Translating research
into action points
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New Information architecture that represents farmers’ farming mental model.
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Features will be broken down into steps, adding feedback, and instructions.
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The Health Check feature will be easy to find and self-explanatory.
Business KPIs
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Crop health checks will increase by at least 20%
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Users select the right crop disease on non-automated recognized cases.
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Organic traffic will increase by at least 5%
UX KPIs
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Plantix will be so easy to navigate that farmers won't need help to use it.
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Use cases and flows will be simplified reducing cognitive load.
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The app will use speak user language.
O3
Information Architecture.
Changing the IA of the app was imperative if we wanted Plantix to be easy to use by farmers regardless of the tech knowledge. Mapping the app as a crop-based knowledge application instead of dividing it per feature was the only way to achieve that.
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Features were hierarchized based on the crop life cycle.
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Clearer affordances in buttons and cards were added to hint which parts of the application were navigation points.
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The copy was carefully considered to match farmers' vocabulary and written as action to indicate what to do at each step.
O4
Predicting AI result cases.
One click away from all
your crops needs.
Features were hierarchized based on the crop life cycle. Clearer affordances in buttons and cards were added to indicate which parts of the application were navigation points.
The copy was carefully considered to match farmers' vocabulary and verbs were written in the infinite form to indicate what to do at each step
IA, Research, UX/UI Design & Strategy
Role
Machine Learning. Android App.
Type
Company
Peat GmbH
Plantix is an Agri app that uses artificial intelligence in image recognition to detect crop diseases, helping farmers grow healthier crops.
When I joined the company, the app was downloaded by millions of users all around the world. However, a big percentage of them used it a few times and uninstalled it after taking a picture and the company didn't know why.
AI for crop disease detention
-Plantix.
O2
Strategy.
Along with stakeholders, carefully considered how the insights gathered could be used to achieve business goals and at the same time develop an easier-to-understand app for any tech knowledge gap that we found.
We kicked off the collaboration with a field trip to India.
The research phase aimed to validate how the user was using the app and understand which improvements in the app needed to be part of the company strategy.
Seeing farmers using the application in a real context led to understanding how Plantix could fulfill farmers' needs and which pain points were preventing it to do so.
O1
Understanding.
card sorting
User interview
1
Farming is seasonal and relies on local knowledge
Plantix was used as a troubleshooting app when farmer's community knowledge was unavailable. Explaining why users uninstalled the app after a few usages and install it again a few months later
2
'I don’t know what I need to do. Should I take a selfie?'
When Farmers downloaded Plantix, the Home screen was empty except for a camera icon. The lack of instructions and exposure to material design made it hard for them to understand how to use Plantix features and benefit from them.
3
The feature-based design prevents users from getting a crop overview
Difficulting navigation and mandatory crop selection on each feature made it hard for the user to get an overview of their crops.
