Anomaly Contributors — Discover the cause of the malfunction
AI, Machine Learning, Sensor Data Analytics, B2B
MY ROLE
UX/UI designer
I was responsible for ideation, visual design, interaction design and prototype.
RESULT
New feature highlighting contributors to anomalies in devices behavior, clarifying the measured parameters and their anticipated values.
MY IMPACT
Cut frontend development time by 25% through design optimization and close collaboration with developers
PROBLEM
BUSINESS GOALS
Retain customers by providing an additional service to them
Increase customer satisfaction by fulfilling their feature request
CHALLENGE
Create a new data visualization but keep it feasible
COLLABORATED WITH
Data Scientists
Developers
Product Owner
Project Manager
TOOLS USED
Figma
InVision
Zeplin
AFFINITY DIAGRAM
USER NEEDS
KNOWLEDGE
Users know causes and severity of the anomaly
CLARITY
Users understand what they see at a glance
FINAL DESIGN
LEARNINGS
WHAT WENT RIGHT
Designs optimized for feasibility
Developing a new visualization takes extra time. So it was crucial to find a balance between ambitious design goals and what can feasibly be accomplished within our time limits. Through close collaboration with developers, I selected a visualization that fulfilled all our needs and could be implemented swiftly.
WHAT WENT WRONG
Inconsistency in copy
Myself and fellow designers wrote the product copy while designing the UI, resulting in inconsistencies in spelling and wording. This lack of cohesion gave our product rushed and unprofessional appearance. It took us weeks to identify and address all the copy issues.
SOLUTION
Keep all UX copy in one reference file