How to use analytics to verify successful software launch

Analysis is one of the most overlooked aspects of software launch. Follow this guide for the next app release so that stakeholders can drive future development from a data-based standpoint.

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When launching a software application in your business, analytics needs to be part of your strategic plan from the beginning. Work closely with developers, product owners, and customers to determine what the minimum executable product consists of, discuss with business owners, and key performance indicators that need to be measurable on the first day. You need to decide. At the very least, the analysis needs to answer two questions. Who are the users? What are the users doing?

For example, if your business knows that 90% of users are using Android devices and are getting through Facebook, there is data to answer the users who are using the app and where to market based on the data. You can decide whether to do it. Do you need to double and grow your Android user base, or do you need to look for other acquisition channels to grow your iOS base?

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Powerful minimal executable analysis gives you the data you need to drive your application after release. If you’re building a digital product or service and haven’t yet considered the type of analytics you need to launch, this guide will help.

Here is a good starting point for the data you want to capture for a feasible minimal analytical implementation.

Data to capture User data What are these users doing?
Geography X
Demographics X
Times of Day X
Device type X
operating system X
Acquisition channel X X
Number of downloads X
Active daily users X
engagement X
Unique visit X
Revenue per user X
conversion X

Which technical tools should I use for this analytical strategy?

One analytics tool doesn’t give you a 360-degree view of your application in the field and the operational flexibility you need after release. This is especially true in the area of ​​mobile apps where changes need to go through the process of submitting and approving the store. A good approach is to combine several tools across the categories of analytics, abstraction, and quality of service to make sure everything you need is built into your app.


Analysis packages are a core component for aggregating and reporting user data. When trying to select an analysis package, there are many factors to choose the right package. One of the key factors is to ensure that your analytics solution is tailored to your application platform. Also, there may be multiple solutions to evaluate within a single vendor’s product.

Two of the most popular analysis packages are Google Analytics for Firebase When Google Analytics 4..

Google Analytics for Firebase

After making a few misleading renamings, Google Analytics for Firebase is the Google solution for mobile app analytics. We continue to use Google Analytics as our core, but it has been published as an event-based model and is more consistent with how we use mobile applications. Google Analytics for Firebase is free and unlimited, but there are no service level agreements.

Google Analytics 4

Formerly known as Google Analytics, Google Analytics 4 maintains the traditional approach to analytics: page views. There are fairly robust free tiers and paid plans for advanced use cases.


After your application is released and you start collecting analyzes, you may want to collect additional data points or format the data differently in order to draw higher correlations. That’s where the tag management system comes in. TMS allows you to quickly update measurement codes and related code fragments, usually from the web console. In many cases, after the initial implementation, you can make these updates without having to update the live app code in the field.

If you have never used TMS before, you should consider the following vendors: Google, Adobe When Mix panel.. One of the interesting aspects of TMS is that it is mostly independent of the analytical solution. For example, you can use Google’s Tag Manager in Adobe analytics and vice versa.

Quality of service

Even with TMS and a robust analytics implementation, we find that these data points are different from the data points that engineering teams need to diagnose the problems they face. This allows us to measure quality of service, the third tool in the MVA toolbag.

The flavors of these QOS tools exist on both mobile and web, as the basic technical differences in these applications require different approaches. For mobile, popular QOS solutions include: Crashlytics, Insta bug When Raygun.. On the web, you should consider tools such as: Air brake When Uptrend..

The general data we collect is:

  • Crash dump (stack trace).
  • Intelligent grouping (quantify unique crashes, not multiple instances of the same crash).
  • Custom data (developer-inserted bread crumbs).
  • Device state (hardware, operating system, and environment qualifiers).

What user privacy and data usage details do I need to know?

Ultimately, the purpose of collecting analytics is to provide the best possible user experience, but privacy and data usage are important considerations. On iOS devices, you now need to ask users for permission to track you across apps and websites owned by other companies. Android and the web aren’t too far behind, so be sure to read and fully understand the platform’s privacy requirements and how they apply to the analytics they collect.

What are the benefits of doing software analysis?

Successful software products need to adapt to the ever-changing market. A well-planned MVA approach creates a direct line between you and your customers and greatly improves the launch of your application. There are analytics SDK reports on user behavior, tag managers that change what they collect in real time, and QOS metrics that developers need to troubleshoot user service interruptions. This 360-degree view provides the data you need to hit your app. How to use analytics to verify successful software launch

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