As designers have more and more in-depth business contact with product design, data analysis has become an important means for designers to understand user behavior. With so many data indicators in business, how to systematically understand the core meaning of different indicators is one of the learning goals of every experience designer. 1. The stock of user data - DAU/MAU DAU/MAU (Daily/Monthly Active User). 1. What is the DAU/MAU ratio? DAU (daily active): the number of active users in a single day (24h) (de-duplication), which reflects the short-term user activity of the product; MAU (Monthly Active):
The number of active users in a single month (30days) (DAU deduplication), which reflects the long-term user activity of the product; DAU/MAU*30 = Average monthly login days for users 2. What does DAU/MAU say The size of DAU/MAU indicates the stickiness b2b data of this product to users , in other words, the frequency with which users open the product. The ratio of DAU to MAU is high, which means that among the users who have used the product for a month, the proportion of users who use the product every day is high. Even if the frequency of use is high, the user's dependence on the product is strong, and it also shows that the user stickiness is strong. On the other hand, it also means that the churn rate of users is low and the retention rate is high.
The ratio of DAU and MAU is low, all conclusions are opposite, user frequency is low, dependence is weak, viscosity is weak, user churn rate is high, and retention rate is low. 3. What is the data value of DAU/MAU Advantages of DAU/MAU Data This ratio is particularly useful for understanding the value of a product to users. It provides snapshots of user retention periods. For companies, this is a useful metric for assessing traction and potential revenue. Disadvantages of DAU/MAU Data One disadvantage of the DAU/MAU ratio is that you cannot see which users are being retained and which are churn. This is where cohort retention analysis is useful. A cohort can be any similar group of users you define – usually categorized by month. 4. Dynamic analysis of DAU/MAU 1) DAU/MAU increased