Goodnotes
Goodnotes
Goodnotes
PDF Analyzer Tool
Role
UX Designer
Timeline
Jan 2025 - Mar 2025
Team
1 PM, 2 Designers, 5 Developers
Context
The Client
Goodnotes is a leading digital note taking platform used by millions of people worldwide. They also became the world's first AI-Powered digital paper company in 2023 after the launch of Goodnotes 6.
The Client
Goodnotes is a leading digital note taking platform used by millions of people worldwide. They also became the world's first AI-Powered digital paper company in 2023 after the launch of Goodnotes 6.
The Client
Goodnotes is a leading digital note taking platform used by millions of people worldwide. They also became the world's first AI-Powered digital paper company in 2023 after the launch of Goodnotes 6.
Our Task
We created a proof-of-concept document analysis and outline generation testing platform, building the foundation for innovative future features in Goodnotes.
Our Task
We created a proof-of-concept document analysis and outline generation testing platform, building the foundation for innovative future features in Goodnotes.
Our Task
We created a proof-of-concept document analysis and outline generation testing platform, building the foundation for innovative future features in Goodnotes.
What I Did
As the lead UX designer, I focused on creating intuitive AI interactions, including a chatbot and multi-model analysis options. I leveraged user research, client feedback, and industry standards, resulting in a 95% satisfaction rate during testing.
What I Did
As the lead UX designer, I focused on creating intuitive AI interactions, including a chatbot and multi-model analysis options. I leveraged user research, client feedback, and industry standards, resulting in a 95% satisfaction rate during testing.
What I Did
As the lead UX designer, I focused on creating intuitive AI interactions, including a chatbot and multi-model analysis options. I leveraged user research, client feedback, and industry standards, resulting in a 95% satisfaction rate during testing.
RESEARCH
How can we leverage AI tools to enhance the academic note-taking experience for students?
Primarily used for academic note-taking and studying, our target audience was predominately college students and everyday notetakers. To combine our client's needs with user needs, I leveraged 45 survey responses and 8 user-interviews to help me understand their typical habits with using AI for studying, how they organize their notes, and how they would most be willing adopt new AI-features. From this research, I found 3 main findings as follows:
Current document analysis and AI-powered note tools have been gaining popularity due to the convenience they offer users
We explored various document analysis tools from NotebookLM to Notion to understand the industry UX-standards of these types of applications and what features already exist. Our key findings were that our application should have an easy upload process, simple analysis interface, and expand on existing AI-features for our user’s specific use cases such as reviewing lecture notes.
RESEARCH
How can we leverage AI tools to enhance the academic note-taking experience for students?
Primarily used for academic note-taking and studying, our target audience was predominately college students and everyday notetakers. To combine our client's needs with user needs, I leveraged 45 survey responses and 8 user-interviews to help me understand their typical habits with using AI for studying, how they organize their notes, and how they would most be willing adopt new AI-features. From this research, I found 3 main findings as follows:
Current document analysis and AI-powered note tools have been gaining popularity due to the convenience they offer users
We explored various document analysis tools from NotebookLM to Notion to understand the industry UX-standards of these types of applications and what features already exist. Our key findings were that our application should have an easy upload process, simple analysis interface, and expand on existing AI-features for our user’s specific use cases such as reviewing lecture notes.
RESEARCH
How can we leverage AI tools to enhance the academic note-taking experience for students?
Primarily used for academic note-taking and studying, our target audience was predominately college students and everyday notetakers. To combine our client's needs with user needs, I leveraged 45 survey responses and 8 user-interviews to help me understand their typical habits with using AI for studying, how they organize their notes, and how they would most be willing adopt new AI-features. From this research, I found 3 main findings as follows:
Current document analysis and AI-powered note tools have been gaining popularity due to the convenience they offer users
We explored various document analysis tools from NotebookLM to Notion to understand the industry UX-standards of these types of applications and what features already exist. Our key findings were that our application should have an easy upload process, simple analysis interface, and expand on existing AI-features for our user’s specific use cases such as reviewing lecture notes.
DEFINE
Scope and Structure
The most important features for our MVP were document classification and outline generation. Additional features identified through our research were organized in a feature matrix based on effort and user impact. I expanded our features like the chat-bot by ideating on context aware chat suggestions and section-based queries.
The most important action for this MVP was to upload a document and view the document analysis. From there a user can also interact with the outline, chatbot, and regenerate the analysis using a different model. I mapped a user flow detailing the actions, decisions, and screens a user might see.
DEFINE
Scope and Structure
The most important features for our MVP were document classification and outline generation. Additional features identified through our research were organized in a feature matrix based on effort and user impact. I expanded our features like the chat-bot by ideating on context aware chat suggestions and section-based queries.
The most important action for this MVP was to upload a document and view the document analysis. From there a user can also interact with the outline, chatbot, and regenerate the analysis using a different model. I mapped a user flow detailing the actions, decisions, and screens a user might see.
DEFINE
Scope and Structure
The most important features for our MVP were document classification and outline generation. Additional features identified through our research were organized in a feature matrix based on effort and user impact. I expanded our features like the chat-bot by ideating on context aware chat suggestions and section-based queries.
The most important action for this MVP was to upload a document and view the document analysis. From there a user can also interact with the outline, chatbot, and regenerate the analysis using a different model. I mapped a user flow detailing the actions, decisions, and screens a user might see.
IDEATE
Considering the interface
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IDEATE
Considering the interface
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IDEATE
Considering the interface
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