The role of data analysis
Data analysis plays the following three roles in the daily operation analysis of cross-border e-commerce enterprises:
(1) Current situation analysis. It provides the overall operation status of cross-border e-commerce enterprises at the current stage (including the completion status of various operating indicators) and the composition of various businesses of cross-border e-commerce enterprises (including the development and changes of various businesses) to measure the current operation status of cross-border e-commerce enterprises. The results of the current situation analysis are presented in various forms of daily reports, such as daily reports, weekly reports, monthly reports, quarterly reports, and annual reports.
(2) Cause analysis: determine the causes of the problems existing in cross-border e-commerce enterprises and make corresponding solutions to the causes. Current situation analysis can help cross-border e-commerce enterprises understand the overall operation status of the store and discover the problems in the operation. Finding the root cause of the problem requires cause analysis. For example, the store sales this month fell by 10% month-on-month. What is the reason? Is it because the store traffic has decreased, or the conversion rate has problems, or the average customer price has decreased? Finding the root cause through cause analysis can help to truly solve the problem.
(3) Predictive analysis. Predict the future development trend of cross-border e-commerce enterprises, so that they can formulate operation plans. For example, cross-border e-commerce business operators generally predict the sales of the next month based on the trend of sales in recent months, and use it as the operation target of the store and the basis for employee assessment.
Classification of data analysis
In the field of statistics, data analysis is generally divided into three categories: EDA (Exploratory Data Analysis), CDA (Confirmatory Data Analysis) and descriptive data analysis.
Exploratory data analysis refers to the exploration of existing data under as few prior assumptions as possible, focusing on discovering new features in the data. Exploratory data analysis emphasizes starting from objective data, exploring its inherent data regularity, and letting the data speak for itself.
Confirmatory data analysis generally has a pre-set model before analysis, focusing on the confirmation or falsification of existing hypotheses.
Descriptive data analysis analyzes the various characteristics of a set of data in order to describe the various characteristics of the measurement sample and its distribution, normality or skewness, etc. These analyses are the basis of complex statistical data analysis. The overall characteristics represented. There are many descriptive statistical analysis projects, such as the mean, standard deviation, median, frequency distribution, normality or skewness, etc. These analyses are the basis of complex statistical data analysis.