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Data Visualization | ML Platform

DISCOVER the emotions that drive human behaviors, decisions, thoughts, and actions.

Empathy Engine is an emotional analyzer ML platform that visualizes human language based on emotions attitude and norm.

Analyzes unstructured text data from sources such as customer, Health care providers, physicians, and patient feedback rIt organizes these inputs into relevant emotion categories derived from thousands of words and phrases. These emotion groups reveal insights into the “deep why” behind human behavior, and are accessible through a user-friendly dashboard within minutes.

 

6 months Process

The project starts with understand user pain points and challenges by conducting usability assessment audit. Then followed by doing test uses each features as a user.  Since the project is migrating existing platform to a new server with completely new features and capabilities, I need to gather new requirements from product owner and  work closely with data scientists. Crete new features and understand the current ML functionalities become two main work streams. 

 

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1. UX Assessment

Using online collaborative Miro board, I post UX/UI audit results to show some low hanging fruits across the platform to put into Sprint 1. The issues that are urgent to be fixed in order to ease current users pain point are put into Quick Fixes for the product designer to review. The nice-to-have future features are also documented for the data scientist to work on the future requirements and prototypes.

Tools used: Miro

 

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2. User Observation & Interviews (Remote)

Remotely, I sit down with 4 people from your target audience, observe their behaviors, and ask them pointed questions about their issues. What are they struggling with? What do they like about the application? Document the steps they take to get their jobs done. Watch user mistakes in virtual interviews really helps identify and shape new product features. 

 

Tools used: Microsoft Teams. Setup: User/Focus Groups.

 

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3. Requirement Gathering 

Based on the learnings from stakeholders interview and user focus group observations, I summarize key feature requirements and discuss these feature requirements with the product owner.
Tools used: Miro. Team involved: PO.

 

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4. Sprint Plan

Now, it’s time to actually build out the design. I put all features into the spreadsheet by sections and schedule a sprint backlog meeting with scrum master, product owner, and developers to put the right amount the tasks into 3 sprints. 

Tools used: Excel. Team involved: Scrum Master, PO.

 

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5. Wireframe

Tools used: Axure

 

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6. Prototype

Click on the Desktop/Mobile dropdown below to switch between adaptive views.
Click on hamburger menu on top left to navigate through sitemap.

 

 

Tools used: Axure

 

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7. Mockups

To quickly explore the look and feel of the platform, I put together dark and light mode mockups using Figma.
I also work with visual, UI, and product designers to help deliver final mockups that are accessible and align with the UX in the prototype through iterative process and make sure interactions are done correctly on staging environment by working with development teams.

 

Tools used: Figma

 

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8. PO/User feedback & iteration

PO reviews the prototype and provide change requests to me for redesigns. The clickable prototype is the most useful design to gather user feedbacks by observing the target audience using the prototype. As they do so, I observe how the act and react to the app. When they’re done, I ask them questions about their experience.