Role
Product Designer
Timeline
Apr. 2025 - Jun. 2025
Team
2 Product Managers
3 Product Designers
2 Product Marketing
Managers
Skills
UX Research
Product Strategy
Product Thinking
Prototyping
User Interviews
Usability Testing
OVERVIEW - THE PRODUCT
Perplexity: An AI-powered research and discovery platform
As the platform looks to grow its presence among college students, our team at Product Space set out to reimagine how Perplexity could better serve academic needs and improve student engagement.
RESEARCH QUESTION
How can we increase Perplexity’s user engagement and acquisition in the college segment?
USER RESEARCH
Understanding students’ AI tools usage
In order to gain product feedback on Perplexity’s existing features and other competitors, we surveyed students at UCLA with 4 user types: ones who only use Perplexity, ones who don’t use AI at all, ones who have used other AI tools but not Perplexity, and ones who have used multiple AI tools including Perplexity.
Guiding questions:
• Why and how do students use Perplexity?
• What value and frustrations do students find in Perplexity and other AI tools?
• Why are students unfamiliar with Perplexity?
Most students are unfamiliar with Perplexity, and early adopters gravitate towards academic uses
1
Students are frustrated with current AI tools - Perplexity’s core strengths align with top user priorities
2
Word-of-mouth and social platforms dominate how students find new AI tools
3
Students use AI for learning & research, demanding efficiency over deep engagement
4
USER RESEARCH
The intersection of statistics and user insights
We wanted to dive more into students’ use cases of different AI tools, features they value the most, and pain points. Based on our 30+ interviews across 15 majors, we identified 4 most popular areas that students use Perplexity and other tools for. We prioritized including direct quotes from students for the Perplexity team to access in the future.
BRAINSTORM
Brainstorming potential features for the product
We came together and brainstormed as many ideas as we could in 10 minutes, and then in-depth analyzed which features we could focus on building out.
FEATURE RECOMMENDATION
Introducing Snippet
After all the research and user insights, I realized the Spaces in Perplexity is often underutilized, but it's one of the unique features that Perplexity offers.
In order to increase Perplexity's user engagement and acquisition for higher education, I created a feature called Snippet that allows users to highlight, save, and arrange key insights from any article or uploaded file directly into Spaces in seconds.
My goal is to transform Perplexity from a read-and-leave search tool into a dynamic knowledge workspace, where Spaces become live hubs for instant organization and collaboration.
THE PROBLEM
Student researchers waste time jumping between AI tools, citation platforms, and academic workflows
While Perplexity offers strong search and citation capabilities, it lacks a lightweight way to capture and save insights in the moment - especially into Spaces, folders where you can save and organize things you find - like answers, articles, or highlights - so you can come back to them later.
USER STORIES
Understanding user's frustrations with Spaces
From the user survey and user interview we have done, there is 90% of students who spend 1-7 hours weekly on research, but constantly switch contexts between research, citation tools, and LMS submission. Students waste time jumping between AI tools and learning platforms.
COMPETITIVE ANALYSIS
To validate the opportunity for the Snippet feature, I analyzed several AI tools to understand how they support content capture, organization, and reading workflows. While many tools offer strong AI generation or Q&A capabilities, none provided a frictionless, in-context way to save insights directly into organized spaces during reading.
Limitations of other AI tools:
• No in-context saving: Most tools don’t allow users to highlight and save text directly while reading
• Lack of organization: There’s no built-in way to group or revisit saved insights - only linear chat history or raw outputs
• No support for external content: Users can’t extract or organize information from PDFs, websites, or uploaded files
• Heavy reliance on copy-paste: Users must switch to tools like Notion or Google Docs to organize their findings.
• Not designed for research workflows: Tools like Copilot and Cursor are tailored for productivity or coding—not content discovery and knowledge building.
DESIGN SOLUTION
Seamlessly save your key insights from articles into Spaces
Here is a look at the prototype of the new feature - backed by multiple rounds of user testing and iterations.
Snippet allows you to:
• Highlight any text from Discover articles, uploaded PDFs, Word Docs, or personal notes
• Save directly to a new or existing Space via a floating toolbar
• Quickly revisit highlighted sections without scrolling or searching
Add to Existing Space
Add to New Space
USABILITY TESTING
Discovering new perspectives
Through five rounds of iteration, I interviewed a diverse group of users - including those who had never used Perplexity, users familiar with other AI tools like ChatGPT, and experienced Perplexity users - to ensure the design remained intuitive and user-friendly for both new and returning users.
Change #1
90% of users expressed interest in a feature that allows them to efficiently add a quote to a Space they have not yet created.
Change #2
I explored different visual styles for how saved snippets would appear. Through user testing, I found that most users preferred a cleaner look — some even referenced Notion’s quote styling as a reference. I also added a trash icon to clearly indicate that the quotes can be removed.
Change #3
Some users mentioned they would appreciate a confirmation after adding text to a Space. To address this, I introduced a new pop-up and tested different placements. I ultimately positioned it here, as it felt most intuitive during later rounds of user testing.
Final Success Metrics
ADDITIONAL FEATURE RECOMMENDATION
PDF Annotation
In the early stage of the project, each designer had a design sprint where we used our survey and interview data to create a feature. I came up with PDF annotation - a feature that allows students to annotate and underline keywords and sentences, tying back to the research problem.
THE PROBLEM
Students need an efficient way to annotate and highlight key information in PDFs on Perplexity.
In user interviews, students expressed interest in being able to highlight and underline text directly within Perplexity, describing it as a more efficient way to use AI.
DESIGN SOLUTION
Students need an efficient way to annotate and highlight key information in PDFs on Perplexity.
In user interviews, students expressed interest in being able to highlight and underline text directly within Perplexity, describing it as a more efficient way to use AI.
FINAL PRESENTATION
Take a look at our final presentation with more features we created, where we presented in front of the Perplexity product manager!
TAKEAWAYS
🌱 Good design reduces cognitive load.
Users are often juggling multiple tools and tasks — My job as a designer is to make the next action obvious, intuitive, and effortless. When flow is uninterrupted, engagement follows naturally.
🌱 Cross-functional teamwork drives product clarity.
Working closely with PMs and PMMs helped align design decisions with product goals, ensuring the Snippet feature wasn’t just functional — but also launched with the right messaging and purpose.
🌱 Test. Learn. Refine. Repeat.
Through rounds of usability testing, I saw firsthand how tiny interaction tweaks — like confirmation states or button placement — made the difference between hesitation and intuitive use.