AWS x BrainStation
Web redesign focused on improving searchability and user-friendliness
Client:
MobGames Inc.
Timeline:
Gaming
Role:
Multimodal Design, Art-direction
Collaborators:
2019-2020, Hello Friday Agency
Overview
Problem: Amazon Data Exchange's current marketplace lacks searchability, user-friendliness, and clear dataset information, hindering organizations of all sizes from efficiently accessing and comparing datasets.
Solution: In 24 hours, my team — comprised of software engineers, data scientists, and project managers — and I improved the Amazon Data Exchange's marketplace. Improvements include a clear search bar, an AI-generated 'For You' page offering personalized dataset recommendations, and restructuring the site’s layout and information architecture for easier scan.
Overview
Problem: Amazon Data Exchange's current marketplace lacks searchability, user-friendliness, and clear dataset information, hindering organizations of all sizes from efficiently accessing and comparing datasets.
Solution: In 24 hours, my team — comprised of software engineers, data scientists, and project managers — and I improved the Amazon Data Exchange's marketplace. Improvements include a clear search bar, an AI-generated 'For You' page offering personalized dataset recommendations, and restructuring the site’s layout and information architecture for easier scan.
Overview
Problem: Amazon Data Exchange's current marketplace lacks searchability, user-friendliness, and clear dataset information, hindering organizations of all sizes from efficiently accessing and comparing datasets.
Solution: In 24 hours, my team — comprised of software engineers, data scientists, and project managers — and I improved the Amazon Data Exchange's marketplace. Improvements include a clear search bar, an AI-generated 'For You' page offering personalized dataset recommendations, and restructuring the site’s layout and information architecture for easier scan.
Given How Might We
The following question was given to us by AWS:
How might we build a more user-friendly approach to navigating the ADX marketplace so that users can more easily find useful datasets?
Given How Might We
The following question was given to us by AWS:
How might we build a more user-friendly approach to navigating the ADX marketplace so that users can more easily find useful datasets?
Given How Might We
The following question was given to us by AWS:
How might we build a more user-friendly approach to navigating the ADX marketplace so that users can more easily find useful datasets?
Getting Started
We began by addressing crucial steps before tackling the problem:
Understanding Amazon Data Exchange (ADX)
Defining roles and collaboration points for each discipline
Each discipline outlined their tasks with time limits. Within the 24 hour period, we had regular meetings that allowed us to regroup, assess progress, and discuss challenges.
Getting Started
We began by addressing crucial steps before tackling the problem:
Understanding Amazon Data Exchange (ADX)
Defining roles and collaboration points for each discipline
Each discipline outlined their tasks with time limits. Within the 24 hour period, we had regular meetings that allowed us to regroup, assess progress, and discuss challenges.
Getting Started
We began by addressing crucial steps before tackling the problem:
Understanding Amazon Data Exchange (ADX)
Defining roles and collaboration points for each discipline
Each discipline outlined their tasks with time limits. Within the 24 hour period, we had regular meetings that allowed us to regroup, assess progress, and discuss challenges.
Quantitative Research
Quantitative Research
Quantitative Research
Competitive Analysis
We also conducted a competitive analysis, examining similar competitors such as Kaggle. This is shown below.
Competitive Analysis
We also conducted a competitive analysis, examining similar competitors such as Kaggle. This is shown below.
Competitive Analysis
We also conducted a competitive analysis, examining similar competitors such as Kaggle. This is shown below.
Revised How Might We
We revised the initial how might we question based on our chosen user group - data science tech professionals.
How might we build a more user-friendly approach to navigating the ADX marketplace for tech data professionals so that users can easily navigate preferred datasets?
Revised How Might We
We revised the initial how might we question based on our chosen user group - data science tech professionals.
How might we build a more user-friendly approach to navigating the ADX marketplace for tech data professionals so that users can easily navigate preferred datasets?
Revised How Might We
We revised the initial how might we question based on our chosen user group - data science tech professionals.
How might we build a more user-friendly approach to navigating the ADX marketplace for tech data professionals so that users can easily navigate preferred datasets?
User Research Summary
Being that data scientists heavily use Amazon Data Exchange, we decided to prioritize this user group.
Due to time constraints, we opted not to seek external interviewees. Instead, our UX Designers interviewed data scientists within our team for insights into their goals and behaviors in navigating datasets. Additionally, we conducted usability tests with our team's data scientists, identifying specific areas for improvement. Here are the key areas we found:
Search bar
Content
Website aesthetic
Categorization of datasets
User Research Summary
Being that data scientists heavily use Amazon Data Exchange, we decided to prioritize this user group.
Due to time constraints, we opted not to seek external interviewees. Instead, our UX Designers interviewed data scientists within our team for insights into their goals and behaviors in navigating datasets. Additionally, we conducted usability tests with our team's data scientists, identifying specific areas for improvement. Here are the key areas we found:
Search bar
Content
Website aesthetic
Categorization of datasets
User Research Summary
Being that data scientists heavily use Amazon Data Exchange, we decided to prioritize this user group.
Due to time constraints, we opted not to seek external interviewees. Instead, our UX Designers interviewed data scientists within our team for insights into their goals and behaviors in navigating datasets. Additionally, we conducted usability tests with our team's data scientists, identifying specific areas for improvement. Here are the key areas we found:
Search bar
Content
Website aesthetic
Categorization of datasets
Persona
From the insights gathered from the interviews and usability tests, I crafted my target user. Below, you'll find a snapshot detailing his pain points, behaviors, motivations, and a concise summary.
Persona
From the insights gathered from the interviews and usability tests, I crafted my target user. Below, you'll find a snapshot detailing his pain points, behaviors, motivations, and a concise summary.
Persona
From the insights gathered from the interviews and usability tests, I crafted my target user. Below, you'll find a snapshot detailing his pain points, behaviors, motivations, and a concise summary.
Task Flow
We narrowed our focus to a key task that our target user finds most important: navigating and locating the correct dataset. The task flow is shown below.
Task Flow
We narrowed our focus to a key task that our target user finds most important: navigating and locating the correct dataset. The task flow is shown below.
Task Flow
We narrowed our focus to a key task that our target user finds most important: navigating and locating the correct dataset. The task flow is shown below.
Hi-Fi Mockups
Below are the tasks listed along with associated screens for a clear understanding of the app's functionality.
Hi-Fi Mockups
Below are the tasks listed along with associated screens for a clear understanding of the app's functionality.
Hi-Fi Mockups
Below are the tasks listed along with associated screens for a clear understanding of the app's functionality.
Reflection
After the 24 hour hackathon, I felt extremely proud for what my team and I achieved. Together, we worked cross-functionally and created a user-friendly solution. Our success hinged on effective communication and strategic planning, involving regular meetings not only to discuss our progress but, more importantly, to check in on how each of us was doing.
Reflection
After the 24 hour hackathon, I felt extremely proud for what my team and I achieved. Together, we worked cross-functionally and created a user-friendly solution. Our success hinged on effective communication and strategic planning, involving regular meetings not only to discuss our progress but, more importantly, to check in on how each of us was doing.
Reflection
After the 24 hour hackathon, I felt extremely proud for what my team and I achieved. Together, we worked cross-functionally and created a user-friendly solution. Our success hinged on effective communication and strategic planning, involving regular meetings not only to discuss our progress but, more importantly, to check in on how each of us was doing.
Other Cases
Other Cases
Other Cases
