Industry:
Nature tech, space tech, GIS, B2B sustainability software
Role:
Founding designer (research, design, strategy, roadmap, PRDs, issue/story prioritization)
Internal collaboration with:
CTO, junior developer
External collaboration with:
Procurement specialists, sustainability managers, nature restoration organizations
Tools & systems used
MUI, Figma, GitLab, Maze, Typeform, Builder.io, Framer, Hubspot, Gemini,, and more.
mission.
To un-sever the relationship between business and nature.
The platform is using Near real-time nature and biodiversity insights via satellite data and GIS data to help
ecosystem restoration organizations show their positive impact on nature and
support procurement teams in understanding and mitigating their impact on nature with the ultimate goal to make nature-positive decisions.
knowledge hub.
Building the knowledge and documentation hub
To ensure our small, remote team remained aligned and built with intention, I created and maintained a comprehensive product and design wiki. This serves as our single source of truth for everything from high-level strategy to detailed data methodology.
It is a living document, that allows us to move quickly without sacrificing clarity or rigor.
Screenshots of our single source of truth wiki
guiding principles.
The principles that guide the product
Based on conversations in our team, I established a set of core principles to serve as our guiding principles. This was a critical foundational step to ensure that as we grew, every product decision would be aligned with our mission and our ethical responsibilities to our users and to nature itself.
These principles are not just ideals; they are the practical, day-to-day guide we use to build a product that is trustworthy, effective, and life-centered.
user journey mapping.
Mapping the complexity
To understand how different user types would interact with the platform across various scenarios, I created comprehensive journey maps that identified key decision points, pain points, and opportunities. These maps became the foundation for prioritizing features and designing contextualized experiences for procurement specialists versus sustainability managers.
Monitoring flow
data viz.
Designing the visual language of our data
With our core principles established, the next step was to create a practical guide for how we would visually represent our complex data. I developed this data visualization guide to serve as a clear rulebook for our team, ensuring that every chart, map, and insight would be not only intuitive and scannable but also ethically sound and true to our 'nature-first' principle
Snippet of a data visualization guideline.
product development in phases.
User-friendly location data import & validation
Problem
A common failure point for GIS and data platforms is the data import process. Most tools are notoriously user-unfriendly, often failing silently or providing cryptic error messages when validation issues occur. This leaves users frustrated, unable to fix their data, and reliant on customer support. Our goal was to design an experience that was the complete opposite: transparent, empowering, and easy to use for non-experts.
Solution
I designed a multi-step validation flow guided by three principles:
Make issues obvious (visibility): The 'Issues found' component immediately summarizes the data's health with clear categories for 'Critical issues' and 'Warnings', so the user instantly understands the state of their upload.
Make issues findable (location): The detailed issue table provides a clear description for each problem and, crucially, lists the exact 'Affected data', allowing users to pinpoint the source of the error in their files.
Make issues actionable (mitigation): We clearly distinguish between critical issues that block an upload and non-critical warnings that can be fixed later. This empowers the user to make an informed decision to either correct their data or proceed with the valid parts of their import, saving them significant time and frustration.
On the roadmap: automatic issue/error correction for the most common issues. The mitigation will be initiated by the user—with a mere click of a button—so that they’re still in control over the data.
Outcome
This transparent and empowering validation flow is a key differentiator for our platform. It significantly de-risks the most stressful part of the onboarding process for new users. By helping users help themselves, we build trust from the very first interaction and drastically reduce the anticipated need for customer support intervention during data import.
Editing location data made easy
Nature insights dashboard
Scientifically sound
For the first version of the platform we are using satellite data from ESA's Copernicus space mission and several geospatial data sets that are either well-knowns and validated by the sustainability and GIS community or come from scholars directly.
Quick, high-level insights
From potential customer research conversations, it was clear that the insights should contain high-level summaries as well as automatically pointing the customers to the most important information.
Creating a connection to nature
My research into nature / environment insights SaaS products quickly showed that the vast majority or platforms have a generic business KPI and "sterile tech" look. Based on the design and data visualization principles I established, that was not an option for us.
Example of applying some of the design and data viz principles to high-level KPI cards.
I use relevant nature photography that is tied to the content of the KPI card. This creates an immediate connection to nature and the ecosystems the company is "in touch" with. The organic shape of the image is chosen because nature consists of organic shapes.
The nature photo changes depending on the data on the card. The border of the KPI card also changes according to the data. E.g., if everything is fine, the border is green, if something needs to be investigated, the border is red, etc.
Maps
Below the KPI cards is the map content, where the customer can interact and get more in-depth information.
The data coming from satellites is deliberately in a separate data layer group as the data coming from static geospatial datasets.
For the satellite data coming from various indexes, I used language that caters to both experts and non-experts. When hovering over a polygon, the specific index name is visible.
big small things.
Sweating the details
From the very beginning I wanted to have empty states, error messages and loading states that convey the brand's tone of voice and attention to detail. These small moments are often overlooked, while they actually impact the product experience.
A concept of a loading state when progressive revelation isn't needed.
More on this case study coming soon!
