AI Cover Letter Generator
Role
Associate Product Designer
Team
1 UX Lead, 1 Product Manager, 2 Developers, 1 Product Designer (myself)
Company
Health eCareers, a job board for healthcare practitioners
Duration
16 weeks (September to December 2023)
WHAT I DID
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
Crafted high-fidelity interactive prototypes
Generated user test script and analyzed testing results
Presented prototype to stakeholders, and company wide employee resource group
1200 visitors in the first 6 months of release
In April, the generator experienced a 175% increase in users, marking the highest growth spike within the first year of release.
After my contract was over, I followed up with my Design Manager to learn how my design had contributed to the product’s impact.
In April 2024, Health eCareers announced the launch of its Innovations Lab, a strategic initiative aimed at reimagining the job search experience through cutting-edge technology. This milestone included the public unveiling of this AI Cover Letter Generator.
Exploring the Problem
Exploring the Problem
What's the problem?
Healthcare job seekers often struggle to write personalized and effective cover letters when applying for jobs.
Healthcare job seekers often struggle to write personalized and effective cover letters when applying for jobs.
In today's competitive job market, crafting a compelling cover letter is crucial for healthcare professionals seeking new opportunities.
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.
In today's competitive job market, crafting a compelling cover letter is crucial for healthcare professionals seeking new opportunities.
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.
How can we solve the issue?
The healthcare industry needs an automated solution for crafting customized cover letters.
The healthcare industry needs an automated solution for crafting customized cover letters.
We can use Artificial Intelligence to analyze a healthcare job seeker’s previous experiences and extract relevant skills and qualifications to generate a tailored cover letter for potential employers.
Goals:
Streamline the cover letter writing process and save healthcare professionals 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.
We can use Artificial Intelligence to analyze a healthcare job seeker’s previous experiences and extract relevant skills and qualifications to generate a tailored cover letter for potential employers.
Goals:
Streamline the cover letter writing process and save healthcare professionals 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.
What would this solution look like?
What would this solution look like?
Integration with Generative AI
Generative AI was utilized in this product to enhance the personalization and efficiency of creating tailored cover letters. By leveraging advanced AI technologies, the system can generate highly relevant, customized content that aligns with the job seeker's resume and the specific job posting.
User Flow
I mapped out a user flow to understand how a jobseeker might interact with the AI generator and to use it as a guide as I begin the design process.
Integration with Gen-AI
Generative AI was utilized in this product to enhance the personalization and efficiency of creating tailored cover letters. By leveraging advanced AI technologies, the system can generate highly relevant, customized content that aligns with the job seeker's resume and the specific job posting.
Creating the Design
Sketches
I incorporated elements from the current user flow and the design style of Health eCareers pages. I also drew upon my own experience using similar tools, such as online AI resume checkers, to inform the functionality and layout of the generator.
Wireframing
After a round of feedback on my designs with my UX Lead, I leveraged the Health eCareers Design System to refine my prototypes to align with our established brand guidelines and optimize the layout for improved usability.
This series of frames illustrates the user's journey while interacting with the generator, from discovering the generator -> customizing the final cover letter.
Personalization
Personalization
To provide job seekers with more control over their generated cover letter, this product enables job seekers to create a version that fits their personality and the requirements of the application. It offers several personalization options to to ensure that each cover letter is uniquely tailored to the job seeker's preferences and the specific job posting. Some key features:
tailor cover letters to individual job postings
offer customization options
incorporate user resume information
Personalization Feature #1: Tailoring cover letter to an individual job posting
Here, job seekers enter job specific details to tailor their 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.
Personalization Feature #2: Customization
Job seekers can customize their generated cover letter according to their preferences. They can specify the desired length, tone of voice, and writing style to ensure that the cover letter aligns with their personality and the job requirements.
Personalization Feature #3: Resume Upload
Job seekers can use this to seamlessly incorporate information from their resume into their cover letters. The system automatically extracts details such as relevant work experience, education, and skills.
Personalized download options
3 capabilities:
directly edit the cover letter
download in different formats
provide feedback
Creating the Design
User Testing
Testing Method
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.
User Test Questions:
What are the participant’s comfort levels and experiences with AI generators?
Do all the options currently provided in the cover letter generator make sense to job seekers and address their needs?
How would participants interact with the generator? Does it work as expected? What are some things they are satisfied with, and what do they dislike?
Key Insights
Insight 1
Participants find the cover letter generator intuitive and a valuable starting point for their job applications.
One participant even mentioned being surprised by the amount of effort required.
Implementation
No design changes were made at this stage. Rather, this helped us understand the product's effectiveness in addressing the original challenge of crafting personalized cover letters.
Insight 2
The value of the AI generator is unclear in how it might aid the job seeker's application process.
Implementation
No design changes were made at this stage. However, this feedback informed our efforts to enhance user understanding of the AI-driven features in future iterations of the product.
Insight 3
Participants want to compare different versions of the generated cover letter. However, restarting the process of generating a cover letter is time-consuming, posing a barrier for users.
Implementation
To address this need, we need to allow the user to generate their cover letter in a different style without restarting the entire process.
I presented these insights to the Product Manager, highlighting user feedback and the proposed solution to address the identified need. After a discussion and approval, a change based on insight 3 was incorporated into the cover letter generator. See the side-by-side comparison of the design iterations below:
Design Iteration #1 (Pre-usability testing)
Design Iteration #2 (Post-usability testing)
The new design includes the same customizing options users saw earlier in the process, providing a quicker way to make changes to their generated cover letter.
