Ecoagro
SaaS Pricing Platform
Product Designer responsible for designing and improving Ecoagro’s SaaS platform for the agribusiness market, connecting producers to capital markets. Focused on usability, scalability, and visual consistency across internal and external systems.
Problem:
The pricing team faced complex calculations for investment operations, including contract rules, different investment types, and indices such as IPCA. Existing processes were manual, time-consuming, and error-prone, making operation management inefficient.
Solution:
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Participated in Product Discovery, conducting interviews with the pricing team to understand rules, business logic, and specific needs.
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Designed a platform that automates interest and value calculations, dynamically adjusting for contract rules and investment types.
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Developed the Design System, standardizing visual identity across internal and external platforms, ensuring consistency and scalability.
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Created an intuitive operational workflow for high-volume data entry, with contextual actions and navigable indices to improve clarity and decision-making.
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Implemented dynamic recalculation features, allowing automatic updates across multiple steps of an operation.
Results:
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Reduced operational time for the pricing team, making high-volume calculations faster and more efficient.
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Ensured visual and functional consistency across platforms, supporting scalability of Ecoagro’s digital products.
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Improved clarity, agility, and safety in decision-making by organizing data contextually for each stage of the process.
Solution Proposals:
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Use AI to identify clothing items from outfit photos, so the user would only need to take pictures of their outfits, and the wardrobe would be automatically assembled according to the app's usage.
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Bringing a more appealing interface to the fashion audience.
The workflow for setting up operations was redesigned to handle large volumes of data more efficiently, improving speed and usability while reducing operational workload. The platform also logs actions throughout the process and dynamically recalculates values whenever inputs change.
Solution Proposals:
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Use AI to identify clothing items from outfit photos, so the user would only need to take pictures of their outfits, and the wardrobe would be automatically assembled according to the app's usage.
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Bringing a more appealing interface to the fashion audience.
As the team’s needs vary at each stage of the operation, the two main screens were structured with a navigable index, organizing information and actions in a contextualized way for each moment of the process, ensuring greater clarity, agility, and confidence in decision-making.
Solution Proposals:
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Use AI to identify clothing items from outfit photos, so the user would only need to take pictures of their outfits, and the wardrobe would be automatically assembled according to the app's usage.
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Bringing a more appealing interface to the fashion audience.
Tools & Methodologies
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Design & Prototyping: Figma, FigJam
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Research & Collaboration: Miro, Notion, User Interviews
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Methodologies: Product Discovery, UX Research, Design Thinking, Agile, Lean UX, Design System
Solution Proposals:
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Use AI to identify clothing items from outfit photos, so the user would only need to take pictures of their outfits, and the wardrobe would be automatically assembled according to the app's usage.
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Bringing a more appealing interface to the fashion audience.
