App Annie, which offers app store analytics, is announcing new features and capabilities for mobile app publishers and developers this morning. The company is adding more ad network data and analytics; it’s also offering new tools to help boost App Store Optimization (ASO).
Both of these are directed toward what might be called app-user acquisition optimization: one being paid and the other organic. Below are company provided screens showing the ASO and paid dashboards:
The company’s ASO tools will reveal keywords and queries used for app discovery. It’s also designed to help developers improve metadata for improved ranking and discoverability. There are competitive metrics as well:
Our new ASO tools will give you access to the crucial metrics needed to maximize your organic search traffic. When you only have a Twitter status worth of characters to work with to position your app on search rankings, every character counts. Our new tool will show you which apps are ranking for the leading search terms, reveal competitors on terms you’re already using, and much more.
The expanded ad network analytics will help developers better determine which networks perform at the lowest cost per user. The company has now incorporated more than 20 mobile networks into its platform, including iAd, AdMob, MdotM, AdColony, InMobi, RevMob, AppLovin, AppLift, Taptica, Everyplay GameAds, among others.
Facebook is not yet there. Nor is Twitter, which recently announced app install ads.
App Annie isn’t an advertising platform or mediator. The data are purely for analytics purposes. Publishers need to execute their ad buys themselves. However they can track impressions, CTR and installs, as well as “eCPI” and similar metrics.
Most of App Annie’s tools and capabilities are free.
According to Nielsen, mobile users spend almost 90 percent of their time in apps vs. on the mobile web. However a limited number of “top apps” dominate, and app discovery remains a major challenge. In addition, a large percentage of apps, once downloaded, are infrequently used and/or ultimately abandoned.
Having a better understanding of app-store user behavior as well as greater visibility on app-install ad effectiveness is of increasing importance to publishers and developers.