A Developers’ Guide to App Analytics. Part 3: Engagement
How many people installed your app? How many opened it yesterday? How long did they stick around? Critical questions – and all answered by engagement analytics…
It’s easy for app makers to get hung up on the total download number. Flappy Bird? It did 50m installs!
But this figure only tells you so much. What if you have an impressive install number but find that 97 percent of your customers never open your app, for example? Mmm, not so impressive.
Clearly, there’s far more to engagement metrics than total downloads.
In this third article on app analytics, we will show how you can go much deeper using the many available engagement tracking tools.
Before we do that, let’s very briefly re-cap the app analytics basics.
App analytics SDKs help developers to understand their customers better. Developers simply integrate these SDKs into their apps to chart the behaviour of their users. They can view the resulting insights via graphs and charts displayed on a dashboard.
In the previous article, we explored analytics that track user experience – in other words, what users are doing inside your app.
Here, we will look into analytics that track key engagement metrics. We can group them into three areas, namely:
- Active user numbers
- Session length and depth
- Churn and retention rates
Let’s dive in.
Daily Active Users (DAU)
Your total app download figure can only tell you so much about your app’s success. What really matters (whether you are monetizing with ads or with in-app purchases) is how many regular customers you have. Your DAU metric will tell you. It counts individual users once, no matter how many times per day they open your app.
Monthly Active Users (MAU)
While DAUs can vary a lot, the MAU figure offers a more reliable indication of your app’s popularity. Your active user base should always be higher than the number of new users. If it is, it means that users are coming back more than once.
How frequently are customers returning to your app? There’s a formula for that. Simply divide MAU by DAU to get a percentage. The higher this percentage, the stickier it is.
For example, let’s say you have 10,000 monthly users and 1,000 daily users. Your rate is 10 percent.
Now, let’s say you make changes to your app. You still have 10,000 monthly users but your DAU goes up to 3,000. Your rate is 30 percent. Well done, you just made your app a lot stickier.
How long are users dwelling inside a single session? This is useful to know, though your objectives will depend on your app type. If you have a train booking or weather app, you probably want sessions to be short but frequent. For a game, you probably prefer them to be longer in duration.
And you can obviously break this data down further to draw more conclusions. Are users following a similar screen flow? Which screen are they coming from? Where are they going next? The answers will help you iterate more effectively.
This is the time between two consecutive sessions of a user inside your app. It’s a good measure of the addictiveness of your product.
Needless to say, this is just scratching the surface of what’s possible to measure. In all the above areas, you always go more granular – by breaking down results by device, age, demography, gender and more.
How many customers downloaded your app, and continue to use it regularly? These are your most valuable users, so it’s vitally important to know the numbers.
Analytics tools can give you the answer. They do this by registering a users’ first login and then tracking their subsequent behavior. So, you look at the number of users that use your app within a set time and then track the same group at a later date to see how many you have retained.
Obviously you can modify the results by changing the inputs. For example, you could compare the activity of your chosen cohort of users this month to, say, last month or the same month last year.
This is the opposite of retention. It shows how many customers downloaded your app, and subsequently deleted it.
There is so much you can know about your users desire to engage (or not) with your app. But this info is pretty useless without the power to change things. This is why engagement tools also let you measure the effectiveness of your actions too.
And there’s no shortage of ‘actions’. They start with the obvious such as making sure your on-boarding process is a delight. You can reduce the number of steps necessary, include multiple registration options or even change the wording. In all cases engagement tools will help you A/B test to see what works best.
Same goes for push notifications and email. Reminding users about new features, community activity, incomplete sessions etc can all drive activity. However, care is needed here. There’s a fine balance between timely reminders and annoying spam.
Your app engagement analytics tool will help you see how many notifications were swiped and read. You can quickly develop an understanding of the best time of day or day of week to send them, You can also see which headlines trigger actions and which fall flat.
Ultimately, all this tracking and tweaking is for one purpose: to drive revenue. So how can you measure RoI? Well, for that you need a different type of analytics tool – one which tells you which users spend the most, which promotions drove most returns, where to place your ads, how to word your payment screens and more.
In the final part of our analytics series, we will take a look more closely at these tools.