Timeline
June 2023-Sept 2023
Team
1 Product Manager, 5 UX Designers, 1 UX Researchers, 2 Developers
My Role
UX Design, Web Design, UX Research
Tools Used
Figma
AfterEffects
Problem
Job seekers are often frustrated by manually matching their job experiences and company preferences when searching for startup or medium-sized enterprise (SME) jobs in the US market.
Goal
During the 10 weeks, we were given the goal to launch an AI-powered B2C recruitment platform that is horizontal sales focused, aiming to help candidates find the best job at startups and small-medium enterprises (SMEs) in the US.
Impact
We presented the interactive prototype and pitch deck to Harvard Innovation Labs and Spark Grants, successfully securing funding and initiating the implementation of the product. MVP will be launching in Q1 2024.
Solution
An AI-powered unified and personalized job seeking platform bridges the gap between job seekers and recruiters, ensuring a transparent process for job matching, applying, and tracking.
Final Outcome
Instant Keyword Highlight on Job Description
Auto-turned on Keyword Analysis, highlight key information from job description
Company Insights In One Glance
Most commented employee reviews for each company
Summarize growth potential, Company culture
AI Resume Optimization Tool
Tailored to each job role
Categorized to Grammar, Formatting, Job keywords matching, and AI rephrasing
Chatbot Help for Tracking Application
Manage candidate’s job application/ interview status
Organized in one place
Research
Survey—Target Users and Needs
We conducted user surveys to gain insights into the sales candidates' job search journey within the startup/SME sector, aiming to identify challenges, opportunities, and user needs in the recruitment process.
Insight 3
Candidates want more direct feedbacks from the recruiters about their job applications.
Insight 1
Users feel that it takes too long to finish an application
From 94 Screening Surveys, we found that:
Insight 2
Users need a keyword filter function to help them match a job more accurately
1:1 Interview—Applicants' Painpoints
After interviewing 7 job seekers, we arrived at key insights using affinity diagramming. Most of them struggle with job matching accuracy and lengthy application
User's Quote
“I spend an insane amount of time on viewing job descriptions, changing resume, filling out the application just for 1 job”
(Paticipant 1, intermediate level)
“Sometimes the job link leads to the company website to fill out extra information”
（Participant 2, mid level)
Key Insights
Optimized Filtering
for Various Needs
User need a keyword filter function to help them match a job more accurately
Guidance and
Feedback
Candidates want more direct feedbacks from the recruiters about their job applications.
AI Efficiency
User needs help on selecting desired salary and position, and reduce labor intensive work
Focus Insight for our team
Persona
Ideation
Map Users Pain Points with Behaviors
Using a user journey map, we were able to clarify each pain point and provide strong recommendations based on their emotions and contexts.
Redefined HMW
"How might we create an enhanced job-seeking platform that not only enables sales candidates to swiftly find their ideal job matches but also facilitates seamless communication with recruiters through AI-powered capabilities?"
Brainstorming: What features should be included?
We did brainstorm to come up with several solutions to elevate the job-seeking experience, and used 2x2 Matrix to evaluate our ideas by automatic and scalability.
Down Selection: Narrow Down key features
We have voted for 3 best design solutions following the principles of accessibility and efficiency.
Keyword highlight
Highlight key information from job description
AI-powered
resume editing tool
Customize candidate’s resume toward each position
AI Chatbot
Answer any questions candidates have
User Flow:
What are possible ways to elevate the job seeking process?
We worked on the Highlighting Job Descriptions, Resume Editing Tool and Ai Chatbot based on down-selction.
3. Prototype
Key Design Exploration-Sketching Main Flow
After creating user flow, I created mid-fidelity wireframes after quick sketches to gather feedback and ideas from clients. I led the design for the Resume Editing Page and Job Listing Page.
Resume Editing Page
Highlight Improvement
AI help users revise content based on job role requirements
Efficient Accept Suggestion
Accept all suggestions in one click
Various Editing Opitions
Save Time for Users checking resumes repetiviely
AI Suggestion
Quickly view current & upcoming tasks for the week
Job Listing Page
Job&Company Preference Filter
Tailor to a variety of needs for applicants
AI Chatbot
AI Tool that help users schedule interview, get interview tips and guidance.
Job Detail&Company Information Overview
Overview for Job Role and Company Insights
Smart Highlight Job Description
Highlight the key information and save time for users
Job Card
Display Job matching rate and quick view tags
Iteration
Usability Testing and Improving
We conducted A/B Testings and Discovery tests with 15 Users. The testing goals are:
Evaluate Flow Clarity
Identify Design Preferences
Assess Visual Perception
Iteration 1- Company Insights
After
Before
Users find slider label filter hard to drag to a specific value
Radar diagram’s info is illegible for users, and detail company information is missing
Job&Company Filter with specific range of value is prioritized for user
An individual section Polaris Insight is created, eg. company growth opportunities(low, medium, high)
Iteration 2- Resume
Affordance: Users cannot view all the problem in one page&need to expand each category
Over trust in AI: omit the situation where users want to modify themselves
Before
After
Menu Bar with clearer options:
let users decide, switch between categories easier
Compare content and Regenerate button, let user decide which resume version is better
Design System
Title Large - Roboto Regular 22/28 . 0
Title Medium - Roboto Medium 16/24 . +0.15
Title Small - Roboto Medium 14/20 . +0.1
Label Large - Roboto Medium 14/20 . +0.1
Label Medium - Roboto Medium 12/16 . +0.5
Label Small - Roboto Medium 11/16 . +0.5
Headline Large - Roboto 32/40 . 0
Headline Medium - Roboto 28/36 . 0
Headline Small - Roboto 24/32 . 0
Body Large - Roboto 16/24 . +0.5
Body Medium - Roboto 14/20 . +0.25
Body Small - Roboto 12/16 . +0.4
Display Large - 57/64
Display Medium - 45/52
Display Small - 36/44
#1F2555
#2A347A
#3B4AB7
#707CCC
#E9EBF8
Branding Colors
Text Colors
#28292A
#3C3C3E
#94969D
#C4C6D0
Background Color
#E8E9F1
#F5F5F5
#F8F9FB
Button & Highlight
#FF8600
#C9F1E8
#FFAB4E
#EE7C00
Reflection
What I learned…
User-Centric Empathy
Immersed in UX research, I empathized profoundly with the diverse challenges users encountered throughout the job application process. This empathy became the guiding force, directing our efforts to create a solution that eased the frustrations arising from aligning job experiences with company preferences.
Effective Communication with Developers
When conveying requirements to developers, it's imperative to evaluate the feasibility of design, features, and user requisites. Since I was woking on developing the Resume Editing feature, I always confirm with the developers whether the feature could be realized or not. While my proficiency in front-end programming allows for validation of website layout implementation, effective communication and collaboration with developers are essential to verify the viability of more sophisticated elements such as AI, large language models (LLM), or intricate language training models.
Prioritization is Paramount
I realized the criticality of prioritizing tasks for the team to accelerate and focus on the right objectives. Establishing timelines and structured decision-making processes were crucial amidst collaborative discussions with other UX designers.