How to turn retail products into professional real-time solutions through data-driven UX.
NutriNet calculates optimal crop types and fertilization schedules by synthesizing soil data, weather forecasts, and real-time field conditions.
Professional agronomists and farmers who rely on NutriNet as their primary decision-making tool for every field and crop cycle.
Any new feature must earn its place. It must feel like professional insight — not a product placement — or it doesn't belong in the workflow.
The organization wanted to introduce bio-stimulants directly into the fertilization workflow. Experienced farmers immediately recognize — and reject — any promotion inside a professional tool.
"The real design problem wasn't how do we show the product — it was how do we make it feel like a professional recommendation, not an advertisement?"
The system is continuously updated with real-time field data for every farmer. After recently integrating satellite image analysis for soil condition detection, it became clear that these existing data streams could power personalized agronomic recommendations — surfacing the right advice for the right user at the exact moment they needed it.
Instead of banners or promotional modules, I designed a system of contextual tooltips and benefit-driven tags that surface within the fertilization planning screen — exactly when the farmer is making active decisions. The product recommendation becomes part of the professional workflow.
The original fertilization planning interface — functional, professional, with no contextual product awareness.
Environmental conditions cross a threshold. The trigger engine identifies a relevant product and prepares a contextual recommendation.
A benefit-tagged tooltip appears within the workflow — specific, timely, and actionable. The farmer sees advice, not an ad.
Each bio-stimulant product was tagged with specific environmental benefit categories. When a trigger fires, only the matching tags surface — ensuring every recommendation is directly relevant to the current conditions.
By mapping products to real-time agronomic events, we turned a business objective into a feature farmers actually valued — personalized, timely, and earned.
Recommendations appear only during genuine agronomic stress events.
Contextual advice outperformed generic promotions — because it solved a real, active problem.
Every interaction fed signal back, making recommendations more accurate over time.