Data Input for Scientists
Role: Lead Product Designer
Project: Table re-design
Timeline: 2024 - Present (GA set to launch May 2025)
Impact: Unblocked ~6 million in ARR
The process began with incremental, high-value updates addressing immediate user needs and evolved into transformative releases with more impactful features.
Problem
Data entry for structured tables was identified as the top pain point for our user base. It presented significant challenges that hindered scientists from efficiently recording experiments and connecting data to its scientific context. These challenges included:
Performance issues: Slow processing of large datasets led users to file frequent bug reports, abandon tasks, and switch to alternative tools.
Inefficient, tedious, confusing UX: Complex, click-heavy, unintuitive workflows created friction, frustration, errors, and drop-off from task completion
Missing Functionality: Lack of essential features such as filtering, column re-ordering, and merging cells limited users’ ability to complete their goals.
“Getting it all into this system is not worth the time”
Why was it important to solve these problems?
Scientists are working at a scale that outpaces their current tools. They need an intuitive way to input, organize, and manage structured data—ensuring accuracy, efficiency, and the ability to scale.
Structured data is critical for preserving customers’ intellectual property, enabling high-throughput workflows, and supporting AI-driven research. It ultimately accelerates the development and delivery of life-saving drugs to market, making the UX flow for data structuring a cornerstone of Benchling’s business strategy.
Solution:
My team and I developed a larger, faster, and more intuitive table design that empowered scientists to automate repetitive tasks while streamlining and accelerating their manual workflows—enhancing both efficiency and user experience in critical scientific processes. Key considerations for our MVP release were:
Streamlined workflows: sped up tedious tasks while lowering cognitive load for end users by shipping key features including automated column mapping, form inputs, row and column re-ordering, filtering, and a performance monitoring log.
Performant & scalable: Virtualized table design with enhanced views ensured an increase in dataset size from 500 rows to 1,000 rows ensuring high-throughput workflows without a lag.
Modular: This reusable platform component enabled other teams at Benchling, including Molecular Biology, Requests, and Bioprocess teams, to deliver their tools to customers faster, accelerating development and scaling across the platform.
“Registering a sample to then put it immediately into a container is smart. Combining those two steps into one is brilliant. ”
Notable features included: drag to re-order, form functionality and table filtering
Impact
Maintaining and expanding our footprint with enterprise biotechnology customers has been a key business goal, and the table redesign played a pivotal role in supporting this objective.
Increased customer satisfaction through streamlined workflows.
Resolved critical enterprise customer needs, unlocking millions of dollars in potential revenue.
Established a strategic foundation for this table as a modular component, enhancing efficiency and scalability for internal teams.
One of our customers enjoyed one of the new table features so much that he wrote an entire blog post about it!
“By the end of the day (literally), I had updated six templates (it took seconds) that I happened to be working on.
Give it a try, it’s insanely simple and disproportionally valuable for scientists’ user experience, productivity, and accuracy. ”