Design LinkedIn Mentorship Experience
Timeline
Mar 2025 (7 Days)
Team
Individual
Type
Design Challenge
Tool
Figma
Research
Understanding the problems through interviews with mentors and mentees
To understand the problem, I conducted 30-minute semi-structured user interviews with 3 mentors and 3 mentees to identify their pain points regarding mentorship. In the interviews, I asked about their experiences across three key scenarios: discovering, connecting, and scheduling.
Too many options can be overwhelming
"So many people on LinkedIn, I'll be overwhelmed trying to find the right match among so many options."
Referrals feel more trustworthy
“If my friend refers me a mentor, it will be reliable for me.”
Back-and-forth communication is frustrating
"After too much back-and-forth trying to book a time, the conversation dies out."
Findings about mentees
Finding a good matching is time-consuming
"I need to review many materials and talk to mentees to truly understand the needs."
Mentees sometimes ask vague questions
"I often receive broad questions like, 'What advice do you have?' without any specific context."
Booking is not efficient
"Figuring out a time that works for both me and my mentee isn’t efficient – there’s too much back-and-forth."
Findings about mentors
Refine the scope
Focusing on long-term mentorship for deeper value and business potential
☕️ Coffee Chat
Free, short, informal one-time conversation
Low commitment
Less structured; more casual
🤝 Long term mentorship
Paid, ongoing relationship
Higher commitment
Structured with goal setting, feedback loops
PERSONA
Who are our target users?
KEY PAIN POINTS
Synthesizing the research, here are three key pain points:
🔍
Hard to find right mentors efficiently
⌨️
Hard to build trust before payment
️🗓️
Struggle to book efficiently
Ideation
I brainstormed and sketched out features
KEY FEATURES
Here are the key features:
🔍
Hard to find right mentors efficiently
⌨️
Hard to build trust before payment
️🗓️
Struggle to book efficiently
AI-powered matching + improved search and filter experience
Trust-building through social proof and free trial sessions
Centralized dashboard to streamline session management
USER FLOW
Mapped out the journey to define the scope
Due to time limits, I will focus on the journey from discovery to trial; the formal mentorship phase is not covered.
goal 1
Help mentees discover mentors efficiently
two ENTRY POINTS
Entry point 1: navigation bar
Adding an entry point to the navigation bar makes the "Mentorship" functionality more prominent, ensuring it is easily discoverable by users. Also, it ensures quicker navigation to "Mentorship" dashboard. After entering "Mentorship" module, users can search for mentors.
Entry point 2: global search
This supports users who may not be aware of the Mentorship module. When they search for other information, they can also discover the mentorship filter. This increases engagement by presenting mentorship as a natural extension of a user's job search or networking behavior, thus enhancing discoverability organically.
"Mentorship" as a filter on search result page
Search result design
A two-column layout that enables efficient browsing
The left column displays search results, while the right shows profile details, allowing users to browse mentors efficiently without opening a new window. This helps mentees quickly scan and narrow down options, reducing the effort of constantly opening and closing profiles.
Determine mentor details through a quick ranking survey
By looking into competitors such as ADPList and MentorCruise, I gained a basic understanding of the information typically included on a mentor profile page. I also discovered that additional details from interviews, such as mentorship style and shared interests, are valuable for decision-making.
To rank their importance, I conducted a quick survey with 50 mentees, asking them to rank these criteria based on importance. I then incorporated the results into the design of mentor details.
Ranking Survey Result
→
Mentor details
AI-Powred MATCHING
Leveraging AI for smarter discovery
Beyond traditional search and filter, I also explored ways to leverage AI to make the discovery experience smarter and faster.
For User
More personalized & efficient matching
AI can analyze users’ profiles, experiences, skills, and preferences to recommend matches
For LinkedIn
Add value to premium & drive adoption
LinkedIn AI is one of Premium's benefits, and offering AI features can drive user adoption
AI-powered matching badges to drive mentorship trial sign-ups
AI-powered matching questionnaire for more accurate matching
Why a questionnaire instead of natural language input? I explored two AI-powered matching approaches: a structured questionnaire and flexible natural language input. After testing with 3 users, all preferred a questionnaire, believing well-crafted questions ensure more accurate matches and help consider the aspects they haven't considered when looking for mentors.
Questionnaire 👍👍👍
"These questions should enable the algorithm to provide the optimal answer." — User Feedback
Natural Language Input
"Don't ask me to think about what to type." — User Feedback
AI-powered questionnaire
goal 2
Enhance a reliable connection before payment
Mentorship Network
Create credibility through social proof
In interviews, mentees mentioned that referrals can help establish mentorship relationships. They want to know whether a mentor has experience working with others from similar backgrounds. To support this, I designed a feature that shows past mentees from your network who have worked with the mentor. This encourages informal reviews and helps build trust.
Show a mentor’s past mentees in your network
Encourage reach out to past mentees to gain insights
FREE TRIAL
Free trial benefits both mentors and mentees by helping them determine if it’s a good fit
For mentees
Gain insight into mentors' capabilities and style before committing to a paid plan
For mentors
Request documents and set up questions to better understand mentees' needs
Free trial application flow
goal 3
Manage bookings efficiently
Key DESIGN DECISIONS
Get mentorship application updates via two channels
After submitting trial applications, mentors will have five business days to respond to mentees. Email and LinkedIn will be the two touchpoints used to inform mentees of the results.
LinkedIn Notification
Key DESIGN DECISIONS
Manage mentorship sessions and applications within a centralized dashboard
Mentees can track the progress of their trial application, including sessions under review and those already approved. In the "Your Move" section, mentees can reschedule if the proposed time doesn't work and freely message mentors with any questions during the trial period. In the "Under Review" section, to reduce uncertainty, a message is shown: "Your mentor will get back to you within 3 business days.
NEXT STEPS
Test free trial mode and iterate
The free trial mode is designed to encourage mentees to try a mentor and for mentors to use this time to better understand the mentee, giving both sides the opportunity to determine whether it’s a good fit. However, the current trial mode is based on limited user feedback. If I had more time, I would test whether this is an effective approach, whether the 7-day duration is optimal, and explore more efficient ways to facilitate mutual understanding.
Explore visuals of mentor profile
The mentor profile is text-heavy and contains a lot of important information for decision-making. If I had more time, I would explore ways to enhance readability.
REFLECTIONS
Find the right balance between research and design
When reflecting, I realized that I spent too much time on research. While research is valuable, I need to better balance insight gathering with forward progress—making reasonable assumptions and refining through iteration. I also learned to narrow scope, as exploring too many paths slows decisions and dilutes focus. Going forward, I’ll set clearer constraints and prioritize key scenarios.