The mobile analysis has become an important tool in the field of mobile gaming sphere. So the developers as well as affiliate marketers can get tremendous benefit from it. Below you will be able to get familiar with common terms and ways of measuring mobile users’ activity.
This term means any activity or particular action of the user. This may be start and end of gaming, sessions, upgrades, buying of new stuff in the app, achievements, bonuses, rewards and so on.
DAU is alliteration to the term “Daily active users”. So this metrics gives you an insight into the amount of gamers who use your app within last day. In this matter each person will be counted as one even if he or she will open the game multiple times per day.
Which means “Weekly active users”. So every week you will be able to get reports about unique users who have been applying your product during the week.
MAU is referring to “Monthly active users”. It works the same as the previous one, but gather the list of unique users within a month.
By dividing these two metrics you will get the results revealing the percentage of the unique users. This option lets you to monitor the amount of players who are active during the month and adjust you promotion approach or other app’s features to your active audience.
Which means “Average Revenue Per User”. So with the help of this metrics you will be informed about the average income got due to the particular user. This data is shown in percentage. This amount are got from the dividing the total number of gamers by income amount. With this metrics you will be able to predict the revenue you may receive with the existing base of active users. This data enables you to plan the future efficient strategy and compare it to the actual of the past one.
LTV (Lifetime Value)
That is how you will know the total revenue you have got from the single player. With the help of this metrics you can to estimate the efficiency and profitability of the existing users and your future benefits. The aim of it is to cost of acquisition comparing with income got from customers.
This method divides users into groups with similar features and actions. This information can be used by developers and promoters in order to target their campaign and adjust it due to the particular group. So it will be aimed on the quality audience who is useful for the app.