The use of a radial interface was pioneered in 2012 and is making a comeback in the past year especially with wearable tech. One advantage of using circles in a touch interface is the ability to have more points adjacent to your finger at the same distance when touching the screen. With squares, the path to the next item would be variable and there would be a smaller limit to the number of items you could fit around a touch point. On smaller displays, circles can be scaled easily to reflect popularity or usage and can be organically tessellated to fit more items on the screen. It seems this circular UI pattern will pop up more in the future for small displays and touch interfaces, giving interaction designers more flexibility to reflect natural movement in their digital experiences.
It seems that this also lends to the extremely desired and useful ‘one-hand operation’. Apple, for example, uses this radial interface in their Apple Watch products but they also included one hand operation in the iPhone 6 interface. The new Reachability feature provides access to all of the top-of-the-screen elements that might otherwise require a second hand, and iOS8’s new thumb-friendly recording interface for Messages shows that same Path-like consideration for our favorite digits and their natural range of motion. Clearly, Apple has decided that making devices accessible with one hand is crucial to winning the wearable market.
Modern business models show that making things quicker often yields positive results. Apple has introduced a suite of new features intended to make our life easier, including a more robust system of Contextual Responses within the new Apple Watch OS, which will provide “quick” responses for iMessages based on the context of the ongoing conversation. This is a brilliant idea. But can it go beyond simple text processing to providing information to the user based on what we think they might like. I would really love to see how this can disrupt travel – especially when combined with GPS and iBeacon technology.
Imagine: It’s Tuesday morning, and you just woke up. Based on your calendar, Apple knows you have a meeting at 9 a.m. but most days you get to work at 10 a.m. Usually you get a coffee on your way to work at Starbucks around the corner, and Apple knows this by passively monitoring your GPS positions over time. So how can Apple make your life easier? What if your Apple Watch could take this data and calculate the best time to leave based on your average walking speed, anticipating a coffee stop and how long it usually takes you to get to your office?
Or if you’re going to visit a client in Windsor and you’re traveling from London. You have a train ticket purchased on South West Trains from London Waterloo to Windsor and Eton Central station. Based on the client contact information in Contacts (or perhaps with integration into Salesforce) Apple knows that you’ll have a 53 minute train ride, and a 10 minute walk to the client office. It also knows that you’ll pass the Starbucks at 18 Thames Street. It suggests an upgrade on the train so you can work with Wi-Fi, walking directions that will have you pass the coffee shop and even prompt you when you arrive to Windsor and Eton Central station if you’d like to pre-order your favorite beverage.
This concept isn’t new. Predictive Analytics has been under development, somewhat publicly, for the past few years, and has been implemented with mixed success in everything from the Google Now app to Netflix’s recommendation engine.
Implementing predictive analytics in your own designs can be as simple as considering how to refer users to the next step in a process, or as complex as detailed behavioral analysis algorithms. Tools such as KISSmetrics and Google Universal Analytics can be employed as a basic data store to monitor usage. As the field grows, interaction designers should keep an eye out for new off-the-shelf platforms for implementing detailed predictive analytics in their own applications.