Daily retention in relation to the total number of assets

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Example: If the DAU is 100 and the MAU is 500, then the DAU/MAU would be 20% (100/500 * 100). This means that 100% of users who accessed the application today also accessed it at some point in the last 30 days, as today is also part of the last 30 days. 20% of users active in the last month logged in today. A higher ratio would indicate stronger daily retention relative to the total number of active users for the month. So the idea is that DAU/MAU represents the percentage of daily users out of the total number of users who used the app throughout the month. WAU/MAU (Weekly Active Users to Monthly Active Users): This metric indicates the ratio of weekly active users to monthly active users.

If the WAU is 300 and the MAU is 500, then the WAU/MAU would be 60% (300/500 * 100). This means that 60% of users who accessed the app during this week also accessed it at some point over the last month. A higher ratio would indicate Azerbaijan Phone Number stronger weekly retention relative to the total number of active users for the month. DAU/WAU (Daily Active Users to Weekly Active Users): What is it? This metric shows the ratio of daily active users to weekly active users. Example: If during the week I had 300 active users and on one day we had 100 active, then the DAU/WAU would be 100/300 or approximately 33.33%. This indicates that about a third of daily users also used the app throughout the week.




Following the logic above, if we had a higher ratio it would indicate a stronger  in the week. PMAU/DAU (Persistent Monthly Active Users to Daily Active Users): What is it? The "Paying Monthly Active Users (PMAU) / Daily Active Users (DAU)" metric shows the percentage of active users who made a purchase in the previous month. Example: This metric tells us whether returning customers to the pizzeria order more pizzas than new customers. A high value indicates that loyal customers are the basis of the business, while a low value may indicate the need to retain customers. In other words, it tells us whether customer purchase frequency increases over time.