Application Analytics

What is Application Analytics?
To assess efficiency and success, application analytics track the performance of online, mobile, and desktop apps. As the software release and development, the paradigm has altered, measuring how effectively apps work has become increasingly vital in order to continuously enhance and fine-tune them. On the backend and frontend of the application stack, web and mobile application analytics track the number of metrics in real-time. Today’s mobile and web application analytics may track information like the number of installs, how long and how frequently people use the app, and what devices and operating systems they use to access it.
Furthermore, application analytics may measure how well an app is operating on the user side, including any bugs, problematic portions, and whether or not users are pleased with the app. All these data points enable engineers to make quick judgments on enhancements and repairs, resulting in a faster update and release cycle. In general, application analytics are intended to extend the lifespan of an application while also ensuring that its income sources stay stable. Understanding even the most detailed information may make a difference in apps that compete with a huge number of others.

Benefits of using Application Analytics
The following are some of the benefits of application analytics:
Contextualized analytics – Gather and evaluate information in every situation.
Codeless Analytics – Capture data from an application without having to write any additional code.
Real-time Insights — Analyze flowing data in real-time.
Log analytics – Log files may be readily evaluated.
Big data capability – Manages the demands of large data centers.

Insights provided by Application Analytics
• Request and failure rates – Find out which sites are the most popular and effective. Find out where users are and when they are active.
• Response time – Determine possible resourcing difficulties by comparing response times and failure rates to request rates.
• Dependency rates – Determine if slowdowns are caused by external services.
• Exceptions – View and analyze server and browser exception reports as well as aggregated data.
• Page views and load performance – as reported by users’ browsers
• Counts — both for users and for sessions.
• Diagnostics for hosts, including Docker and Azure
• Diagnostic trace logs – Allows for the connection of trace events with application requests.
• Custom metrics – Keep track of specific business events and important milestones.