This project aims to develop an AI-driven customized cover letter generator for healthcare professionals, including but not limited to Nurse Practitioners, Physicians, Physician Assistants, etc. Here is what I contributed:
- Created detailed wireframes and high-fidelity interactive prototypes
- Generated a user test script and analyzed testing results
- Collaborated with product manager, UX designers, engineers to bring my design to life
- Presented my design process to company-wide employee resource group
1200 visitors in the first 6 months of release.
A few months post-release, the generator experienced a 175% increase in users, marking the highest growth spike within the first year of release.
This product was a part of Health eCareers new ‘Innovations Lab’, a strategic initiative aimed at reimagining the job search experience through cutting-edge technology.
Product Designer
UX Lead
Product Manager
2 Developers
Visual Design
Interaction Design
Prototyping
12 weeks (September to December 2023)
Overview
In today's competitive job market, standing out against competition is more difficult than ever.
With the number of applicants out there, hiring teams have less time to sort through cover letters that are either too long or boring, and need to find one that captures their attention. Writing a cover letter that stands out is time-consuming and requires a deep understanding of the job requirements and the candidate's skills and experiences. Additionally, it's challenging to balance the need to showcase the candidate's qualifications with a persuasive and professional tone. As a result, job seekers may miss out on job opportunities due to poorly written or generic cover letters.
Solution
Introducing, the AI Cover Letter Generator
Goals:
- Streamline the cover letter writing process and save valuable time
- Help applicants stand out during their job search
- Come up with an innovative tool to retain Health eCareers’ market competitiveness and the value of their platform against other job seeking platforms.
Design Considerations
How do we use AI as a guide, without overrelying on it?
To provide job seekers with more control over their generated cover letter, the generator offers several personalization options to tailor each cover letter according to the job seeker's preferences and the specific job posting. Some key features:
Enter job specific details to tailor the cover letter for a particular job posting. The system incorporates key words and phrases from the job posting, increasing the likelihood for their application to be seen by the hiring team.
Customize the generated cover letter by desired length, tone of voice, and writing style to ensure that the cover letter aligns with their personality.
Seamlessly incorporate information from your resume into the cover letters. The system automatically extracts details such as relevant work experience, education, and skills.
User Testing
Participants are hesitant but open to creating new cover letters and evaluating the best one.
I worked with the UX Lead to run an unmoderated user test on my high-fidelity prototype with 10 participants who were Physician Assistants, Registered Nurses, Obstetrician, and Nurse Practitioners, with job experiences of up to 20 years of experience.
Post-Release Testing
- There is a misunderstanding of the purpose of the cover letter generator, which is to tailor one’s cover letter to a specific job posting.
- Participants want to be able to include personalized options within their generated cover letters.
Post Project Reflections
- Designing with generative artificial intelligence involves understanding the technical system before starting any design work.
- I learned how to discern valuable feedback, prioritize findings, and transform research findings into actionable changes.
- A challenge I faced was finding the right balance between automation and personalization.
- Presenting and convincing others about the importance of the product is also equally as important as creating the design.
- If I had enough time to continue working on this project, I would… track metrics such as time on task and conversion rates to identify areas for design improvements in the next iteration, and conduct a longitudinal study to see the correlation between generated cover letters and hiring rates.
Try the generator!