电商数据分析师要用到的4种数据分析方法

Enterprise data analysis pays more attention to the business background, carries out data analysis and interpretation based on the business background, and excavates the effective information hidden behind the data. Among them, the data analyst acts as a bridge to transform data into information to solve problems or meet needs. For example, through the analysis of the data, e-commerce data analysts can understand the popularity of the products, find the problems of the products, and grasp the specific conditions of the products through data analysis so as to formulate targeted product plans and ultimately generate income. In the whole process of data analysis, what do e-commerce data analysts do? Now the editor will give you a summary of the four methods often used by e-commerce data analysts in data analysis.

Before carrying out the data analysis work, we can first establish the evaluation criteria, and then use this as a reference standard to analyze the quality of each variable of the product and the relationship between each variable. The four methods often used by e-commerce data analysts in data analysis are: comparison, transformation, retention analysis and product price comparison.

Comparative analysis also includes horizontal and vertical comparison. Horizontal comparison is to see who to compare with, you need to choose a suitable competitor to set as the standard of comparison. Vertical comparison is to compare yourself with yourself. For example, if you list the daily turnover of the store, you can clearly see the change in the turnover. Of course, the time unit of comparison can also be week, month, quarter and so on.

On the issue of transformation, we need to understand some commonly used statistical indicators. If you want to know the influence of a store in the market, you can look at "the target number of users of the store"; if you want to analyze whether the store is making a profit, you can look at the average amount of consumption per user over a year, that is, "average consumption amount"; to judge users' satisfaction with the product, you can look at "users' repurchase rate". After determining the above statistical indicators, we can determine the conversion indicators according to the number of target users of the store.

We can judge the traffic of the store by observing the number of active users on a daily, monthly and quarterly basis. But what is needed in the operation of the store is not only traffic, but also "retention", that is, those users who stay in the traffic pool or often visit the store. There is "retention" in order to achieve the sustained growth of products, so it is very important for stores to do retention analysis.