MRV Data Accelerators
2025
Climate tech
UX Enhancement
Rapid Delivery
A rapid one-month delivery that reduced the time for farmer data entry by 70%, satisfied urgent customer needs, and set the stage for scalable, AI-driven solutions.
Irene L - Design; Vivian D - Product; Lionel H - Eng Manager; Rebecca H, Madeline O, Nan W - Fullstack Eng
Context
Data accelerators make MRV possible
Agribusinesses depend on farmers to supply extensive data to measure, report, and verify (MRV) their GHG emissions and reductions. Farmers must locate their fields on a geospatial map and, for each one, provide detailed records on crops, tillage, fertilizer, and irrigation going back up to five years.
Busy and not usually tech-proficient, farmers struggle with the volume of data entry, relying on various ‘data accelerators’ to make the process more efficient.
Balancing an overhaul, expectations, and urgency
One of our biggest customers, Cargill, was preparing to launch its 2025 program, spanning 1.4 million acres of emissions measurement.
At the same time, we were wrapping up a major data infrastructure overhaul paired with a massive UX/UI revamp — still scrambling to deliver essentials like data validations, satellite-based pre-fills, and other features customers had come to expect from the legacy platform.
With just a month until launch, it was critical we release a key data accelerator: Duplicate Data. Our initial plan was to reimplement the legacy version, but further analysis revealed it left key use cases unaddressed, posing a major risk to our relationship with Cargill.
The legacy Duplicate Data UX
Challenge
Where the legacy UX fell short
From past programs, we knew customers expected a Duplicate Data feature to support four distinct use cases. However, the legacy experience only addressed one of the four, leaving the others unmet and creating significant gaps for customers.
Facing constant requests from Cargill for updates on the feature’s release, we knew we had to pivot quickly and deliver an improved experience — while acknowledging that the most holistic solution couldn’t be shipped in such a short timeframe.
Approach
Solution
Seamless copying, flexible overwrite
We launched an alpha of the new Duplicate Data feature to Cargill for active use and immediate feedback. It allowed users to copy events across stages (crops, tillage, etc.) directly from a field’s data table, choose target fields, and decide how to handle existing data.
The new Duplicate Data UX
Outcomes
Average time to complete enrollment Decreases by 70%
This feature has now shipped to all customers. For our largest program, Cargill US, which spans 1.1M acres, we saw a 70% decrease in the average enrollment duration when compared to the previous year's program.
With shrinking sustainability budgets, agribusiness teams must do more with less. Duplicate Data and other Regrow data accelerators make that possible, differentiating our product from competitors.
Next Steps
Thinking critically about what to tackle next
With Duplicate Data launched, product and design paused to reflect — using design thinking to determine which accelerator would deliver the most strategic impact next.
AI as the ultimate accelerator
One opportunity we see is leveraging AI. We prototyped a visionary experience to show how it could save time and further differentiate Regrow from competitors.