Financial Times

Data Dashboard

    scoutasia

    Scoutasia is a new Financial Times and Nikkei corporate data and news service that provides context on more than 600,000 Asian companies across more than 20 countries in North Asia, South Asia and ASEAN. Combining data and news on public and private companies, as well as macro trends and bespoke reports, the service provides organisations with unrivalled regional business information. The business ambition is for the product to quickly become the most respected Asia-focused service of its kind on the market.

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

    Project objective

    Deliver a new responsive data-visualisation product 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.

    Team & Role

    I was hired as a contractor in the position of Product Designer, responsible for usability and competitive research, design language, design system, UI and micro-interaction design. Working within an agile environment, the team consists of 1 Product Owner, 1 Product Manager, 1 UX/UI Designer and 1 UX Service Designer, 4 Full-stack developers and 1 Tester. The team is located across London and Tokyo.

    Project Kick-off

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

    • Customer Segments & Personas: Their demographics, backgrounds and motivations.
    • 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:

    • Who will use Scoutasia?
    • What they will use the tool for?
    • What are the different use cases for this user?

    scoutasia senior interview

    Key takeaways

    After digesting the learnings from the senior team members interview, 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

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

    secondary persona

    Empathising with our end users

    We travelled to Nikkei offices in Tokyo, Japan to facilitate five 1:1 session with potential customers in Asia. Common patterns learned from the interviews provided strong rationale towards design choices on “Connections Map”, “Company Search” and “Targets List”.

    Learnings

    A common usage scenario learned from the user interviews was that they would likely be in a rush or commuting in a train most of the times while checking for relevant news about companies they follow and discover 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.

    Key takeaways

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

    Design Language and Guidelines for developers

    Working closely with our in-house development team, I designed a UI pattern library to keep consistency between different sections of the product and to allow developers to re-use UI components. The Design Language is based in a mixture of both Nikkei and Financial Times branding guidelines.

    scoutasia design guidelines

    Creating the user interface

    After establishing the design language, the design process started and we began to design the product. Key elements were taken into consideration when designing the interface:

    1. Ensure the designs tied back to research findings
    2. Ensure business objectives firmly aligned with the design concepts
    3. Understand any technical limitations

    Feedback was always collected during the process, confirming everyone felt confident to move forward to validate the concepts to the target users.

    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

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

    scoutasia home

    Page overview containing news and notifications from companies the customer tracks, and general news from companies around Asia.

    scoutasia search results

    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 form the company.

    scoutasia connections map

    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.

    scoutasia mobile version

    News and notifications would be available on mobile. The decision of what features should be available was based on the learnings from the user interviews and tests during the design iterations. Users would be in a rush or commuting in a train most times while checking for relevant news about companies they follow and discover new companies mentioned in the news.

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