Measuring your app’s success is about more than watching the number of downloads increase.
Vanity metrics like downloads aren’t indicative of how much users are actually engaging in your app, or if they’re even completing the actions you want them to.
You need to be analysing and comparing a range of data to really boost your app’s performance – this data will form the backbone of your future app updates and marketing strategies.
It’s easy to fall into a deep hole of ‘analysis paralysis’ where you feel so overwhelmed by numbers you can’t get out and see the light.
If you focus on improving these five metrics then you’ll be on your way to releasing valuable and effective app updates in the future.
Acquisitions represent the amount of people who have downloaded and installed your app. They show whether your user base is growing and where your users are coming from.
From acquisition metrics you can find:
• What channels the new acquisitions are coming from – this will show you where to pour more of your ad budget into
• What the percent of downloads that turned into opens were – this will show you which ad networks (e.g. Facebook) are bringing in the highest value users, not necessarily the greatest number of users
• The cost per acquisition – this will reveal the return on investment for each acquisition campaign
• Your app store ratings and reviews – this will reveal public perception of your app, giving you qualitative feedback
• Your conversion rate of app store traffic to downloads – if traffic is high but you aren’t getting that many downloads you may need to optimise your description/screenshots to push conversions.
The real value of acquisition metrics is in analysing how your acquisition campaigns are performing.
Engagement metrics show if your users are getting value from your app – and, more importantly, if you’re getting value from them.
Engagement can be broken down into four parts:
• Active users: Active users are people who have downloaded your app and have exhibited behaviour that you define as ‘actively engaged’. Are there any common characteristics of your high-engagement users? For example, demographics like country, age or device? Perhaps you can re-position your branding to target more people who fall in high-value demographics.
• Session length: This will give you insights to unlock greater revenue potential. For example, if your funnel takes five minutes to complete and the average session time is only four minutes, you either need to make the funnel shorter or optimise certain steps to push customers further down.
• Goals completed: Each app has its own goals, depending on the industry and vertical it operates in. It may be to get checkout transactions or get shares on social media, for example. Tracking the number of users who complete these goals will show which screens/funnels you need to spend more time optimising.
• User loyalty: This is shown via data like frequency of app launches and session intervals between launches. When you know the typical time lapse between app launches, you can better time your prompts (push notifications, in-app messages and more) to encourage regular opens.
The greatest value in engagement metrics is they reveal the characteristics of your most engaged users who are opening your app frequently, for long sessions and are completing the actions you want them to.
We call these highest value users ‘power users’.
By identifying what drives their high level engagement, you can identify what strategies will be most effective at replicating their behaviour in your disengaged users.
Behaviour metrics essentially cover all the broad activities that users are performing in your app.
Diving into behaviour metrics lets you profile your customers in more meaningful ways than you can could just using device type, location and other basic demographics.
It will reveal which features are giving users the most value and which you should optimise in the next update or get rid of completely.
When you’ve identified optimal behaviour (ideal behaviour you wish every user exhibited) you can analyse people exhibiting that behaviour and hunt for patterns.
Examples of behaviour metrics:
• What screens do users spend the most and least time on? What buttons are they clicking on? What features are they not using? This is where you’ll gain insights for improving user experience in future app updates.
• What percentage of people completed a desired event or action? For example, if your app has an in-app referral program, how many people actually complete the action and refer a friend when prompted?
• What percentage of push notification or in-app message are opened? A/B test different copy, timing and offers to see which are more enticing to customers.
• What kind of in-app events are attributed to that push notification? It’s great that they opened it, but we want action here!
Quality metrics refer to the quality of the code. Technical/user issues can be tracked & measured using 3 sub-metrics:
• Automatic crash-report: Ask your developer to set up automatic crash-reporting inside of your application.
• Manual user feedback
• App store reviews
The first two options should be implemented into the application from the get-go, the latter needs to be monitored over time.
Even when working with the most skilled app developers you’ll find your application will still have bugs. As soon as an issue occurs it’s best that it’s noted with a crash-report and sent directly to the developer, and to the marketer with a time-stamp. This allows the marketing person to cross reference increases or decreases in engagement with temporary technical issues.
As technical issues affect the user experience you will need to keep a close eye on these reports and make sure that bugs/issues are fixed quickly and diligently.
Retention is measured as the percentage of people who return to your app after their first visit.
Retention is one of the biggest issues facing app developer’s today. According to Localytics, 58% of users who download your app won’t use it after 30 days.
An important sub-metric of retention you need to monitor is your users’ life-time value (LTV).
If your retention rate is low, then hitting critical mass becomes an expensive ordeal. A high retention rate increases the average LTV because you get a longer lasting user, but the cost per acquisition stays the same.
Clearly defined data lets you make accurate decisions. Raw, un-segmented, inaccurate data lets you make guesses.
Your job is to set up a system that reports the data you need to know in order to make these executive decisions. And if it isn’t you who’s making the decisions then your manager will love you for reporting to them with a clean spread of comprehensive metrics.
Logan Merrick is the co-founder and director of Buzinga App Development. Download his free Startup Guide To App Development for steps on how to take your app from idea to commercial success.
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