is a tool regardless of class App, App class shopping, or game App and so on, are an important data index is the App user retention rate, so App user retention rates are divided into several categories? How should we retained data analysis of App
?Two days before the
on the Internet to see such a problem, tool App developed a user oriented, retained has reached 55%-32%-16% (the next day, 7 days, 30 days), growth in the scale of 1K-2K in daily use some means of promotion (after the total has reached 300 thousand users, live on 2W8. But at the same time, 8W months) the daily loss of users on this scale. After a month of active users, user retention basically no change and what at the beginning of the month, then the face of such a problem we should how to analyze
then according to the known data analysis, retained has reached 55%-32%-16% (the next day, 7 days, 30 days), DAU=2w8, MAU=8W, DAU/MAU=35%, DAU/MAU can be called the current user retention rate, (for example, if you have 500 thousand DAU, 1 million MAU, the DAU/MAU value is 0.5, indicating that the game relatively strong viscosity. When the ratio is close to 1, it means that the user super active, in a month, the user login every day, the loss rate is low, strong user stickiness. DAU/MAU ratio is an important parameter of App, is closely related to the success or failure of App. In general, the value of DAU/MAU between 30%–60%, indicating that the user viscosity of App can still be within the scope of this value, the mean DAU/MAU in the 35% level, the standard deviation is 0, DAU/MAU value did not change, indicating that this section App not serious loss of the old users, and whether the work can be gradually growth is the loss rate and rate of new users compared, so that the problems in the growth rate of new users and the new user retention rate, so that we can find the root cause of active users, user retention basically no change and what at the beginning of the month, then according to the problem solution.
user retention rate analysis is basically retained from the next day, data retention and other data analysis, combined with the daily DAU/MAU value, DAU/MAU average, standard deviation and other data, analysis of the root causes of the impact of user retention.