Analytics is one of the most overlooked aspects of software launch. Follow this guide for your next app launch so stakeholders can drive future growth from a data-informed location.
When your business launches a software application, analytics should be part of strategic planning from the outset. You will need to work closely with developers, product owners, and customers to determine what your minimum viable product includes, and work with your business owner to decide. key performance metrics to measure on day one. At a minimum, your analytics should answer two questions: Who are your users and what are they doing?
For example, if your business knows that 90% of your users are on Android devices and get it through Facebook, then you have data that answers who uses your app and can make informed decisions. based on location data. Should you duplicate and expand your Android user base, or should you look for other conversion channels for iOS platform development?
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A powerful minimal feasibility analysis will give you the data you need to drive your app post launch. If you’re building a digital product or service and still haven’t considered what kind of analytics you need to have available to launch, this guide can be helpful.
Here are good starting points about what data to collect for most minimally viable analysis implementations.
| Data to capture | User data | What are these users doing? |
|---|---|---|
| Geography | X | |
| Demographic | X | |
| Time of day | X | |
| type of device | X | |
| Operating system | X | |
| Conversion channel | X | X |
| Number of downloads | X | |
| Daily active users | X | |
| Engagement | X | |
| Unique hits | X | |
| Revenue per user | X | |
| Convert | X |
What tech tools should you use with this analysis strategy?
An analytics tool won’t give you a 360-degree view of your application in the field and the operational flexibility you’ll need after launch; this is especially true in the mobile app space, where changes need to go through in-store approval and submission. A good approach is to combine several tools across the analytics, abstraction, and quality of service categories to ensure you have everything you need into your application.
analysis
The analytics package is the core component for aggregating and reporting on your user data. When you are trying to choose an analytics package, there are many factors that go into choosing the right package. An important factor is making sure the analytics solution is tailored to your application platform. In addition, in the service of a single provider, there may be multiple solutions to evaluate.
Two of the most popular analytics packages are Google Analytics for Firebase and Google Analytics 4.
Google Analytics for Firebase
After many rounds of confusing name changes, Google Analytics for Firebase is Google’s solution for mobile app analytics. It still uses Google Analytics at its core, but it’s exposed as an event-driven model, which is more in line with how people use the mobile app. Google Analytics for Firebase is free with unlimited usage, but no service level agreement.
Google Analytics 4
Google Analytics 4, formerly known as Google Analytics, maintains the classic approach to analytics i.e. page views. It has a pretty robust free tier as well as paid plans for advanced use cases.
Abstract
Once the app is live and you start collecting analytics, you may wish you had collected more data points or formatted the data in a different way to derive more advanced correlations. That’s where the card management system comes into play. TMS allows you to quickly update your measurement code and related snippets, usually from a web console. In many cases, after the first rollout, these updates can be made without requiring a code update for your live app in the field.
If you have never used TMS before, there are many providers to consider including Google, Adobe and Mixpanel. One interesting aspect of TMS is that most are independent of your analytics solution, such as allowing the use of Google Tag Manager with Adobe analytics and vice versa.
Service quality
Even with TMS and a robust analytics implementation, you’ll find these data points don’t match the data points your engineering team needs to diagnose problems your users are experiencing. That brings us to the third tool in your MVA tool bag: Measure Quality of Service.
Flavors of these QOS tools exist for both mobile and web, as the fundamental technical differences in these applications require a different approach. For mobile devices, popular QOS solutions include Crashlytics, Instagram and Raygun. On the web, you’ll want to look at tools like Air brake and Trends.
Common data to collect include:
- Crash dump (stack trace).
- Smart clustering (quantifies a single incident instead of multiple instances of the same incident).
- Custom data (developers inserted path).
- Device state (hardware, operating system and environment modifier).
Which user privacy and data usage details do you need to know?
While the ultimate aim of collecting analytics should be to provide the best possible user experience, privacy and data use are important considerations. On iOS devices, you are now asked for user permission to track them on 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 privacy requirements for your platform and how it applies to the analytics you’re collecting.
What are the benefits of analyzing your software?
Successful software products must adapt to a constantly changing market. A well-planned MVA approach will create a direct line between you and the customer, while greatly improving your application launch. You’ll have the User Behavior Reporting Analytics SDK, a tag manager to make real-time changes to what you’re collecting, and the QOS metrics your developers will love required to fix any user service disruptions. This 360-degree view will provide the data you need to make your app famous.
