Why you need native app analytics.

Mobile native app usage has increased significantly since the pandemic started, but the wide-spread adoption of native app analytics tools and platforms has lagged behind. 

Today, companies need to understand what their customers are doing across all digital channels, not just websites. In fact, many companies now re-direct customers from their mobile websites to the app store. 

Here’s a look at how native app analytics are different from web analytics, and what you should be looking for in your mobile app analytics platform. 

How are native app analytics unique?

Building and developing native apps require a different set of skills, so it’s not surprising that digital teams need to take a different approach to analytics. 

Screens vs. pages.

Unlike websites, which are composed of static web pages, native apps have screens. This means analytics platforms should focus on how users interact with various screens. This is why heatmaps are especially important for mobile native app analytics.

Cookies vs. user IDs.

Websites have predominantly tracked users with third-party cookies. Native app analytics take advantage of the personal nature of smartphones. People tend to have personalized logins, which means that it’s easier to keep track of how users interact with your native app over time. 

Shorter, more frequent sessions.

Mobile apps tend to have a shorter session timeout than webpages. However, people access mobile apps more often. It’s usually more convenient to use your phone than reach for your desktop or laptop. 

Measuring offline capabilities.

Many apps have some offline capabilities. To understand how users interact when offline, some native app analytics tools allow you to record what happens on the native app when there is no internet connection. This way, you can upload data to a collection server when users log back into the mobile network. 

Segmentation.

There’s a wide range of devices for both iOS and Android phones, which is why cohort analysis is important. Between each of those camps, native apps are constantly releasing new versions and pushing fresh updates. With cohort analysis, you can break down the experience by device type, operating system, and version.

Cohort analysis.

After breaking down users into specific segments (e.g., Android users vs. iPhone users), native app analytics platforms can then analyze how many people are impacted by the same or similar error. This can help teams discover patterns, and address the issues that are most pressing for large numbers of users. 

Why Quantum Metric for mobile app analytics.

Historically, many companies have selected one vendor for web analytics, another for native app analytics. 

With Quantum Metric, however, enterprises can see how user behavior changes from channel to channel. This way, enterprises can compare how desktop users and mobile users navigate through their digital products.

After deploying Quantum Metric’s SDK (software development kit), you will have access to out-of-the-box metrics with minimal coding. 

In terms of mobile app analytics, Quantum Metric offers anomaly detection, real-time analytics, behavior analytics that detect rage taps and other frustration, and more. The platform helps teams quantify the impact of each action, as well as how much a technical error, app crash, or API failure is costing an organization.

Check out our native app analytics product tour to learn why retailers, financial service institutions, airlines, QSRs, telecom companies, and other industries are using Quantum Metric to improve their mobile apps.