Homepage |
Tutorials
Mobile Analytics - Data Points
Mobile Analytics has a sleuth of data points from which you can get valuable information about your mobile
app's user base. You can then use that information to better target your users for things like
in app purchases, and sending push notification or in app messaging to keep your users
from churning.
Three common components of mobile analytics are demographics, interests, and engagement.
Demographics is about the user: where they live, their age, gender, and the type of device
their using including the OS (operating system). You can usually get this user details by
using third party SDKs or having your own in app sign-up process.
How To Use This Information
Demographics can be used to target your users based on age groups, and location groups. For example if
you have a 'shopping app for clothing', you could target specific age groups based on 'clothing deals' your app has.
User
Interests is about what your users like or their preferences: based on our
'shopping app for clothing', a certain age group might favour more funky clothing and
accessories while an older demographic might prefer more traditional styles.
With this information you could send 'push notifications' to your specific age groups when
you have 'app clothing deals' or perhaps 'new arrivals n styles' in those categories.
Engagement is the third component of mobile analytics and this includes all
actions that users take while using your app. This is also further divided into categories of
activation, conversion and retention.
Activation - this is about how the user must sign up for your app. Using our 'shopping
for clothing app', example, you might have users give their email and optionally select their
favorite type of clothing style.
Conversion - this is about in app purchases made by your app users.
For example, when users purchase an item of clothing, you can track this as
a 'conversion event', and have the user id, type of card used, amount they paid, time, the category of the purchase, and the page from where
they made the purchase in the app.
The data collected from their in app purchase can then be used for these next metrics
which will give you detailed insights into the spending behaviour of your app users.
ARPU - Average Revenue Per User; this metric is derived by calculating your total
number of users in a certain time slot, and divide that by the total revenue
in the same time slot.
ARPPU -Average Revenue Per Paying User; Those users who made a purchase in a selected time slot, and divide that by the
total amount of revenue in the same time slot.
ARPDAU - Average Revenue Per Daily Active User; Total numbers of daily active users, then divided by the total revenue
that was made by the app for the day.
Payer Conversion Rate - number of users who made at least one purchase in a given
time slot, then divide that by the total number of unique users for the same time slot.
Lifetime Value (LTV) is the revenue that is generated by a user. Commonly used
to determine this value is ARPU x (1/Churn rate).
Churned Payer - this metric is the percentage of users who had made a purchase from
your app but then stopped using your app.
Retention - this metric is about what users do when using your app. You can collect
data each time a user logs in or uses your app including the day and time; the device they are
using, their physical location, and where they go in your app - the screens they browse including
the length of time they spend on a particular screen.
The following data points will provide you with a detailed view of your users' behaviours
while using your app.
DAU - Daily Active Users; this is the number of unique users who use your app each day.
MAU - Monthly Active Users; the number of unique users who use your app in a month or a 30 day
time-frame.
Sessions per DAU - this metric lets you know how many times per day a user returns to use
your app.
To get the number divide the total sessions per day by the total number of DAUs for the same
day.
D7 Retention - this gives you the total number of users who are still using your app after 7 days.
D1 Retention - the users like D7, but who are still using the app after 1 day.
Sticky Factor - to get data on the number of monthly user who have become daily users of your
app. To get the number, divide the number DAUs by the number of MAUs.
Retention Rate - to get this data, you first need to have a cohort of users. You can make a
cohort by selecting a certain group of users and give it a name.(usually within your
analytic dashboard you can make a cohort) Then using the data
from your cohort, you can get data on retention rates.
To do so, you select from a cohort you made, and then
divide that by the same cohort but in a different and previous time frame. This gives you
data on users you retained from one time frame to another.
Churn rate - this is the number of users who stopped using your app from one time frame to
another.
By using the data points from Retention, Activation, and Conversion, you get meaningful
insights into how users are interacting with your app; and if they continue to use your app
after certain time frames.
You can implement cohorts for users for any number of tracking metrics. Sessions are also useful
to see where users go in your app and which screens they spend the most time on. This is
information you can use to tweak your app and make it more user friendly.
Conversion metrics let you know what items in your app appeal to users and if sale items
bring in more conversions.
With demographics you can find out which age groups are moreso using your app and where they
spend most of their time in your app; and do certain age groups tend to buy or make purchases
compared to other age groups.
Almost all the Analytical Websites we reviewed allow you to make cohorts and events for
collecting data about your users. Use these to get detailed metrics that can help you improve
your app and bring you more in app purchases.
To read about Analytical Services that offer both free and paid metrics for mobile
apps: GoTo
Mobile App Metrics On-line Services
AndroidAppCoding.com - All Rights Reserved.
All images posted on this Website are ©Copyrighted Material.