Using research insights from 1-1 interviews with twelve members of the Moleskine community, I developed three use cases to guide the design flows.
The "super creative" is interested in reaching out to the community and getting more exposure. He's an artist who likes a specific anime style and is pleasantly surprised by the large body of work from artists similar to himself in the community.
Watson refines his feed according to the things he likes - the more it is used by liking, sharing and viewing images, the more accurate the results.
He finds an artist with very similar drawings. They get in touch and decide to start a Meetup with other artists based on their shared interest in anime.
The creative professional decides to use M+ to take her work in a new direction. She uploads her work-in-progress through the menu bar app directly to the community.
M+ showcases related images from the community and external contextual references that are linked together through a pipeline of Watson's smart API's. She finds a book that seems to be the perfect resource for her project and proceeds to purchase the book through a third party vendor.
An overview of the system from input to diagnosis. The cognitive system learns and develops "expertise" the more it is used, evaluating all possible meanings and abstracting underlying ideas and concepts to provide relevant results.