree is to help us sort out our own ideas and avoid repetitive and irrelevant thinking.

The use of logical trees must follow the following three principles.

Essentialization: summarize the same problem into elements.

Framing: organize the various elements into a framework and abide by the principle of no emphasis and no leakage.

Relevance: the elements within the framework maintain the necessary interrelationship, simple but not isolated.

Disadvantages: the related issues involved may be omitted, although brainstorming can be used to summarize the issues involved, but it is still difficult to avoid the existence of inconsiderate places. Therefore, when using the logical tree, try to consider the problems or elements involved.

Eg: just to give an example does not mean that only these factors are considered.

(4) 4p: mainly used to analyze the overall operation of the company.

4p, namely product (Product), price (Price), channel (Place), promotion (Promotion)

Eg: just to give an example does not mean that only these factors are considered.

(5) user behavior: the purpose is relatively single, that is, it is used for the research and analysis of user behavior.

User usage behavior, that is, the various actions taken by the user to obtain and use goods or services.

First of all, users need to have a process of cognition and familiarity with the product, then try it out, then decide whether to continue to consume and use it, and finally become loyal users.

The complete process of user usage behavior:

The user behavior theory can be used to sort out the logical relationship between the key indicators of product analysis and build a product analysis index system in line with the actual business of the company.

Eg: just to give an example does not mean that only these factors are considered.

These methodologies can not only be used alone, but can be used nesting according to the specific situation.

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Last

Clarify the main role of data analysis methodology:

Straighten out the thinking of analysis to ensure the systematization of data analysis structure. Break down the problem into related parts and show the relationship between them. To guide the development of follow-up data analysis. Ensure the validity and correctness of the analysis results.

Clarify the difference between data analysis methodology and data analysis:

Data analysis methodology is mainly from a macro point of view to guide how to carry out data analysis, it is like a pre-planning of data analysis, guiding the development of later data analysis work.

The law of data analysis refers to specific analysis methods, such as comparative analysis, cross analysis, correlation analysis, regression analysis and so on. Data analysis mainly guides how to carry out data analysis from a micro point of view.

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