top of page
Group 777.png
Indiana University Logo
Jobbox Logo

Improving Job Tracking with an AI Powered Kanban Board style job application tracking system for applicants

 UX Research / Prototyping /  Testing

Client/Firm

Indiana University

Role

UX Designer

Timeline

2 months

Team Size

1

Jobbox Hero Image 1.png

Project Snapshot

  • Reviewed and redesigned an existing platform, JobBox, to streamline job tracking by converting email alerts into a Kanban-style dashboard with AI-powered suggestions.

​

  • Conducted research through exemplar analysis and mapped user journeys to understand the pain points in current job application workflows.

​

  • Prototyped and tested iteratively, from paper sketches to high-fidelity designs, incorporating user feedback throughout.

​​

  • Prioritized usability, personalization, and visual organization to reduce cognitive load and improve user control over the application process, scoring 100% as an academic score.

Discovery

Problem Statement

How do we redesign Jobbox's tracking feature-set to help users efficiently manage their applications in a personalized and structured way without relying on scattered tools, manual spreadsheets, or cluttered inboxes?

WHY IS THIS A PROBLEM?

For many job seekers, the job application process is chaotic. Emails from job boards pile up, spreadsheets quickly become outdated, and follow-ups often fall through the cracks. From my research, I found the below.

​

  • Most users rely on makeshift systems like Excel or notes apps to track job leads, which lack automation or reminders.

​​

  • Email-based job alerts are overwhelming and often not organized around personal skills or interests.

​​

  • Users struggle with remembering which jobs they’ve applied to, which require action, or what their next steps are.

​​

  • Existing tools rarely encourage reflection or provide motivation throughout the job search.

​​

JobBox aims to transform this process by using the email updates from several job search websites in the user's inbox into a tabular format. Where it had room for improvement as a platform, was allowing users to effectively track and manage those jobs. This redesign focused on turning cluttered inboxes into an actionable Kanban board, enriched with AI-driven recommendations, smart nudges, and clear visual hierarchy. The goal is to reduce cognitive load and give users clarity, momentum, and confidence.

EXEMPLAR REVIEW & CONCEPTUALIZATION

I examined how leading platforms handled job discovery, task tracking, and personalized organization. These exemplars grounded the redesign strategy and feature set:

image 148.png

LinkedIn

LinkedIn tracks applicant skills and compares them with job requirements to recommend best-fit opportunities. A skill-matching system could help users prioritize applications by identifying jobs where they have the highest chance of success.

image 149.png

Trello

Trello features an intuitive kanban board view with custom labels. Implementing customizable job status categories in a Kanban-style board would allow users to tailor their job tracking to their personal workflow.

image 7.png

Zoho Recruit

Zoho Recruit uses AI to scan applicants and assign a percentage-based ranking based on their profile. An AI-driven recommendation system which works with the system could help job seekers assess which postings to prioritize.

image 150.png

Excel

Excel enables manual job tracking with customizable spreadsheets. Many job seekers use Excel for tracking due to its customizability. Adding custom tags could offer similar flexibility while maintaining a familiar structure.

USER INTERVIEWS & PERSONA DEVELOPMENT

To ground my redesign in real-world needs, I conducted informal interviews with job seekers at various stages such as college students, recent graduates, and early-career professionals. My goal was to uncover how people currently manage the job hunt, what tools they use, and where their frustrations arise.

​

One of the most common themes was email overload. Participants described how job alerts from different platforms piled up in their inboxes, leading to disorganization and stress. Many relied on Excel sheets, Notion boards, or handwritten lists to track applications, but these systems often fell apart due to a lack of reminders or structure. A few people admitted they missed deadlines simply because they forgot where they left off.

"There’s no way for me to see where I am with each application unless I check five different places"

"I have used jobbox, but I still have to have a separate google sheet to complete my application"

These insights shaped my central persona: Ryan, a design professional who recently lost his job. Ryan’s story reflected the emotional arc many users go through including shock, overwhelm, and eventual progress. His experience helped me focus on the need for automatic organization, gentle in-feed prompts, and clear visual indicators of progress.

Journey Map.png

By mapping Ryan’s journey, I ensured that JobBox aligned with user expectations and emotional needs. His persona stayed central to my design process, helping me make decisions that prioritized usability, motivation, and clarity throughout the experience.

Overview

PROJECT OVERVIEW

JobBox was developed as a review and redesign project for INFO-H-564: Prototyping for Interactive Systems in collaboration with the platform Jobbox.cc. The goal was to improve an existing platform that helps users manage job applications by turning cluttered job alert emails into a centralized tracking system. Users often face information overload and fragmented tools when applying for jobs. JobBox addresses this with a clear visual interface, AI-powered suggestions, and smart nudges to organize and streamline the process.
 

This project explored the end-to-end user experience, from receiving job alerts to saving opportunities, tracking progress, and updating statuses. The design process included low, mid, and high-fidelity prototyping, backed by user feedback at each stage. The result was a cohesive, personalized system that reduces friction and increases clarity during the job search.

CLIENT OVERVIEW

This project was completed in collaboration with the team behind JobBox (jobbox.cc), who supported the academic redesign through feedback sessions and . Ryan Kaminsky, the creator of Jobbox, provided insights into the platform’s goals and user needs. While conducted within an academic context at Indiana University, the redesign was informed by real-world perspectives and client interaction. Our target users included college students, recent graduates, and job seekers navigating high email volume and disorganized job pipelines.

MY ROLE

As this was an individual project, I performed end-to-end redesign of JobBox, from research and exemplar analysis to prototyping and usability testing. I mapped user journeys, built low- to high-fidelity designs, and planned the usability testing strategy. I also focused on developing interaction flows and alternate pathways to ensure accessibility and flexibility.

