Having a plan, the right metrics and managing the right outcome with mobile app metrics against that plan is the best way to ensure success. Gone are the days when your job stopped once your client’s app was live. Customers now expect you to be there, to support them, use your expertise and help them deliver success. You now need to think of yourself as the “Product Manager” of your clients app, working with your client to set the right target, the means to measure the performance of the app against those mobile app metrics and most importantly take the corrective action to drive success.
So where do you start? The problem comes when you’re faced with the hundreds of possible app metrics to report. Which ones are important? Which aren’t?
Also – numbers on their own often don’t tell you much. It’s the combination of the metrics and the inter-relationship or ratio between one mobile app metric and another that helps you build actionable insights for your customers.
So with that in mind, here are 14 metrics you need to be thinking about.
Start talking about app analytics with just about anyone and the first thing they’ll mention is downloads. Sure – it does sound impressive when you can brag about hitting millions of app store downloads – and it certainly looks good on the monthly report you give to clients – but downloads on their own is probably one of the most meaningless metrics. Why? simple – BECAUSE THE NUMBER NEVER GOES DOWN. Have a user who downloads an app and deletes it after seeing the splash screen? Doesn’t matter. It’s still counted as a download. Another important stat to keep in mind – up to 25% of users delete an app after one use.
That said – don’t throw this metric away. Its how you use the number that’s important. What’s important is to track two important elements of downloads. First the trend over time, is the overall download trend rising. Are more potential users finding your clients app and downloading it? If so, that’s good, of course. But were not done yet, that leads us to the second most important element, the ratio of downloads to installs (see next section). If that ratio is growing, by that we mean is a higher percentage of all the app downloads ending up as active installs, then you are on a winner. So don’t dismiss downloads from your KPI’s, just make sure you use them to give you meaningful insight.
So, I hear you ask, whats the difference between downloads and installs? They are the same, right? Well no. Installs pretty much does what it says – tracks the number of times the app has been installed on a device. The difference is between someone who actually downloads the app and then installs the app on a device. Typically this is measured by the firing of the first “app open” event. Understanding the ratio of downloads to installs gives you insight into how many folk download the app but never install. Increasing this ratio will have a huge impact on active installs.
ACTIVE INSTALLS VS ACTIVE USERS
Something to keep in mind when we’re talking about mobile app metrics. This is where things start to get a little tricky and you need to read the label. Some analytics products differentiate between “installs” and “users”, while others lump them into one or the other. An “active install” is an app installed on a particular device, for example, if you download and install Candy Crush on your iPad and then decide you can’t live without the joy of defeating self replicating chocolate and install Candy Crush on your iPhone, this is counted as two separate “active installs” by some analytics programs, while others would count this as one “active user”. There are pros and cons with both measures, you could argue that the key measure is the number of devices that the app is active on is a true measure of traction. Or you could argue that it should be all about the eyeballs and users is the critical measure.
Again, as with installs its the ratio between installs and active installs that important. Is this trend improving over time. Is the remedial work you are doing with your client driving up this ratio? Or, have big rises in new installs driven down the active install ratio, showing that the quality could be worse.
Retention rates are one of the most important mobile app metrics you can track for your clients app. In a nutshell, retention rates measure the number of users who opened the app for the first time and compares that to the number of users who return to the app over a certain period of time. For most apps, you’ll probably be seeing a good retention number for the first few weeks after an app is downloaded (everyone likes new and shiny apps) but how does this number hold up after two or three months, or even a year?
Critical here is to understand the different between retention rates and the expected usage patterns of the app. If its a seasonal app, say a ski app then you’d only expect it to be used for a few weeks of the year. So you have to measure retention over a long time span. If its a transport commuter app then you should expect daily week day use. So context and setting the right targets here are important rather than taking a one-size fits all approach.
For some apps, location is important, for others it could just be “noise”. Where the app lends itself to a geographically diverse user base. Where activities are running to drive up traction in specific locations then of course tracking this is essential.
