User behavior data is a foundation that can help us understand and recognize users in the Internet era; first of all, our operation is user-centric, Whatsapp Database but from the perspective of user analysis, there are mainly two models: The first is the well-known "page analysis model", which is mainly represented by Umeng and Baidu Statistics in China; around the situation of page Whatsapp Database jumps, data collection is carried out to help us analyze; there will be New problem - we can't know why users stay on this page, and we can't very accurately restore what users see and get; so such a page analysis model is not detailed enough and not flexible enough .
The second is the behavior event analysis model based on Whatsapp Database user cognition. Compared with page analysis, the user behavior analysis model is more comprehensive and flexible in data collection. We usually do a lot of things when doing operations: Whatsapp Database doing activities, doing content, designing copywriting around the business goals of attracting new people and promoting activities, and designing some targeted activities to push users; we also need to pay attention to a lot of operation methods,
From Design different operating Whatsapp Database strategies from the perspective of human nature. In short, what we do is to hope that users can recognize the product and the value of our operations; but what I want to ask is - do you know whether the things we have done Whatsapp Database are the same as our expectations. In response to this problem, let's first take a look at the data needed to evaluate the operation effect. Usually, we will look at the cumulative number of users used, the number of active users, the retention, and the length of stay, which are some of our common indicators.