Though the number of applications is increasing, the number of successful applications remains limited. Application analytics solutions capture and analyze application metrics such as usage patterns. Insights from application analytics enable companies to continuously improve their cloud, desktop and mobile applications. Benchmarking and tracking a relevant set of metrics which we provide below enables companies to have an edge in application analytics

What is application analytics?

Application analytics is the collection of data, real-time analysis and reporting of application usage patterns. It covers analytics in mobile, desktop, and other device applications. It can be used to gain insights into IT operations, customer experience and business outcomes.

With these insights, businesses can make improvements in their product, marketing, and overall profitability. For example, by monitoring the performance and analyzing crash reports, companies can quickly fix bugs.

Why is application analytics important now?

Number of applications is increasing and there will be over 500 million apps and services by 2023 according to IDC’s estimations. Due to the rise of applications, advanced analytics is a necessary tool for companies to manage these growing numbers of applications effectively. Even Apple Store alone has ~2.5m apps as of 2018:

Source: Statista

What are application analytics use cases?

Continuous monitoring – Dashboards

Application analytics solutions track key performance indicators(KPI) which outline how well the app is performing and keep the whole team (management and development team) on the same page.

Continuous improvement

App analytics is a fundamental part of any application life cycle. It enables 

  • improving the software with less effort by focusing on what is essential for customers. It helps product teams make data-driven decisions about user experience and design since it provides knowledge of how the application is used.
  • tracking KPIs over time to measure improvements.

What are the different types of application analytics?

Application analytics is relevant for cloud, desktop, and mobile applications.

Mobile application analytics is especially relevant, given the winner-take-all nature of the mobile application landscape. Though there are 4 million applications in the Apple AppStore, a few successful mobile apps dominate mobile usage. Though industry analysts are in general bad at making making predictions, this makes Gartner’s prediction about low rate of mobile success (they predicted 0.01%) correct. To gain an advantage, organizations have to make data-driven decisions.

What are the important KPIs for applications?

What to track is an important challenge for application developers when they start to use app analytics. Here are some essential metrics to track; they are sorted from most important to least:

  • Active Users
  • User Conversion Rate
  • Retention Rate
  • Churn Rate
  • Usage Time per Session
  • Sessions per User
  • User Lifetime Value (LTV)
  • First-time User Drop-off Points
  • Usage Time per Session
  • Exit Rates from Funnels
  • Referral Codes and Their Success Rates

What are the challenges associated with application analytics?

Application metrics in isolation may not be informative. Companies can resolve this by comparing their KPIs against benchmarks. Here is an example of Quettra’s research about average retention day per user. 

retention_graph_average
Source: Quettra

There are numerous companies publishing public research and information on different mobile app’s metrics that companies can leverage. Some major providers are: App Annie, Appfigures, newzoo, Nielsen and Priori Data.

What are the tools used in application analytics?

There are application analytics solution specific to desktop, cloud or mobile applications. We deep-dived into mobile analytics tools as an example.

Mobile application analytics tools

App analytics tools are divided into three categories:

  1. In-App Analytics: In-app tools reveal patterns of user behavior within the app. Session recordings, navigation paths, touch heatmaps, and conversion funnels are tools to see patterns of user behavior.
  2. Performance and Crash Data: These tools provide data such as load times, crash reports, and session details. With performance and crash data tools, developers can track crash and performance data and fix it quickly.
  3. Marketing and Install Tools: Unlike other categories, marketing and install tools focus on data about new customers. Some of these data metrics are impressions, clicks, installs, and conversion rates.

Here is a list of the important mobile app analytics tools:

  • Google Analytics
  • Apple Analytics
  • Flurry
  • Fabric
  • Appsee
  • Localytics
  • Count.ly
  • Geckoboard
  • Firebase
  • Mixpanel
  • AppDynamics
  • UXCam
  • Adjust
  • AskingPoint
  • AppsFlyer
  • Buildfire
  • Leanplum
  • App Annie
  • Apptopia
  • Kumulos
  • Apptica
  • Trafficguard
  • Smartlook
  • Singular
  • Tune
  • Kochava
  • AppFigures
  • LeanPlum
  • GameAnalytics
  • Amplitude
  • Apptimize

We’ve written a few articles about analytics before, feel free to check them out:

What is Analytics?

AI in analytics

Security Analytics in Age of AI: In-depth Guide 

Exploring Analytics & AI

Workforce Analytics: Guide for Businesses

If you still have questions about how Application Analytics can influence your organization and how you can get started, we can help:

Let us find the right vendor for your business

Sources:

Mobile metrics: Ymedialabs

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