Then your business type will be: information service type business + e-commerce type business (information service type, you need to display information on the official website executive email list to get sales leads; e-commerce type, you are a farm and naturally want to sell things). The data indicators you may need at this time are: GMV, customer acquisition cost, single product sales, PV, UV, customer unit price, new users, etc., repeat purchase executive email list rate. Probably the most important of these are: new users, repeat purchases, total sales. In order to improve these most important metrics.
You may try various methods to acquire new users and use various methods to increase the repeat purchase rate. (2) Data acquisition and collection How to obtain executive email list and collect? The most direct and effective method I have learned from actual combat is to leave professional matters to professional people. You only need to sort out the data indicator system and tell the technology, and the technology will help you executive email list obtain and collect the data you need. (3) Commonly used data analysis methods dismantling; funnel; Compared. Next, one by one 1) Dismantling. It is to dismantle the core indicators into detailed indicators, and determine which aspects of the problem/opportunity ratio appear.
For example, when you disassemble the indicator of sales, you can disassemble it like this: Four essential knowledge systems for high-level operations: strategic executive email list planning, omni-channel operations, brand marketing, and data analysis Another example: When you analyze why the retention rate of young and new users of products is particularly low, you can disassemble it like this: Four essential knowledge systems for high-level operations: strategic planning, omni-channel operations brand marketing, and data analysis 2) Funnel For executive email list example, if you are the operator of Airbnb, then when you sort out the booking conversion path analysis, you need to disassemble it into three funnels for data analysis.