Trackr

Project Background & Personal Journey

Trackr started as a personal initiative inspired by the challenges I faced during my own job search journey. Managing applications, resumes, interview updates, and deadlines across multiple platforms often felt overwhelming and unorganized. I wanted to create a solution that could simplify and centralize the entire process for job seekers.

As a solo designer and frontend developer, I independently designed and developed the platform from the ground up. My focus was on creating a clean, modern, and user-friendly experience that reduces complexity while helping users stay organized throughout their job search process.

Beyond application tracking, I envisioned Trackr as a scalable career support platform with intelligent productivity tools. This led to the integration of features such as ATS analysis, resume optimization, resume building, and AI-powered cover letter generation, with future plans to expand into a fully AI-driven job assistant ecosystem.

Research

During the research phase, I explored how modern job seekers currently manage their applications and analyzed platforms such as Teal, Huntr, LinkedIn Jobs, and Notion-based job trackers. These platforms provided useful tracking and resume optimization features, but many solutions still required users to switch between multiple tools for application tracking, resume building, document management, and AI-based optimization.

I also studied common pain points experienced by students and professionals during the job search process. Users often struggled with tracking application statuses, managing different resume versions, remembering deadlines, and handling repetitive manual tasks across multiple platforms. Most existing tools focused only on one part of the workflow instead of providing a unified experience.

These insights helped shape Trackr into an all-in-one platform focused on simplicity, organization, and productivity. The research phase strongly influenced the decision to combine job tracking, ATS analysis, resume optimization, and AI-powered career tools into a single scalable ecosystem designed to reduce complexity and improve the overall user experience.

User Surveys & Interviews

To better understand how users manage job applications and interact with existing tracking systems, I conducted a combination of online surveys and user interviews with students, recent graduates, and active job seekers. The research focused on identifying workflow pain points, tracking behavior, and expectations for automation and organization tools during the job search process.

Survey Overview

Key Survey Findings

User Interviews

I conducted one-on-one interviews to better understand user frustrations, motivations, and workflow challenges during the job search journey.

Key Takeaways

Card Sorting & Affinity Mapping

To better understand how users mentally organize job application workflows, I conducted card sorting and affinity mapping activities based on insights collected during surveys and interviews. These exercises helped identify how users grouped features related to application tracking, document management, interview progress, and automation tools. By clustering similar behaviors and expectations into meaningful themes, I was able to simplify the platform structure and improve overall usability.

The findings played an important role in designing a more intuitive information architecture for Trackr. They helped prioritize core features, reduce unnecessary complexity, and create clearer navigation flows aligned with real user expectations and behaviors during the job search process.

Meet the Users: Personas, Task Flows & User Journeys

Before starting the wireframing process, I explored communities and platforms where job seekers actively discuss their application experiences, career planning strategies, and productivity workflows. This included browsing job search communities, LinkedIn discussions, Reddit forums, and productivity-focused platforms to understand how users currently manage applications, resumes, and interview tracking.

By observing real user behaviors and workflow patterns, I gained deeper insight into the frustrations users face during the job search journey. Many users struggled with scattered tools, poor organization, repetitive manual tracking, and a lack of visibility into their application progress. Understanding these behaviors helped me identify not only what users needed, but also the motivations and emotions behind their actions.

These insights allowed me to build realistic personas representing different types of job seekers and professionals. Based on their goals, frustrations, and behaviors, I developed user journeys and task flows to ensure the platform delivers a smoother, more intuitive, and productivity-focused experience.

The research insights helped me define 3 primary personas:

Exploration & Ideation

During the exploration phase, I studied how users interact with job tracking and productivity platforms in real-world scenarios. Based on research insights, I explored multiple layout structures, navigation patterns, and dashboard concepts to create a more intuitive and organized experience.

I experimented with card-based layouts, table views, workflow-focused navigation, and minimal interface designs to improve usability and reduce complexity. Special focus was given to visual hierarchy, accessibility, and faster access to important features such as application tracking, resume tools, and AI-powered workflows.

The ideation process also helped shape future AI-driven experiences including ATS analysis, resume optimization, and automated status updates, ensuring the platform remains scalable and adaptable for future growth.

Workflow

The Trackr workflow was designed to create a smooth and organized experience for users throughout their job search journey. The platform guides users from onboarding to application tracking and career optimization through a centralized and intuitive workflow structure.