Microarray Analysis
Powered by Illumina’s Infinium technology, Microarray applications provide scalable, high-quality analysis for thousands of DNA samples, aiding drug development and disease research for scientists and bioinformaticians to improve global healthcare.
As the lead UX designer, I helped the product team reinvent the legacy product into a cloud solution, driving over 85% of customers to transition within a year. This shift to cloud led to a 20% increase in total revenue, marking the highest ever for Illumina's Microarray segment.
Design Process
When I took on the project, I began with UX discovery process to better understand the current situation. This involved interviewing customers, observing lab operations (Illumina's lab provides microarray services to clients such as Ancestry.com), and facilitating workshop with subject matter experts including field scientists.
To design the product experience, I first needed to understand the entire landscape of the workflow. I visited the lab and interviewed scientists to learn how bioscience and technology intersect. Given this simplified of version of journey map, my focus was on the final step where users complete DNA sample scanning, downstream the data to the cloud, and run further analyses for studies.
As shown in the twitter post above, customers have criticized Genome Studio, a legacy Microarray analysis tool, for issues with its usability, version compatibility, and being limited to genotyping assay only.
After identifying issues in the discovery process, I created this lean persona to define clear goals: simplifying analysis setup with a cloud-based solution to replace Genome Studio. This unified platform supports customers who utilize both sequencing and microarray analyses within a single platform.
Once I understood the technology and the key problems to solve, I began designing the information architecture. Through multiple iterations with the product development team, we refined the architecture by defining where users initiate analysis setup, identifying essential input and output components, and ensuring a cohesive cloud experience for users to analyze the scanned data at ease.
Design Solutions
After collaborating on series of design explorations with the team, I created a high-fidelity prototype for user studies, refining it through iterative feedback until release. Since launch, the product has evolved with continuous updates, providing a robust end-to-end experience beyond just a genotyping analysis tool.
The analysis setup workflow serves as the entry point to Microarray Cloud Solution, enabling users to configure settings, select biosamples, and launch analysis for a specific applicaiton type tailored to assay purpose such as Genotyping assay (identifying genetic traits and study disease risk) or Pharmacogenomics (understanding how genes affect drug responses for personalized medicine).
A key highlight of the cloud setup is the ability to customize configurations beyond the commercial product settings. This flexibility allows customers to focus on specific gene expressions for specialized assays.
Previously, advanced users had to rely on multiple tools to customize thresholds for output data that meets their specific assay parameter. With the new design enhancement, users can now manage everything within a single workflow, eliminating the need to switch between multiple applications.
A recent enhancement, 'Planned Analysis', allows users to save analysis setup in advance and auto-launch it when sample data is ready. This feature helps users streamline the process, and increased the number of samples analyzed, contributing to the company's Micoarray revenue growth in overall.
From the 'Planned Analyses' data table, users click the analysis name to review the setup details. Clicking “Edit” switches the view to edit mode, allowing users to reconfigure the setup.
From the local tab, users can navigate to Data management, a centralized file browser to conveniently access and manage all scanned data in an organized structure tied to the lab experience.
This cloud solution provides greater flexibility for experiments, offering a wider range of applications, and complete control with custom configuration and QC thresholds. Additionally, the microarray analysis setup workflow was integrated within BaseSpace Sequence Hub, the industry leading genomics software, allowing scientists to seamlessly use both genome sequencing and microarray applications within a single platform.
Measure Outcomes
Every product design should be measurable for gaining insights about its performance and learning user behaviors. I achieved this by using tools like Google Analytics and WalkMe Insight to track events and feature engagement, while collaborating with researchers for qualitative insights.
Above is a summary of user research on the early version of the microarray analysis setup workflow, showing high efficacy across all categories, including average satisfaction levels – 6.2 of 7.
Showing above is a shot of Google Analytics I created to track the completion rate of the analysis setup workflow showcasing the system’s efficiency for users with 84% success rate after configuration was done.
We’ve been using WalkMe to conduct NPS for all our software products, including BaseSpace Sequence Hub, where Microarray resides. Since I took over, the NPS score has increased by 152% over the next three years, reaching nearly 50.
Lastly, here’s a KPI shared by my product manager, highlighting how the cloud solution has significantly surpassed the legacy app with a scalable, user-friendly workflow. As we made customers happy, it directly contributed to a boost in microarray sales and software subscription growth.
Next: See customer interactions of tracking and managing software usage cost in Usage Explorer.