Revamping the Audience Selector
Simplifying the process of organizing your data into valuable, trade-ready audiences.
Project Website
Deliverables
SaaS Product Design • Design System • Visual Design
Client
Fanbank - Pumpjack Dataworks
Year
2020 - 2023
Introduction
FanBank by Pumpjack Dataworks is a cloud-based software service that helps sports organizations unify their fan data, understand its financial value, and securely exchange data assets with business partners.
Teams, leagues, and federations worldwide use FanBank to better know their fans and unlock new value.
My Role
As a generalist UI/UX designer working closely with a Lead Product Designer, I was responsible for product design, visual design, and UX design.
My main focus was on revamping the Audience Selector tool to enhance user experience and streamline the filtering process.
Design Proces
Discovering the Problem: The Need for a Better Tool
When I joined the team, the Audience Selector tool had several issues:
• Basic Functionality: The tool was a basic filter and search feature.
• User Frustrations: Users had to recreate filters repeatedly, leading to inefficiencies.
• Lack of Collaboration: There was no sharing feature, which hindered collaboration and data sharing.
Research: Understanding User Needs
To uncover the root of these issues and identify opportunities for improvement, I developed a research plan. Since we were working with a B2B platform, we had direct access to our users, allowing us to conduct interviews to discover their pain points and gather insights. I took a Jobs-To-Be-Done (JTBD) approach to focus on the functional needs of our users using the Audience Selector tool.
Interviews: Gathering Insights
I conducted interviews with five individuals from three different clients, including people from marketing, data analysis, and sales teams. During these interviews, I asked them to walk me through their current filtering process and share their thoughts on the existing system. This helped identify the specific frustrations they encountered at each step.
Defining the Problems: User Journey Mapping
From the interviews, I created a synthesized user journey map. Key findings included:
• Overwhelming Filters: Users felt overwhelmed by too many filters.
• Lack of Informative Traits: Users wanted more informative trait information.
• Need for Real-Time Feedback: Users required real-time feedback and clearer guidance.
• Efficient Report Generation: The report generation process needed to be more efficient.
JTBD - Functional Needs
To address these issues, the Audience Selector tool needed to meet several functional needs:
• Efficient Filtering: Users needed quick access to specific audience segments.
• Complex Query Creation: Users required the ability to create queries with multiple criteria.
• Real-Time Feedback: Users wanted real-time data summaries during filtering.
• Sharing Capabilities: Users needed to save and share filtered segments with colleagues.
• Filter History: Users desired access to a history of their last-used filters.
Competitive Analysis: Learning from the Best
I also conducted a competitive analysis, researching tools like Facebook Business, Twitter Business, and Hootsuite. Although we didn’t have direct competitors, this research allowed us to identify design patterns and features that could be adapted to improve our own Audience Selector tool.
Ideating: Brainstorming Solutions
Using the insights gathered from research, I brainstormed solutions for each identified problem. Ideas were evaluated based on feasibility, desirability, and viability.
User Flows: Mapping the Experience
I then worked on user flows for each functional need, establishing how users would achieve their goals within the tool. These user flows started as basic steps and evolved into detailed flowcharts.
Design and Prototype: Bringing Ideas to Life
The final prototype included several key features:
• Save and Share Segments: Users can now save and share specific audience filters.
• Complex Query Creation: Users can create queries using logical operators (AND, OR, NOT).
• Use of Saved Audiences as Variables: Simplifies creating refined filters.
• Real-Time Updates and Feedback: Immediate feedback on audience size and characteristics.
• Contextual Information and Labels: Real-time summaries for quick insights.
