We worked alongside SAP to pioneer new ways of creating software that could learn how users work best. Not only learn but also solve issues related to productivity through tailored, personalized experiences.
Our research revealed that notifications distract workers. They take people away from the task at hand and require people to regain focus. Even these small instances add up to a dramatic loss in daily workforce productivity.
So we looked at how particular notifications related to specific user groups – end users, business users, and developers. We discovered that the usefulness of a notification was determined by the complex relationship between what the user is doing and what the notification was actually about.
To create a product for individualized notifications, we needed to use Artificial Intelligence and Machine Learning techniques. Our Machine Learning model captured data, which we then used to determine each user’s response to specific types of notifications.
After building the ML model, we were able to predict an individual user’s behavior when receiving different notifications and then use the same model to prioritize the notifications that the user found useful.