I had just started working on an established freemium web game targeting children in the 6 - 10 year old range when, senior leadership became interested in getting more users to check their notifications page. This page was both a vector for marketing our paid subscription offers and where subscriber benefits were delivered to the players. I was personally interested in seeing if there was something we could do to meaningfully affect player engagement patterns, since many of our new features launched to relatively lacklustre engagement. While our most active cohorts always checked out the new updates, we always seemed to have significant issues with feature discover in our core users.
Read more: Directing Focus: How a Basic UI Test Shaped an Attention Framework
I was working on a large educational game targeted at young children. At the time, the developer had discovered issues with with tutorial or FTUE (First Time User Experience) completion rates and I asked if I could look more deeply into the issue. From everyone's experience at the time, this issue had been around for some time, but they didn't have good tracking of the onboarding funnel, so they couldn't see what the underlying issues were.
The way the game worked, you could explore everything quasi-freely without engaging in any educational content, but if you wanted to progress you had to engage in combat encounters, and to do anything in an encounter you needed to answer educational questions.
Read more: Educational Gaming and the Impact of Existing Knowledge
This was something I put together for the interest of colleagues at work, and I got some good feedback from it so I thought I'd share it publicly. I want to preface this with the fact that I'm neither a physician, an epidemiologist, a virologist, nor any other kind of medical expert (I don't even play one on TV!), and I don't work even tangentially in healthcare. I'm just a numbers monkey who reads the news.
I've seen a lot of people on every possible social network posting graphs of the local COVID-19 infections. Sometimes they're line graphs, sometimes they're bar charts, sometimes they're even line graphs and bar charts, but I haven't seen much in the way of model fitting. So, I thought I'd throw a couple of basic models at the data and see if they met expectations.
Read more: Modelling the NS COVID-19 Outbreak - 12 May, 2020