Wejo Studio

Wejo Studio is a SaaS platform that distills vast amounts of connected vehicle data from across the US road network and makes it accessible to users via a suite of products. I worked on this greenfield project with the Wejo Product team, initially to define user requirements, develop an early prototype to set the direction and to prove the concept to key internal stakeholders. I then went on to design the UX and UI of the first production version and built a team of designers to further develop the platform experience.

There were two main elements of the first version of Wejo Studio - the structure of the platform itself and the first product available within it, Intersection Performance.

As part of the structure and architecture of Wejo Studio as a portal, we included single sign-on (SSO) and two-factor authentication (2FA) for sign-in, as described in the user flow and wireframes below. This was the very first user flow created for Wejo Studio and informed not only the user journey for accessing the portal, but also helped to inform the basics of how the platform would be built from an engineering perspective, including the decision to develop it using the Material UI React framework.

Intersection Performance is a product which enables traffic managers to see real-time and historic vehicle behaviour at intersections across the entire United States road network, visualising this data in a clear and easily-accessible way. This was the first product of its kind, literally replacing manual road-side counts that are compiled in to reports.

Our early work on this product was informed by Wejo Business Analyst interviews with traffic managers to validate our early decisions and find gaps in our knowledge and understanding. From these interviews, we identified the key tasks that traffic managers carry out, how they do it and what they were most interested in to be able to do their job. Working with the BA and product teams, I developed user flows and wireframes to discover how these tasks would manifest as a digital experience within the platform structure. I then created prototypes which we tested internally and with the traffic managers in a regular cycle of iteration.

We faced a unique question of how live data of a traffic intersection should be visualised. The aim was to visualise traffic intersections in a clear, consistent and intuitive manner, no matter the complexity of the intersection and traffic movement (from simple suburban junctions to major interchanges, freeway merging and U-turns). It was as much a challenge for the engineering team as it was for design, with AI and machine learning used to define exit and entry points.

Working within these technical confines, I explored many visual solutions to find a simple, elegant, uniform solution which could be applied to any intersection across the US road network. This exploration involved hand-drawing over random intersections from Google Maps and inspiration from HUD graphics from sat-nav systems.