Post-Release Results
After the product was released, I conducted another unmoderated user test to gather evaluative user testing findings from healthcare professionals post-release. Because this was towards the end of my contract, I made the following recommendations for the next designer to iterate on my design:
Finding 1
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.
Recommendation
Add a line of instructions telling users to copy and paste job information from a real job posting they are interested in.
Finding 2
Participants want to be able to include personalized options within their generated cover letters.
Recommendation
Add an input box allowing users to highlight specific qualities that they believe are important to include in the generated cover letter.
Reflection
Designing with generative artificial intelligence involves understanding the technical system before starting any design work.
This approach helped me align my design approach with the system's capabilities and limitations.
I learned how to discern valuable feedback, prioritize findings, and transform research findings into actionable changes,
I gained hands-on experience with conducting user research, through crafting test scripts, analyzing interviews, and synthesizing interviews. Utilizing supporting clips from testers was a valuable way to strengthen my design changes and recommendations.
A challenge I faced was finding the right balance between automation and personalization.
It was important to give users the ability to gain ownership over their work, while taking advantage of the abilities of AI. To address this, I added customizing features to tailor each cover letter to individual experiences.
Presenting and convincing others about the importance of the product is also equally as important as creating the design.
I refined my ability to articulate design rationale and advocate for user needs within a cross-functional team when meeting with Product leads and Developers. By presenting my project progress at a company-wide UX working group meeting, which was created to bring UX teams together across the various subsidiaries at Everyday Health Group. A screenshot of my presentation is shown below!
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
Conduct a longitudinal study to see the correlation between generated cover letters and hiring rates
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.
User Test Questions:
What are the participant’s comfort levels and experiences with AI generators?
Do all the options currently provided in the cover letter generator make sense to job seekers and address their needs?
How would participants interact with the generator? Does it work as expected? What are some things they are satisfied with, and what do they dislike?
Testing Method
User Testing
Key Insights
Insight 1
Participants find the cover letter generator intuitive and a valuable starting point for their job applications.
Implementation
No design changes were made at this stage. Rather, this helped us understand the product's effectiveness in addressing the original challenge of crafting personalized cover letters.
Insight 2
The value of the AI generator is unclear in how it might aid the job seeker's application process.
Implementation
No design changes were made at this stage. However, this feedback informed our efforts to enhance user understanding of the AI-driven features in future iterations of the product.
Post-Release Results
After the product was released, I conducted another unmoderated user test to gather evaluative user testing findings from healthcare professionals post-release. Because this was towards the end of my contract, I made the following recommendations for the next designer to iterate on my design:
Finding 1
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.
Recommendation:
Add a line of instructions telling users to copy and paste job information from a real job posting they are interested in.
Finding 2
Participants want to be able to include personalized options within their generated cover letters.
Recommendation:
Add an input box allowing users to highlight specific qualities that they believe are important to include in the generated cover letter.
Reflection
Designing with generative artificial intelligence involves understanding the technical system before starting any design work.
This approach helped me align my design approach with the system's capabilities and limitations.
I learned how to discern valuable feedback, prioritize findings, and transform interview findings into actionable changes,
I gained hands-on experience with conducting user research, through crafting test scripts, analyzing interviews, and synthesizing interviews. Utilizing supporting clips from testers was a valuable way to strengthen my design changes and recommendations.
A challenge I faced was finding the right balance between automation and personalization.
It was important to give users the ability to gain ownership over their work, while taking advantage of the abilities of AI. To address this, I added customizing features to tailor each cover letter to individual experiences.
Presenting and convincing others about the importance of the product is also equally as important as creating the design.
I refined my ability to articulate design rationale and advocate for user needs within a cross-functional team when meeting with Product leads and Developers. By presenting my project progress at a company-wide UX working group meeting, which was created to bring UX teams together across the various subsidiaries at Everyday Health Group. A screenshot of my presentation is shown below!
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
Conduct a longitudinal study to see the correlation between generated cover letters and hiring rates
WHAT I DID
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
Crafted high-fidelity interactive prototypes
Generated user test script and analyzed testing results
Presented prototype to stakeholders, and company wide employee resource group
1200 visitors in the first 6 months of release
In April, the generator experienced a 175% increase in users, marking the highest growth spike within the first year of release.
After my contract was over, I followed up with my Design Manager to learn how my design had contributed to the product’s impact.
In April 2024, Health eCareers announced the launch of its Innovations Lab, a strategic initiative aimed at reimagining the job search experience through cutting-edge technology. This milestone included the public unveiling of this AI Cover Letter Generator.
1200 visitors in the first 6 months of release
In April, the generator experienced a 175% increase in users, marking the highest growth spike within the first year of release.
After my contract was over, I followed up with my Design Manager to learn how my design had contributed to the product’s impact.
In April 2024, Health eCareers announced the launch of its Innovations Lab, a strategic initiative aimed at reimagining the job search experience through cutting-edge technology. This milestone included the public unveiling of this AI Cover Letter Generator.
WHAT I DID
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
Crafted high-fidelity interactive prototypes
Generated user test script and analyzed testing results
Presented prototype to stakeholders, and company wide employee resource group
AI Cover Letter Generator
Role
Associate Product Designer
Team
1 UX Lead, 1 Product Manager, 2 Developers, 1 Product Designer (myself)
Company
Health eCareers, a job board for healthcare practitioners
Duration
16 weeks (September to December 2023)
AI Cover Letter Generator