Working closing with a motion designer and writer, I defined and built out the UI and patterns you see below. I also worked with several TPM's and PM's to shepard and sell overall vision and corner cases between research. This was an attempt to create a simple yet scalable framework to handle more wait time data as Google's machine learning improved and local listing info becomes increasingly available.
We learned that a new graph and visual take on it was not only too much work, but didn't align with data viz across the evolving Google ecosystem. Words were powerful and also misleading depending on how we articulated the wait of each place. The sensitivity of this info was also to be considered, as well as how it played a role in decision making between parsing how busy a place was at that very time vs another day of the week. After rounds of research, we also found new ways to allow users to traverse between times as well as focus on the worst case scenario at a glance.