Profile Builder
Early in my time at Jobcase, I redesigned profile setup into a modular, step-by-step flow that doubled completions and increased resume uploads by 60%. The data quality this unlocked became the foundation for the AI products I later led.
Company
Jobcase
Role
Product Designer
Platform
Web & Mobile
Methods
Usability Testing, Data Analysis
Background
Jobcase is a platform dedicated to empowering workers, with over 100 million members connecting to find jobs, share advice, and navigate the world of work. Workers use it to manage their job search and access a support-oriented community, while employers post roles, engage candidates, and manage hiring.
This case study focuses on improving the member experience, where a new profile builder was designed to help job seekers create more complete and effective profiles, making them more visible to employers and better matched to roles.
Problem
Incomplete profiles were limiting job matching, and members kept dropping off before finishing.
New members frequently abandoned their profiles before completion, leaving them less visible to employers and unable to access stronger job recommendations. The existing flow was fragmented, passive, and lacked a clear value narrative. There was no explanation of why completing a profile actually mattered, which meant members had no reason to push through the friction.
Hypothesis
"If I create a more intuitive, modular profile builder with clearer progress signals and motivational feedback, members will complete their profiles faster and with more accurate information, improving job matches for members and application quality for employers."
Research
Members needed to understand the value of each step before they'd bother completing it.
Data showed members most often abandoned profiles during work history and job interest entry. Qualitative feedback revealed the task felt like "busywork" with no clear payoff. Unmoderated usability tests with 9 participants across three Jobcase personas validated the solution direction. Key findings:
- Value messaging only landed when tied directly to job visibility or better recommendations
- Resume upload was strongly preferred over manual entry but was often missed without clear emphasis
- Progress cues and milestone recognition meaningfully increased motivation to continue
- Flexible entry options improved both completion rates and the accuracy of profile data
Solution
A guided, modular experience designed to increase completions and improve data quality.
Example flow: adding work experience
01
Designed for Scale
The modular structure was built to flex with the business. What counted as a complete profile could be redefined over time, with new fields or sections added without rebuilding the experience from scratch.
02
Progress, Made Visible
A progress indicator and Star Status system gave members a clear sense of how far they had come and what was left. Making progress visible reduced drop-off and gave members a reason to keep going.
03
Resume Upload & Parsing
Manual entry was the biggest drop-off point. Partnering with engineering, the team evaluated and integrated a more reliable resume parsing API, letting members upload a resume and instantly populate key profile fields, with a review step to confirm accuracy.
Results
0×
Profile completions after launching the new guided builder experience.
+0%
Fully filled profiles, leading to stronger job matches for members.
+0%
Resume uploads increased, improving employer-facing profile quality at scale.
Business Impact
Better profiles meant better inventory for both sides of the marketplace.
Complete profiles are Jobcase’s inventory quality. Every downstream system, from job matching to employer search to the AI coach, is only as good as the profile data underneath it. Doubling completions and lifting resume uploads 60% raised the quality of that inventory at 100M+ member scale: members got stronger matches, employers got more qualified applicants, and both sides of the marketplace flywheel spun faster. This was the earliest of the three projects here, and it’s why the later AI work was possible at all. The career coach and hiring assistant both ran on profile data this system produced, so when I moved into leading AI product design, I was building on infrastructure I had shaped myself.