You must analyze data operation. There are many common data analysis frameworks at present, but not just any framework can be us. It requires the operators of enterprise websites to choose the appropriate analysis framework according to the company’s development stage.
The following Fractal data-bas operation analysis framework
AARRR model. Introduction to the data analysis framework for product operations in website operations This framework mainly divides the indicators that companies ne to pay most attention to into five categories: user acquisition, increasing activity, increasing retention rate, obtaining revenue, and viral transmission.
The first category, user acquisition (Acquisition), is very important
In website operation, and high-quality users are effective for enterprise product operations. They will affect the subsequent operation direction, operating costs and product planning. When looking for high-quality users, the choice of promotion channels is crucial. Website operators can set labels and entry barriers according to the tone and positioning viber database of the corporate website, and obtain high-quality users after natural filtering of users.
In this category, website operators ne
To pay attention to the following data: 1. Page views (PV); 2. Unique visitors (UV); 3. Number of visits; 4. Landing page; 5. Exit page; 6. Bounce rate; 7. Number of impressions; 8. Number of server hits; 9. Dwell time; 10. Source of visit. The second category: improving user activity (Action) Before increasing user activity, users ne to be classifi first, and then take advantage of social networks target operation strategies are develop bas on the attributes of different user categories.
User attributes include: city, age
Years of work experience, school graduat, income, etc. Different users are prioritiz in operation activities and content delivery, and then content is accurately deliver to different user groups. Common user activation methods include: user subsidies, gamification, and active invitations. The indicators of user activity include: the number of users who actually participate in the activity, the number of users convert to new users, and the proportion usa data of participating users. The third category is to improve user retention.