 

My background in enterprise systems and UX helped guide the redesign to balance structure with adaptability.

TOOLS & PLATFORMS

🛠️

Core Platforms

Figma
After Effects

🧠

User Research

User Interviews
Exemplars

👨‍💻

Design

Figma
Paper Prototypes

✅

Testing

Test Scripts
Excel

Prototyping & Testing

I followed an iterative design process, building low-, mid-, and high-fidelity prototypes that were each tested with users to validate design choices and uncover areas for improvement. At every stage, I focused on clarity, ease of navigation, and reducing the mental load associated with job tracking.

LOW FIDELITY PROTOTYPING

The paper prototype tested core flows like saving a job, updating status, and editing preferences. Early feedback confirmed the Kanban layout was intuitive, and users appreciated being nudged to complete their profile from within the job feed. However, they wanted more control over categorizing jobs and requested space to add personal notes. Metrics from this round showed strong task success (100%) and average satisfaction scores of 4.25 out of 5.

Low Fidelity.png

MID FIDELITY PROTOTYPING

Using Figma, I built an interactive prototype that introduced drag-and-drop functionality, detailed job views, and multiple entry points for editing. Users completed tasks faster and with fewer clarifying questions. One key takeaway was the need for better onboarding or visual cue, where some users weren’t sure what certain icons or sections represented. Task completion again held at 100%, with satisfaction scores rising to an average of 4.42.

Positive findings

  • Users found the drag-and-drop interface satisfying and intuitive, allowing them to update statuses without extra clicks.

  • Having both a Kanban and detailed view gave users control and flexibility over how they managed job information.

  • Users appreciated being able to access profile settings or edit preferences from different parts of the interface, reducing backtracking.

Areas for Improvement

  • Some users were confused by icons as well as the layout during the onboarding, which was unaltered from the initial design. Multiple users noted that they didn’t fully understand the platform’s capabilities at first glance. These instances highlighted a need for redesign in the onboarding process.

  • In some places, users weren’t sure whether to act from the feed or detail view, highlighting a need for clearer guidance on where to take action.

HIGH FIDELITY PROTOTYPING

Building on mid-fidelity feedback, I approached the high-fidelity prototype with a focus on onboarding clarity, improved filtering, and contextual guidance. The goal was to refine the experience without adding friction, addressing areas where users had previously felt uncertain or missed key actions. I introduced visual polish, emphasizing ease, momentum, and clarity at every stage.

High Fidelity Demo
High Fidelity.png

Outcomes

4.42 / 5
User Satisfaction Score

Users consistently rated the experience highly across all testing rounds, with the high-fidelity version averaging a 4.42 satisfaction score. The improved clarity, smoother task flow, and added guidance features were key contributors to this strong reception.

100%
Task Completion Rate

Every participant in both the mid and high-fidelity tests completed their tasks successfully. This metric reflected the system’s overall intuitiveness and the effectiveness of its progressive improvements in usability.

While my background in enterprise tools gave me a foundation in workflows and efficiency, this project challenged me to center design around clarity, momentum, and empathy. I learned how small nudges, visual hierarchy, and flexible interactions can reduce cognitive load in overwhelming contexts like job seeking. Above all, it deepened my confidence in designing tools that feel both useful and human

20250505_202144-EDIT.jpg

Check out this Case Study Next!

Thumbnail 6.png

or

Design

EXPLORATION & IDEATION

I structured the JobBox experience around three key phases: discovering job leads, organizing progress, and achieving closure through follow-ups and offers. These stages helped me anchor the design decisions around real user behavior and pain points.

​

  • Discover & Navigate – Users start by signing in through Gmail, which automatically pulls job-related emails. From there, they receive AI-powered job recommendations based on their skills and preferences. Job leads are displayed in a scrollable feed and can be saved into the Kanban board with a single click or by dragging. This phase is designed to reduce friction and eliminate the need to manually copy-paste job details.

​

  • Organize & Track – Once jobs are saved, users can update their statuses using a drag-and-drop Kanban interface. I created alternate pathways like an editable detail view and embedded prompts within the feed to help users manage their search without breaking their flow. This stage helps users maintain momentum, see their progress, and avoid duplicate applications.

​

  • Follow Up & Personalize– As users complete applications or land interviews, they receive automated nudges for follow-ups and to build their profile in Jobbox for better recommendations.

​

Based on that I sketched out the flow of interactions and key elements I wanted to focus on for this redesign.

Initial Sketches.png

KEY IDEAS AND FEATURES

The core of the JobBox redesign is built around three interconnected systems:

Smarter Feed.png

The Smarter Feed

The JobBox feed surfaces jobs pulled from email and ranks them based on skill match, location, and past activity. Inline prompts nudge users to update their profile, follow up, or complete key actions, turning the feed into a personalized dashboard for job discovery and engagement.

Customizable Kanban Board

Users manage their job search visually through a drag-and-drop Kanban board with customizable columns like Saved, Applied, and Offer. The board helps reduce clutter and makes it easy to track status at a glance.

Customizable Kanban.png
Detailed View.png

Detailed Application View

Each job opens into a detailed view where users can add notes, upload documents, and categorize jobs. It centralizes job information and simplifies follow-ups without needing to revisit the original email.

Together, these features made JobBox feel both powerful and approachable. I focused on building a system that felt like a natural extension of tools users already relied on in the existing system while layering in intelligence and structure to reduce effort. With a clear user flow and flexible interaction options, the platform supported both casual and committed job seekers, helping them stay focused, organized, and motivated throughout their search.

bottom of page