There’s a new wave of analytics coming for mobile. The first wave, as you may have guessed was downloads. Downloads, downloads, downloads. A lot of success and measures of quality were done on this.
We then moved into focusing on engagement. With the assumption that downloads could be bought, and the observation that many apps were never opened beyond the first or even after download, we moved to measuring monthly active users. This was the second wave. MAU or DAU quickly became the statistic that drove metrics and still does today. For example, MAU gives a better indication of server load than downloads do.
But now the third wave is approaching. This is the measurement of out of app interactions. The traditional model of interaction is open app, do task, close app. However, now, there are other ways to interact with your app. These include, but aren’t limited to:
- Voice Search/Commands (Siri, Google Now, Alexa)
- Interactive Notifications
- In-Car experiences (Carplay, Google Auto)
- Bots (Facebook, WeChat)
- Messaging Add-ons (iMessage Stickers, apps)
- Sharing (Post to your app’s online content feed, eg twitter)
- Wearables (Watch Faces on Watch, Android Wear)
We’re all encouraged to think about how we can add value to users through these “extensions” of our apps. However, sometimes this may decrease in app engagement. We need a way of measuring if our attempts to add value is working.
Measuring these are essential to determine app success. However, it’s easy to get bogged down in the data.
“Computers promise a fountain of information, but deliver a glut of data” — Jeff Johnson
We need tools to give us insights and suggest actions to improve our apps. For example, are our users using Siri search right? Do our users use our Today widget on iOS? Are we being used in the car as much as we think we are?