After more than two years in the mobile and web space, it is about time to add support for Unity to our data acquisition environment. We have recently received an increasing number of requests for a Unity integration so that we believe, it is now the perfect time to support one of the industry-leading platforms for game development.

One recent customer request came during an EU research project where is part of the consortium. The ENVISAGE project aims at bringing successful gamification approaches to the educational learning space. In a first step, this also includes making analytics accessible to teachers in school environments. The overall objective is to personalize learning, improve learner’s performance, and help teachers to get important insights.

Virtual Labs for Educational Learning

Individualizing user experience, analyzing performance improvements, and obtaining behavioral insights. Does this sound familiar to you? Besides e-commerce platforms, mobile games, or lifestyle apps, educational software benefits from analytics as well. One of our first task was to track the learner’s behavior in the Wind Energy Lab. This lab is a 3D-simulation which teaches students how wind and turbines interact to generate energy.

The ENVISAGE Wind Energy Lab now tracks data with the help of's Unity SDK.
ENVISAGE – Wind Energy Lab

In this lab, typical events are “start simulation” or “stop simulation”, certain interaction points like “add turbine”, and a configurational part. The Unity scene construction is very similar to mobile app development with activities. A user or student explores its path through the Unity app. We want to gather this behavioral information and collect it for (predictive) analytics. At the end, Unity allows building apps for different platforms. So there is not much difference to native mobile app development. Unity provides a very nice in-house analytics suite. However, for our purposes, we need a more flexible and elaborate tracking in place.

Why Not Just Use Unity Analytics?

Unity analytics is a classic example of descriptive analytics. Like Google Analytics, it serves its purpose well but in many settings, it is necessary to go beyond that level of analytics to compete with the state of the art automation and personalization. There are two main reasons why we created our own plugin for Unity. First, our preferred integration is Segment and we love how easy Segments integrates into all kinds of ecosystems. The service is well structured and their tracking specifications are very helpful. Unfortunately, Segment does not offer a plugin for Unity.

The second reason is due to some technical limitations. We are working hard on dynamic difficulty adjustment and personalized recommendations for the perfect strategy in a game or learning application. For this purpose, we envision a bidirectional communication between our backend and our customer’s app or game. Depending on the customer, our backend can evaluate different strategies and our API can then deliver individualized strategies for individual users or segments. Therefore, a plugin that communicates directly with our API is much more interesting than a piece of software that only sends data to a tracking interface. Our customers add the Unity plugin, start the tracking, our algorithms receive the data, enrich the data, and send actionable results back to the end user, i.e., the learner or player. This will ultimately lead to the next level of individualization where the degree of difficulty or the content will suite each user perfectly. Every user — or player — should have the optimized user experience based on his or her behavior. This helps that nobody gets bored, or frustrated on the other side of the spectrum. The first steps towards this vision is our developer friendly Unity SDK and its smple integration is depicted in the image below:

Adding the SDK to your Unity app is dead simple and only takes a few minutes.
The SDK integration is dead simple and the basic setup takes just about 2 minutes.

What’s next?

As described, our main purpose for developing and maintaining this SDK for Unity is making our machine learning algorithms available for Unity developers and game owners. One big opportunity for machine learning in the gaming industry is personalizing the gamer’s experience. We are convinced that a machine-aided game flow control helps you to assist improving user retention and increase in game purchases. This certainly does not only hold for the game industry but also the educational learning space.

To learn more what offers for developers of games, please visit If you are working in the educational learning space, we have also summarized some information for you: And lastly, don’t forget to follow us on Twitter.