⋅Understanding the User⋅
In order to observe and learn how social strategists handle scheduling and sourcing content, I conducted a design exercise with 4 users who represented distinct use cases (one who was in charge of a big Facebook page, another who owned multiple small pages, another who lead “lifestyle” brands, and one from BuzzFeed News).
We did a whiteboard exercise where each person mock-scheduled their Facebook page based on a set of scenarios that I threw at them.
We learned that sourcing content to put on their pages was time-consuming and often stressful, because many strategists are required to publish a set amount of content per day, regardless of how much new content is read to publish. Whether a day was slow or filled with new content was impossible to predict, and often left strategists scrambling to find “evergreen” content (aka older content appropriate for re-posting) to round out the schedule.
After our user sessions, our team vision was clear: we wanted Planner to be a place where you can not only see what has been scheduled already, but also where you haven’t scheduled. We would also provide content recommendations directly within the tool to help alleviate the pain of sourcing.
After initial stakeholder interviews and user sessions, the requirements for the project started to take shape:
- Show users when content is scheduled to publish to social pages
- Show users when there is nothing scheduled
- To help users fill out their schedule, show users a queue of recommended content, where they can schedule content directly from this view
An early design exploring a timeline-style view
Some early designs exploring a calendar-style view at different densities: 7-day vs. 5-day, 4-day, with thumbnails or just text
⋅Recommendation Queue Explorations⋅
Paper prototyping with users to get a sense of what they might expect from a recommendation queue, how it might work, and what data is important to see.
Left: Early prototypes to refine the drag-and-drop animation. Right: An early prototype shown to users to get a sense if the order of content and information in the cards were on the right track.
Designing the recommendation queue