AI-Driven Platform

Financial Times

Nikkei Inc.’s acquisition of the UK-based FT Group created one of the world’s largest business media conglomerates. It was a bold and unprecedented move, and it sought to respond to the rapidly changing media and technology landscape.

All information in this case study is my own and does not necessarily reflect the views of Financial Times

Project Objective

To deliver a simplified and beautified data-visualisation tool that keeps customers informed and ahead of their competitors. It is aimed at a wide variety of users, including M&A bankers, corporate strategy teams, salespeople, compliance officers and is designed as a business tool that will save them both time and money.

We set out to build and sustain a design system followed by a visual language and foundational component library to support developers with documentation available to internal and external partners.

Team & Role

I joined this project in its early stages to co-direct the visual design by creating a design language and coming up with a solid design system to bridge the gap between development and design. The team consisted of 1 Product Owner, 1 Product Manager, 1 UX Designer and 4 Full-stack developers and 1 Tester, and it was split into 2 locations: London and Tokyo.

Stakeholder interviews

The project began over a series of meetings to discuss roadmap assumptions, how success would be measured and business objectives. During the week, we met with key stakeholders from London and Tokyo to explore:

  1. Customer Segments & Personas: Their demographics, backgrounds and motivations.
  2. Our Design Thinking process and tools to collaborate and work with Developers and Product owners.

We interviewed 11 senior team members to answer key questions:

  1. Who will use ScoutAsia?
  2. What they will use the tool for?
  3. What are the different use cases for this user?

Key takeaways

After digesting the learnings from the stakeholder’s interview, we created two proto-persona describing the target users and audience of ScoutAsia based on the assumptions of our stakeholders. Creating these two proto-personas allowed our product team to build a shared understanding of our potential users and to begin designing and building immediately without getting overly bogged down with the details of user behaviour.

By creating these two proto-personas, we also had a better understanding of the users we should recruit for user research and usability testing. We identified the following key themes and differences for our personas:

Primary Persona

  • Comprehensive data
  • Deep dive
  • Task completion
  • Impossible deadlines
  • Timely explanations
  • Compiling detail
Primary Persona: Jennifer Teo

Secondary Persona

  • Steers and hunches
  • Macro view/big picture
  • Forming a strategy
  • Setting timelines
  • First to know
  • Summaries
Secondary Persona: Peter Bauer

Empathising with our end users

The team travelled to Tokyo, Japan in order to engage with stakeholders from Nikkei. We took the opportunity to facilitate 1:1 sessions with potential customers in Asia. Common patterns learned from the interviews provided strong rationale towards design choices on tools like the “Connections Map”, “Company Search” and “Targets List”.

Some of the outcomes based on the user interviews: Users demonstrated to be more
interested in a feature where they could see all related connections from a company.

Key learnings

A common usage scenario learned from the interviews was that most customers would likely be in a rush or commuting in a train most of the time while checking for relevant news about companies they follow and discovering new companies mentioned in the news. They would feel more comfortable using a desktop to perform advanced tasks, like accessing a company’s connections map and a company’s market comparison chart.

Design, Test, Ideate

After establishing a strong understanding of the customer base, features and business objectives, we began to build the experience and the design process started. My personal deliverables were the Design Language followed by “Company Search” and “Targets List”. The iterations of the design concept can be found below.

First concept based on the interviews with key team members
The second design concept is based on the learnings and feedback from the user research
The third and final design concept was created after two iterations followed by two user testing sessions, having all the necessary and essential features that customers need in order to perform their daily tasks while using the product.

Key learnings

Interviewing potential customers and data scientists from our team while conducting competitive research on data-visualisation products helped us to organise complex data best practices. The learnings led us to our design concept, scenarios, and mockups.

Prioritising System Parts

Working closely with our in-house development team, we set the goal for V1.0 of the design system to build the foundation by creating a compressive, scalable visual language and build atomic components most often reused and combined to make user experiences. Our emphasis in this process was to emphasize displays and data collection through normalization of form controls and standardized UX patterns and best practices.

The product

ScoutAsia consolidates data from companies into one central location. It allows customers to:

  1. Visualise news from companies of interest
  2. Visualise complex connections map
  3. Save companies to a custom target list and receive news and notifications
  4. View and download standard reports and charts
Page overview containing news and notifications from companies the customer tracks, and general news from companies around Asia.
Search results page: It displays companies and their relevant news. The customer can select and add them to their targets list in order to receive notifications about any activity from the company.
One of the key features offered by the product. The connections map gives the customer a full view of the company followed by their parents and child companies.

The beta product was launched in Q1 2018 and is iterating through a series of interviews and usability testing with end-users in Asia.