Product Design · Case Study

Removing friction from the hiring pipeline

Role
Product designer in a team of 4
Timeline
10 weeks
Tools
Figma, Miro, Claude
Domain
B2B · HR Tech
Final pipeline dashboard

Context

Understanding the problem

Hiring Managers and recruiters lack efficiency and standardized tools to select, evaluate, and manage candidates' application status throughout the hiring process. Due to a large volume of candidates, recruiters need to effectively manage communication, screening, and tracking across numerous applicants.

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Research

Listening to the people who hire

We interviewed 8 professionals across the hiring spectrum, from early-career recruiters to department heads.

Head of Talent
Lanai
Dept Head
Ernest Righetti HS
Recruiter
Octa
Hiring Manager
GoDaddy
Sr. SWE Manager
Google
Admin Support
University Housing
HR Professor
Cal Poly
HR Specialist
XYZ Graphics
8
Interviews
5
Usability tests
4
Key flows
10
Weeks

Core Need

A clear, shared view of where every candidate stands — accessible to everyone involved in the hiring decision

Ultimate Goal

Ensuring both the company's and the candidate's success. Finding a candidate that meets company needs and culture fit.

Pain Points

01Scheduling chaos
02No pipeline visibility
03Mismatched candidates
04Unconscious bias
05Stakeholder alignment

Ideation

Exploring the solution space

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Crazy 8s
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Solution Sketches

User Flow

Mapping the hiring journey

01Creating Job Inquiry
02Sourcing Candidates
03Screening
04Interview Rounds
05Team Review & Selection
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Usability Testing

Testing assumptions before committing to pixels

We tested low-fidelity prototypes with recruiters and hiring managers to understand how users think before designing how they work.

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Screen 1: Candidate list
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Screen 2: Candidate profile

Task given to participants

"Review candidate profiles and select one best-fit candidate to move to the interview stage."

Key Observations

Where users got stuck

Blocker

No clear way to select candidates

Users had no way to move a candidate to "selected." The action lacked any visual affordance.

Blocker

Dead-end on candidate profile

After opening a profile, users didn't know if they could select from there or had to go back.

Friction

Resume was non-negotiable

Both participants needed the full resume before evaluating. No summary was a substitute.

Friction

AI score lacked transparency

Users questioned what the score was based on. Trust required explainability.

Key Decisions

Making design decisions

Each finding from testing pointed to a design tradeoff. Here's what changed and why.

01

Multiple paths to select a candidate

Testing revealed users had no way to move candidates forward. Selection was added to both the list view and candidate profile, with clear visual affordances at each point.

Before
Before wireframe
After
After design
02

Resume embedded in the profile

Both participants refused to evaluate without seeing the full resume. Embedding it directly in the candidate profile keeps users in the evaluation context.

Before
Before wireframe
After
After design
03

AI score with visible reasoning

Users didn't trust a percentage without context. The score was expanded into a breakdown showing contributing factors so recruiters can evaluate the AI's judgment alongside their own.

Before
Before wireframe
After
After design

Design Details

Key interface decisions

Feature image
Pipeline status pills
Color-coded indicators on every card showing exactly where a candidate sits in the process.
Feature image
Candidate comparison
Side-by-side evaluation with aligned criteria, scores, and interviewer notes in parallel.
Feature image
Transparent AI scoring
Score expanded into contributing factors so recruiters can evaluate the AI alongside their own judgment.

Outcomes

Creating interactive prototypes

Screen
Job Creation
Screen
Candidate List
Screen
Candidate Profile
Screen
Comparison
Screen
Team Review
Screen
AI Evaluation
Screen
Job Creation
Screen
Candidate List
Screen
Candidate Profile
Screen
Comparison
Screen
Team Review
Screen
AI Evaluation
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Reflection

Process over tools

In the age of AI, spending time defining the problem and understanding context has become more valuable than time spent in Figma. Tools come and go, but strong foundations and solid process remain the same.