Audience analytics is needed for correcting an advertising campaign and an app itself so you could get maximum income from your product in any conditions (even changing ones). Analytics should cover all the stages of conversion way. The main task of a mobile marketing specialist is to understand all the important aspects of interaction with an app and know the effect from advertising.
Not all the users who installed an app become loyal users. Some don’t pass a registration stage right after the launch. That’s why a number of registrations is always fewer than the number of installs. A good index is 60-80% of registrations but it largely depends on app theme. Besides, there may be more installs than registrations due to a fact that some users are already registered in the app and download it for another device. You can track it with the help of Game Cente and authorizations via social networks.
It’s the quantity of active users who visit an app during a definite period. There’s daily (DAU), weekly (WAU) and monthly (MAU) audience.
This parameter displays an average quantity of time each user spends in an app during one session. It’s not valuable on its own but it allows to segment users by the time they interact with your app.
A marketing specialist should understand how much income do users bring. ARPU index is used for this — an average income from each user. But a business model often doesn’t imply that all the users make transactions, for example, in a case with free-to-play scheme. That’s why an average income is often calculated for a category of paying users — ARPPU (an average income from each paying user).
This metric displays the per cent of opening letters and push-notifications by users. You should be aware of how users react to your tries to get them back to an app.
It’s important to know how much does one install cost. There’s a special metric for it — eCPI (efficient install cost). You need to divide CPI by virality coefficient in order to calculate it. You can calculate virality this way:
eCPI should be lower than CPI.
LTV (life time value) is another important metric. It displays an income from each user for all the time he/she uses an app. LTV is calculated by a simple formula:
Expenses mean all the expenditures: from app development to purchasing advertisements. It’s important to understand that LTV index should be higher than eCPI. I.e. expenses on advertising should be less than an income from each user. A good recoupment of advertising is when LTV exceeds eCPI by 2-3 times.
You can increase LTV and decrease eCPI with the help of precise targeting. But only practice will help here. It’s necessary to make test selections and choose a more beneficial audience on their bases. Besides, it’s important to push each user to larger expenses in an app.
Keeping users is an important task for a marketing specialist. Retention Rate is a special metric for this. It shows per cent of users who left an app some time later. Retention Rate is usually calculated by days during the first week and then — by weeks. It’s good when the index stays at the level of 15-20%. An acceptable index is from 10% and higher.
There are 2 other metrics which cover the process of organic spread of an app. It’s virality and the word of mouth.
You can calculate the first index like this:
In practice it looks the following way:
Virality more than 1 is a good result.
Another metric is “word of mouth”:
You can see the number of users who came by invitations of other users as a result. You can make correction by Churn Rate and virality for more precise index of the metric. A deeper analysis includes user segmentation by activity and loyalty.
Different tricks are used in an app for virality increase. Everything depends on theme and idea of your product. Besides, you should take into account “age” of your users. Stimulate to invitations friends of those people who are in the beginning or in the middle of a life cycle in an app. The ones whose LT is getting closer to the end won’t have enough time to bring you profit.
Loyalty is one of the main indices in audience evaluation. There are several metrics which help to describe it.
The 2 indices shouldn’t differ a lot. But Churn Rate is always bigger than Return Rate.
There are many reasons why users leave: technucal bugs, abundance of edvertisements, unsufficiently considered interface. For example, Churn Rate in social networks may increase because of small audience.
Return Rate may be increased by retargeting and tools for getting similar audience, for example, Facebook Lookalike. It’s significantly cheaper than attracting new audience.
We’ve discussed main metrics which any mobile marketing specialist should use. You can track advertising efficiency and the level of app optimization. A wise analysis of the indices allows to find problems in app mechanics and advertising campaign.