Nowadays, mobile app development services play an integral part in everyone’s life. The high popularity of applications creates high competition in a mobile business. A large number of applications appear every month, but only a small part of them receive the planned attention from users. That’s why analytics is important for mobile apps: even for startups, it is necessary to monitor indicators of app performance to create a successful digital product.
After the creation and the launch of the application and during the development of a promotion plan, the following questions arise: how can we monitor its effectiveness and what metrics should we use for this purpose?
There are several groups of mobile analytics metrics: indicators that help to monitor audience growth, user retention, user activity, and monetization. These mobile app analytics metrics help to monitor the effectiveness of the created product and make the required management decisions for its further development.
New Users is the indicator that shows the number of new users that appeared on a particular day or period. The project will grow when the number of new users exceeds the outflow from the application. The ways of involving new users are advertising campaigns and the introduction of viral mechanisms.
Total Users shows the number of users who are in the database at the selected date.
Downloads is the number of downloads of the application for a specific period.
These analytical metrics for mobile apps help to determine the effectiveness of the project and to analyze the dynamics of the interest of users, which is why analytics is important for mobile apps promotion.
1-day Retention is the percentage of users who have returned after the first visit. Such an indicator directly reflects the user's interest in the project. Your product does not suit the user if he doesn’t return per day after the visit. Most often, it is associated with the inconvenience of the product or the lack of functions required by the user.
7-day Retention is the percentage of users who have returned after 7 days since their first visit.
28-days Retention is the percentage of users who have returned after 28 since the first visit.
7-day retention and 28-day retention are analytical metrics for mobile apps that provide an opportunity to analyze the retention of users for a longer period. The user is interested in the product if he returns after 7 days since the first visit and especially if the user returns after 28 days since the first visit. Ideally, all three indicators should be 100%, but it happens very rarely.
Rolling Retention is the percentage of active users who have opened the product for the first time on the selected date.
The following mobile app analytics metrics are used to estimate user activity:
DAU (Daily Active Users) is the number of active users who logged into the application on a certain day. It helps to determine the user’s activity throughout the day.
WAU (Weekly Active Users) is the number of active users who visited the application during the week. These analytical metrics for mobile applications help to determine the user activity during the week. But it is not the amount of DAU for 7 days. If a unique user enters the application every day for 7 days, then this indicator will increase.
MAU (Monthly Active Users) is the number of active users who visited the application within a month.
These mobile analytics metrics help to determine the scale of the project, and their growth is very important. To ensure this growth, it is required to maximize the flow of unique users and the percentage of their retention.
Sticky Factor = DAU / WAU or WAU / MAU, reflects the regularity of user inputs.
The indicator shows how regularly users visit the application and helps to determine their interest in your application. Mobile apps analytics benefits are the possibilities to measure the success of your app by user behavior and, with the right analysis, adjust your further promotion strategy.
But these indicators have strong fluctuations because of the unstable flow of new users. To avoid such fluctuations, the following indicators were developed: LDAU (Loyal Daily Active Users), LMAU (Loyal Weekly Active Users), and LMAU (Loyal Monthly Active Users). The difference from the previous indicators is that these indicators take the number of unique loyal users into account. In this case, the user is loyal if he launches the application at least once a day after the first visit.
It turns out that the closer the DAU and LDAU indicators are, the fewer users who do not return to the application after a day since their first visit. Accordingly, the closer DAU and LDAU are, the higher the indicator of 1-day retention.
Users Online shows how many users are in the application at a specific moment. This indicator updates every 5 minutes. It is especially useful for online games.
Sessions is the indicator that shows the number of sessions (the number of visits of app users) over the period.
Average Session Length is the average duration of the session (determined by dividing the total duration of all sessions by their number). This indicator is relative: in some applications, a long duration of the session is a good indicator (for example, in games), in others, a short one is good (for example, applications for calling a taxi).
Lifetime shows the duration of the app's usage from the first to the last entrance. It is the most effective metric for narrow user segments. It helps to determine the lifetime for each segment and to offer discounts, share gifts, etc., just at the moments when it’s needed most of all. This indicator needs to be increased because the longer users are in the application, the more loyal they are.
Paying Users is the number of active paying users per day.
Paying Share is the percentage of users who made payments out of all active users during the period.
Ideally, each user is a paying user, and Paying Share is 100%. In fact, this indicator is much smaller, and its growth of at least 1% is already a great achievement for the project.
Paying Conversion is the percentage of paying users among all those who registered for a certain period. As in the case of Rolling Retention try to find a jump in the behavior of this indicator. It is possible that it will indicate to you some conditions in which the percentage of paying players is greater than the number of registrations. Each payment made by the user is a separate transaction in the database. Therefore, one user can make several transactions for a period.
Transactions is the total number of transactions per period.
Transactions by User shows how many transactions an average paying user has made during a certain period. Mostly, these mobile apps analytics indicators become higher in free-to-play games, because in such projects there is a high probability that after the first payment will follow the second, the third, and so on.
Gross is the total amount of all player payments for a certain period.
However, this money will not come to the developer in full measure: the application store takes their commission.
Revenue is the indicator that shows the income minus the commissions of the stores.
ROI (Return on Investment) shows the percentage of return on investment in paid traffic. It is calculated by dividing Gross by Install Costs. If ROI> 100%, it means that the traffic has paid off.
ROI 7,14, 30, 60, 90 is the return on investment for 7, 14, 30, 60, 90 days respectively. They allow the evaluation of the effectiveness of advertising companies for different periods of time by placing them in equal conditions.
RROI is calculated by dividing Revenue by Install Costs.
ARPU (Average Revenue Per User) determines the average income that is received from one active user for a period. ARPU shows the monetization efficiency of the project: the higher the indicator is, the greater the income per user for a period is. It is very convenient for comparing the effectiveness of projects.
ARPPU (Average Revenue Per Paying User) determines the average income that is received from one paying user for a period. While determining this indicator, only users who have made a payment for a certain period are considered.
Cumulative ARPU is the indicator that helps to track the audience that has appeared for a certain period. In this case, the income that these users brought, as well as their number are taken into account.
Cumulative ARPU N days (for 7, 14, 30, etc. days) is a nondecreasing metric: that is, the more days since the registration has passed, the higher this indicator is.
LTV (Lifetime Value) analytical metrics for mobile applications shows the amount of money that a user brings in on average for the entire time of usage of the application. This indicator combines both the duration of the user's activity and his payments and allows to determine the cost of attracting a new user. For an effective business, it is necessary for LTV to be more than the cost of attracting users. Therefore, the longer the user is in the application and the higher the average income from it, the higher the LTV.
In this article, we have surveyed key mobile analytics metrics that it is important to pay attention to. Nevertheless, the most important thing while analyzing an application is not the indicators themselves but their interpretation.
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