Left for a week - left forever: burnout of the audience of mobile applications based on Localytics data

    The problem of audience burnout (churn) is one of the most acute in the marketing of mobile applications. The falling quality of traffic leads to the fact that already the next day you can not detect up to 90% of users who came to the application yesterday. Is it worth it to panic or is there a chance of their return? Localytics analytic platform presented an interesting report on “burnout” of the audience and periods of risk of “no return”. We offer you the translation of this article.

    On the smartphone of an average American, you can find more than 30 downloaded applications along with pending downloads, which leads to a high degree of competition between them in the struggle for user attention.
    Earlier, we reported that 22% of users open the application only once, while 34% return to it 11 or more times. It is very important for sellers to quickly calculate one-time users and return them to the application until they are gone forever.
    But how to determine which users will stay for a long time?
    The answer lies in the interval between the first and second visits to the application.

    With a 60% probability, users who do not return within 7 days will never return.
    According to a global study on the use of iOS devices (iPad and iPhone), on average, a user returns no more than 6 hours after the first session. However, if the user does not open the application for more than one day from the moment of the first launch, with a probability of 40% he will never return at all.
    The longer this “period of non-return risk” lasts, the greater the likelihood that the user will not return: after 7 days after the first launch of the application, it is already 60%.

    For certain categories of applications, retention measures must be taken even more promptly. Statistics of applications in the Social and Entertainment categories states that, not returning to the application within 12 hours after the first launch, the user will no longer return to it with a probability of 50%.

    News applications, on the other hand, have the longest time span between the first and second launch.
    On average, they have a “risk of non-return” period of almost 24 hours. Moreover, even if the user does not open the application within 7 days after the first launch, there is still a 59% chance that he will return later. Perhaps this is due to news cycles, increased public interest in news on days of significant events. Health app metrics are close to Social and News. The average user opens the application again after an hour and a half, but there are a large number of users returning much less quickly.

    Users with the longest first sessions return to the application within 1-12 hours, immediately followed by those who return within 24 hours - this is typical for almost all categories of applications and mobile platforms.

    The second group of users, which make up almost half of all returning users, clearly demonstrates the typical behavior of users in relation to new applications: a long first session for testing new items and another approach during the day.
    Users who spend less time getting to know the application also return to it after a few days, which is not surprising.

    Re-engaging users

    It is incredibly important to motivate users not to delay visiting the application again, especially when it comes to applications of the Social, Entertainment and Lifestyle categories. So how not to miss users?

    Push messages appearing on the screen are a great way to re-engage users. However, to avoid an overabundance of users, especially those who only once opened your application, you will want to make your messages more understandable, target them to a specific audience.

    The distribution of push messages into categories will allow you to contact only those users who are in the “risk of non-return” group, and not to all at once. If the push campaign is connected with analytic data, you can contact users based on their behavior during the first session. For example, you can contact users who did not complete registration or did not pay attention to any of the key functionality during the first visit.

    Thus, despite the fact that the “period of non-return risk” may look intimidating, application developers will be in a much better position armed with know-how to retain users in specific time periods (for example, sessions) and tools to combat the outflow of the public, such as push and inline messages.

    The material is based on data from Localytics, a leading analytical and marketing platform for mobile and web applications among more than 1.5 billion devices, 25,000 applications and 5,000 customers.
    Localytics processes 50 billion data entry points each month. For this article, we investigated new users of iOS applications in November 2013 and tracked their user activity until February 2014.

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