The questions you should be answering here are:
* Where are your users?
* Are they all coming from one country or from all over the world?
* If they’re just in one country, are they just in one specific region?
One of the most important data points you can get out of location is time zones. This can help you to optimize timings in sending out push campaigns. If the majority of your users are in California, there’s not much point in sending out a push notification at 2am Pacific Time. Knowing what your countries your app is operating is can also help you in planning for language localizations in the future.
You want users to keep using your app, right? That’s why you want to measure its stickiness – a term used to convey how often users are returning to an app and you could say a close cousin of retention rates. One of the best ways of looking at this is focusing on figures known as MAU (monthly active users) and DAU (daily active users). Let’s say, for example that you had 702 daily active installs. During the previous month, you had 4700 active installs. 702 divided by 4700 equals 0.149 or an app stickiness of approximately 15%.
Again, tracking the stickiness trend as part of your mobile app analytics data-set is important. Is the app becoming more or less sticky over time and what can you do to drive this number north?
Here’s further reading if you want to explore MAU vs. DAU statistics in depth.
USER TIME IN APP
This measure of mobile app analytics is important but can be tricky. Everyone wants their users to spend plenty of time in their app, right? In most cases, the answer would be yes. However, what if the reason that the reason that the user is spending more time in the app is because of poor app performance – hanging screens, interrupted sessions, etc. That’s bad. You’ll want to take a look at any kind of performance analytics and coordinate them with user time analytics to make sure that your users are spending more time in the app for the right reasons.
Sure, it’s handy to know how many iOS and Android (anyone mention Windows Phone?) users your app has, but this metric is a lot more important than that. It also gives you an insight into what versions of operating systems your users are using. This can help speed development times by showing you which versions you no longer need to support and where you should be putting your development resources.
This shows you which version of your app your users are using. Seems simple enough, but this can also help highlight any problems that users might have with upgrading in versions of the app. It’s also handy metric to use when targeting users with push campaigns to convince them to upgrade to the next version. Or – you can use a push campaign to ask why they haven’t upgraded yet.
What is the frequency with itch users are coming back to your app? Do users use your app every day? Every week? Every month? You can use session intervals to laser target your power users – those who are using the app every day (or in an X time period) and represent your app’s core audience. These are the users you want to keep happy. If the sessions seem to be dropping, you can target these users with a push campaign to get them back into the app. Remember that it costs 10 times as much to attract a new customer than it does to keep an existing one.
API CALLS AND PROCESSING TIMES
How this is broken down depends on your analytics package. No matter what it’s called, it’s a good metric to keep track of. The API traffic metric measures the number of API calls made by your app over a given time frame. API calls refers to the number of times that an API is used by an app while processing types shows the average response time for an API call. Generally you want to have about a 1 second response time for an API. Anything over 3 – 4 seconds and the majority of users (60%) will abandon the transaction and possibly delete the app out of frustration.
This shows the amount of data stored by users of your app. This is good to keep an eye on for planning future platform upgrades and features.
App crashes are bad. We all know that. Crash analytics can provide you with deeper insight into why an app has met it’s untimely end and help you answer questions to keep the app running its best. Are crashes happening only on a certain operating system and or version? Is it a memory issue? Or does the crash only happening with specific app versions?
CUSTOMER LIFETIME VALUE
At the simplest level, the Customer Lifetime Value (CLTV) tells you how much each app customer is worth and also what you pay to gain that customer. The only problem comes when you have to sit down and derive a formula to determine CLTV. The nice folks over at Apptamin have an excellent post on the topic of figuring out CLTV. Suffice to say, once you get CLTV figured out, you’ll have a much better idea of if your ad spending is working or you need to try another direction.
So, mobile app metrics is a big subject, but too important to ignore. The key to gathering the right data is to use an awesome app analytics tool.
We hope you’ve found this article useful and has given you some ideas on how to approach this with your clients, so you set the right measures and not just pick whats easy.
Did we leave any metrics out? Feel free to leave a comment below!