This post is produced by IronSource.
When it comes to their data, most app developers focus on the visualization layer — and with good reason. Their focus is on being able to have visibility into user behaviour in-app.
But in order to be able to visualize your data, you first have to collect and manage it, and if you want to get serious about really using your data to drive further app success across every area, you need to start paying attention to how that data goes from your app to whatever data warehouse you choose.
How do you collect the data? How do you handle spikes in traffic? What amount can your infrastructure handle in real time? What happens if the flow of data is interrupted? Do you have backups setup? Can you fix bad logs without breaking other things?
When it comes to data flow management, app developers tend to have a ‘set it and forget it’ attitude. As long as it’s working, they don’t want to worry about it. But while it may feel like a luxury, strong data management is actually fundamental for your app’s long-term health.
What is data flow management?
As the name suggests, data flow management refers to the movement and transfer of data from the ‘client’ or system (in this case, your app), through a data pipeline to a data storage warehouse (for example, Amazon Redshift). Data tools like visualization and analytics are then layered on top of this infrastructure, enabling you to more easily access the insights your data reveals.
Why does It matter?
If you’re developing an app that sends live updates, generates personalized experiences, or has other data-intensive demands, then it goes without saying that you depend on your data moving with precision from your app into the database.
Having control over your data flow is also important because it allows you to gain truly granular insight into your app and your users. What you see in your visualization dashboard is just an abstraction of this data. If you want to truly understand user behavior on a granular level, it’s critical to have access to all of your data all of the time.
Being able to understand exactly how many rewarded video ads it takes before a non-paying user becomes a paying user, or when a level in a game becomes too hard and users fall off, or even to predict the LTV of a user or when they are likely to uninstall your app, is vital information which can have a far-reaching impact on the success of your app.
What are your options?
When creating the backend for an app, most developers start off using free solutions for managing the flow of their data events. In fact, data management often comes included in free ‘end-to-end’ solutions that also store your data in their database and provide a dashboard where you can see some basic information about user behavior. For apps with scaling data needs, however, free solutions are often insufficient for dealing with more than a limited number of events.
At this point, app developers have two options: a paid end-to-end solution, or separate third party solutions for each of the three critical data layers (collection, insertion, visualization). While paid end-to-end solutions can be an excellent choice for some (cash-laden) enterprises, small- and medium-sized app operations are better served with separate third-party solutions.
Simply put, third-party solutions are cheaper and more practical than developing on your own. In a perfect world, you would be able to build data infrastructure specific to your operation. In fact, many large technology companies do this.
But this simply isn’t realistic for the vast majority of app developers. Building a unique data flow solution requires an experienced team of developers with a lot of time on their hands. Until this day comes, third-party solutions make a lot more sense.
End-to-end data management can save you a lot of headache, offering a comprehensive solution and enterprise-grade reliability to make your life easier. The downside of these solutions is that they prevent you from getting the control you need to query your data when you want, and how you want. In short, without being able to get on-demand access to your raw or log data, you will ultimately lack the ability to get granular insight from your data, and may also end up lacking the insight your competitors probably have.
The challenge of going independent is sourcing different solutions for each layer of your data infrastructure — and then ensuring that they can all interface as needed. On the upside, you will be able to source best-of-breed solutions for each of those levels — combining/incorporating between different service providers — as opposed to relying on one provider for every step. A further advantage is the pinpoint control you will have over your raw data, giving you the access you need to deeply understand how your users are interacting with your app and how you can improve the experience.
What you want to avoid are solutions that own your data, give you few customization options, or don’t give you granular vision that will limit your ability to leverage the power and intelligence of your data in the long run. So, not sure which solution is best for you or what your app’s needs will be in the future? Let flexibility be the determining factor.
Shimon Tolts is General Manager, Data Solutions at ironSource.
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