Watson Search and Suggest
Our team was tasked with concepting a future state of one of the key tools within the IBM Watson Data Platform. GM and Chief Business Officer, Derek Schoettle wanted to change the way people perceive data analytics and make it easier for our users to search and locate specific data within their catalog.
With a three week deadline, our team reviewed feedback from sponsor users, conducted three workshops, developed a point of view around design principals and crafted UX wires and Hi-Fi visuals for this blue-sky project.
Behind the scenes
We started by changing our thinking about information consumption. With Catalog being a technical tool, we took a look at how other consumer facing products allow people to search and find what they are looking for. It was all about the ease and delight of the experience.
A list of products included:
Airbnb, Amazon, Amazon Prime Video, Apple Music, Google, Google Trends, Hostel World, Hulu, Netflix, Quora, Sound Cloud, Spotify
Each team member was tasked with creating a storyboard for three features gathered from the previous workshop.
Features we gravitated toward:
• Refined search
• Human centered browse
• Users vet content
• Recommendations based on network
• Credible profiles
• Contextual ecommendations
• Search always comes first
• Use progressive disclosure
• Users are not shown all assets, ever
• Provide a curated browse (by system, social, user)
• Social is key
• Every user has a profile
• Visually differentiate types of content to user
• Projects are separate from catalog
• Use tags and collections not categories