Redesign a data validation platform

Challenge

The platform’s initial version was launched with some financial services customers, offering basic features. As enterprise databases grew in complexity—with diverse structures, interdependencies, and data flows across business units—business users found it increasingly difficult to independently manage and validate their data. Simultaneously, our design team faced a common challenge in redesigning for B2B product: lacking of establishing direct connections with real users to understand their needs more deeply.

Approach

Given these challenges, we applied an alternative approach to address the issues of redesigning a B2B product where direct access to end users is limited. Our goal was to find strategies that would enable us to gain valuable user insights and design effectively while aligning with business goals. As UX Designer, I organized the redesign into three phases: pre-discovery, discovery, and delivery.

Pre-discovery: We gathered foundational knowledge through stakeholder interviews, competitor analysis, and insights from sales and customer-facing teams to understand product and market needs.

Discovery: We conducted deeper user research, including heuristic evaluations and data analysis, to identify key redesign elements and priority.

Delivery: We moved from insights to action, building and iterating on prototypes, then finalizing the design for development handoff.

Hypotheses and gut feelings

The phased approach beginning with pre-discovery enabled us to make informed, user-centered design decisions that ensured the product remained relevant, despite limited access to real users. This structure also allowed us to refine and ground our initial hypotheses and gut feelings in a more objective, data-driven manner. Put simply, our hypotheses and gut feelings were validated through the data gathered during the pre-discovery and discovery phases and experiences of each member.

Insights

To evaluate usability and identify issues, I selected the platform’s initial version, focusing on core functions, for usability testing. Participants included key stakeholders and sales and customer-facing teams, offering valuable feedback. I also conducted a heuristic evaluation to assess its alignment with usability principles and uncover additional improvement areas.

Navigation complexity and unintuitive UI

• Confusing system setup: The system features an overly complicated structure, requiring users to navigate many steps to complete basic tasks.

• Challenges with action recall: Users often struggle to remember the specific actions needed to navigate the system effectively.

• Demand for support documentation: There is a strong need for comprehensive support documentation and a more streamlined setup.

• Frustration with unintuitive UI: Users report significant frustration with the interface, which lacks intuitiveness and clear guidance.

• WCAG issues: Users report confusion with KPI-color selection in data visualizations.

Difficulties in accessing, utilizing, and interpreting data

• Data accessibility issues: Users struggle to read and access data in the system, complicating their analyses and decision-making.

• Complex data filtering: The data filter system is overly complicated, making it difficult for users to apply filters effectively.

• Inefficient table workflow: The workflow for managing tables is inefficient, causing delays and hindering seamless data interaction.

Key redesign elements

Drawing from insights gathered during the pre-discovery and discovery phases, along with our data-driven intuition, we identified the key elements for the redesign process.

• Flexibility and efficiency of use: Navigation should be visible and accessible at all times. Implementing shortcuts, such as one for creating dynamic filters, can streamline interactions for both novice and experienced users. Additionally, frequent actions should be customizable, and current tasks should be saved on a landing page for easy recovery in future sessions.

• Match the real world: Use real-world terminology at appropriate times. Filters should be displayed as dropdown menus, and SQL queries should appear alongside plain text for better clarity.

• Error prevention: Provide confirmation options or warnings before users finalize actions to minimize mistakes.

• Reduce redundancy: Eliminate irrelevant information, unnecessary actions and popups. The reporting table and UI design should focus on essential elements to improve usability.

Inclusive design

I incorporated Inclusive Design principles to address diverse user capabilities, needs, and goals in data validation and visualization in order to allow adaptive strategies. This involved:

• WCAG-compliant color options for data visualsization.

• Customizable font sizes and table density settings.

• Minimizing disruptive popups by using tooltips and subtle nonmodal overlays instead.

Inclusive Design extends beyond aspects like colors, font size, and text density. However, within the constraints of this project, I focused on making it as accessible as possible.

User flow of key features

Next, we designed the user flow for the key features with the objective of streamlining the user experience. By analyzing the pathways users navigate to access key features, we aimed to minimize friction and reduce unnecessary complexity.

High-fidelity prototypes

Everything has finally come together! I took charge of developing a new design system, creating high-fidelity prototypes, and conducting direct testing with stakeholders. Additionally, a design catalog for the platform was created to support future knowledge transfer.

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