Overview.

My role

In 2023, I joined Ragene as their first UX/product designer, tasked with building upon the initial work designed by their engineers. Over the past year, I've played a pivotal role in designing and refining a data analysis and visualization product.

Team

2 Product Manager

4 Developers

2 Bioinformatics Scientists

This case study shows how I collaborated with an interdisciplinary team to incrementally revamp the product from both user and business perspectives. Through my efforts to enhance the no-code data analysis tool, I've significantly improved user experience, attracted new customers, and contributed to paving the way for potential scientific breakthroughs.

Timeline

2023-2024

Context.

What’s Ragene?

1. It's pretty obvious that AI is the biggest gimmick to attract user & investment right now.

In bioinformatics, mastering programming algorithms for data processing often presents a steep learning curve. Ragene's no-code data analysis platform significantly streamlines this, boosting researchers' efficiency.

Why Ragene AI?

1. It's pretty obvious that AI is the biggest gimmick to attract user & investment right now.

In bioinformatics, mastering programming algorithms for data processing often presents a steep learning curve. Ragene's no-code data analysis platform significantly streamlines this, boosting researchers' efficiency.

2. It's a good chance to embed AI for Ragene to boost users’ productivity in life sciences.

In bioinformatics, mastering programming algorithms for data processing often presents a steep learning curve. Ragene's no-code data analysis platform significantly streamlines this, boosting researchers' efficiency.

Kick off.

Understand User

There are two types of user groups on our platform.

Mapping the complexity from these research projects proved difficult; with multiple actors, unique to the places they worked at, it was hard to map valuable user journeys. However, we boiled some of the significant themes down to two major archetypes.

Identify Opportunity

Facilitate workshop with internal users to ideate AI application scenarios.

In bioinformatics, mastering programming algorithms for data processing often presents a steep learning curve. Ragene's no-code data analysis platform significantly streamlines this, boosting researchers' efficiency.

Develop Roadmap

Prioritize features based on business needs and development challenges.

While Ragene is currently concentrating on the functionality of data analytics, it is also planning its future direction. It is anticipated that once the core functions of the product are nearly fully developed, Ragene will begin to establish a community centered around life science research and data analysis. This community will enable users to communicate and enhance the platform's resources.

Design Phase 1.

Use Cases

There are 3 main use scenarios of user interaction with chatbot.

Initially, the team planned to develop an onboarding process to help users learn about the platform's features and usage. However, user research showed that our primary users—biology students and researchers—have a strong ability to explore and learn new tools independently.

Design Highlight

An optimized Conversational UI grounded in specific use cases.

Initially, the team planned to develop an onboarding process to help users learn about the platform's features and usage. However, user research showed that our primary users—biology students and researchers—have a strong ability to explore and learn new tools independently.

Design Phase 2.

Design Iteration

1. AI can automatically generate analytics pipeline based on prompts, rather than just offering textual guidance by Chatbot.

While Ragene is currently concentrating on the functionality of data analytics, it is also planning its future direction. It is anticipated that once the core functions of the product are nearly fully developed, Ragene will begin to establish a community centered around life science research and data analysis. This community will enable users to communicate and enhance the platform's resources.

2. AI can automatically fill out the parameters of the node, rather than just offering textual guidance by Chatbot.

While Ragene is currently concentrating on the functionality of data analytics, it is also planning its future direction. It is anticipated that once the core functions of the product are nearly fully developed, Ragene will begin to establish a community centered around life science research and data analysis. This community will enable users to communicate and enhance the platform's resources.

Design Phase 3.

New Finding

Users are concerned with the analysis process because they care about the insights and output.

The visualization preview of each node is displayed directly on the node after the node computation is completed, without the need for each selection. So users can view multi data visualization at a time.

New Design

1. AI interpretation

The visualization preview of each node is displayed directly on the node after the node computation is completed, without the need for each selection. So users can view multi data visualization at a time.

2. AI generate report

The visualization preview of each node is displayed directly on the node after the node computation is completed, without the need for each selection. So users can view multi data visualization at a time.

Design Phase 4.

Design Iteration

Driven by user feedback & product strategy.

The visualization preview of each node is displayed directly on the node after the node computation is completed, without the need for each selection. So users can view multi data visualization at a time.

🎉 Phew~ You made it!