Unity Monetization Dashboard

  • Lead product designer on the Monetization portion of the dashboard.
  • UI/UX design including user flows and high fidelity mockups. Base wireframes were created by a contract designer before I joined the company
  • Prototyping in Framer to communicate abstract ideas and concepts
  • Worked with other designers across the web products in different offices. Worked with all of them to collectively create a component library
Unity’s game engine has seen a fair amount of success, becoming the engine of choice for mobile game developers. However, the company realized it is severly lacking in services that aim to aid developers further. Developers had been asking for a live operations dashboard direct from Unity and now we have the opportunity to deliver. Unity started up a Cloud Services team and an Ads team to try to tackle some of these requests. The Cloud Services and Ads team had worked in silos and had their products well under way.
When I joined the Unity Monetization team, there were no product designers and a fragmented platform. It was clear that before starting on the work the Monetization team wanted to start, the company needed to figure out how it wanted to position all of its services as one unified vision. After several weeks, the product designers on all three teams worked together to determine the information architecture and basic layouts of the pages following Material Design philosophies.
Moving forward, we agreed upon regular sync meetings amongst the team of designers to ensure we were always reviewing each others work and verifying consistency across shared components.
My job as the lead product designer for Unity Monetization, I was tasked with finding ways to provide developers with a dashboard that:
  • provides data on how much money they’ve made and from what segments
  • provides developers a way to configure Unity monetization features
  • provide a space to explore a machine learning Ads/IAP product and the data it provides
Testing a live machine learning cohort sorting idea.
Testing a live machine learning cohort sorting idea.
Example of a live activity feed.
Example of a live activity feed.
Showing how we can communicate that this is live data.
Showing how we can communicate that this is live data.
I prototyped several ideas using Framer to help communicate some of the more complex ideas around machine learning, user activity, and live data. We wanted to use machine learning to identify players who would be more likely to purchase IAP and allow developers an easy way to show IAP promotions to these users where an ad would normally be.
After months of work with PMs and engineers, we were able to ship the first version of the Unity Monetization dashboard that encompassed revenue reporting and configurations for in-app purchasing. We soft-launched the tool to a select few Unity partners who were eager early adopters of our products to help us test the usage of these new features.
Through these key users, we were able to deduce additional UX and design wins that would help improve a decent "Material Design" version of the dashboard into a better experience to help surface the most crucial information when they first land on the dashboard.

There's obviously more to this story.

A lot of process went behind the creation of this project that I am unable to display in such a public manner. But if you'd like to hear more, get in touch.

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