Boldvue is creating a digital platform that helps job candidates improve their interviewing ability and earn their dream job. I joined the team to increase engagement and retention with an updated user experience.
2018 - 2019
product strategy
ux design
visual design
The Product
On the original Boldvue website, job candidates would record videos of themselves answering interview questions and post them on the site. Community members would then rate the response and comment with feedback.
The product was intended to be used cooperatively by college classes, led by a professor. The professor would invite all students to a group, and then they could work together to improve each other’s responses.
The Problem
In testing the product with several university classes, the team recognized the following trends:
User engagement was dropping and some were leaving the platform altogether
Regular users found the platform exponentially less valuable as the network effect deteriorated
Quantitative Analysis
First, I evaluated the current Boldvue site to see what it could teach me about the user experience. The following metrics proved to be enlightening (all values reflect mean values of Boldvue's private test group):
Video rating
Video length
Videos posted/user
In analyzing this data, I formed two hypotheses - users weren’t incentivized to leave reviews, and when they tried to leave a review it was time-consuming and ambiguous. I used these insights as a baseline for the rest of my research.
Contextual Interviews
In an effort to better understanding the experiences that job candidates were having while interviewing, I conducted contextual interviews with current Boldvue users, job candidates that were actively applying for jobs, and hiring gatekeepers (recruiters, hiring managers, etc.).

My intent was twofold — to understand how all actors currently felt and acted in the hiring process and to gain insight on what could improve. Combined with some valuable research that the Product Manager had recently conducted, I came to the following conclusions:
Fear of the unknown
According to the job candidates I spoke with, the greatest anxiety while preparing for an interview is the fear of the unknown.
Mentor Needed
The blind were leading the blind, and students felt that they needed a mentorneeded a knowledgable mentor to lead them along the hiring process.
Feedback was too difficult
Leaving feedback on a video took too long (average time spent watching and commenting was 7-10 minutes) and was ambiguous.
Little community involvement
Job candidates were hesitant to post videos because they didn't feel their classmates were bought in to using the product.
Primary User Persona
To make sure our solution was consistent with the experiences that job candidates were having, I pulled all of my data together and created a persona. Meet Jessie.
To make sure our solution was consistent with the experiences that job candidates were having, I pulled all of my data together and created a persona. Meet Jessie.
Jessie served as the (virtual) human embodiment of all of my data. In creating Jessie and looking forward I began discussing possible solutions with the team.
Same goal, new strategy
In analyzing the research results, it became apparent that if we were going to significantly help candidates improve their interviewing skills, we needed to reevaluate the product strategy. The initial product was designed as a content sharing platform, much like Youtube or Instagram.
However, the content sharing model didn’t incentivize feedback or provide the candidate with any plan for growth. Instead, we decided that we could better prepare job candidates by creating a deep learning environment where candidates could receive coaching, practice their skills, and perfect their interviewing.
A framework we could trust
Before I could redesign the app, I needed to identify a learning process that was proven to generate real growth among users. After some research, I decided to model my process after the deep learning cycle described by Daniel Coyle in his book The Talent Code.
Journey Mapping
To implement this deep learning model, we designed a simple loop in which candidates could learn, practice, evaluate, and re-practice. For this to be effective, we needed to make sure the community was strong and active.
I identified three strategic pillars that, together, would develop a collaborative environment for deep learning.
Powerful learning curriculum
A simple but effective learning curriculum that would provide job candidates with tips, resources, and expert examples.
Simple practice and feedback loop
Candidates can quickly record their answer practice and send it out to the community for review. Classmates then take a streamlined process to leave feedback in under 3 minutes.
A collaborative community
The community is continuously involved with subtle rewards of activity and accomplishment. Repracticing an answer and reviewing are given greater weight, as these are the two most important aspects of the learning/network loop.
We tested prototypes with a number of testing groups to validate the strategy and work out usability quirks. Eventually we arrived at a design that we could implement with confidence.
Design System
I built the Boldvue Design System to accommodate scalibility, so the team can continue to add content over time without needing drastic redesigns. The typography, color scheme, iconography, and use of illustrations were intended to be both professional, and compelling - essentially more buttoned up than candy crush, but more fun than LinkedIn.
A platform that meets job candidates where they are
My research showed that providing job candidates with powerful coaching, consistent feedback, and an engaging community could unlock a deep-learning experience that would drastically improve their ability to earn job offers. The final solution accomplishes this goal in the following ways:
Job-specific curriculum
Boldvue provides interview questions for different industries, jobs, and types of interviews so when job candidates go into an interview they know what questions to expect and they are prepared.

Expert coaching
Boldvue will coach a job candidate through each interview question, with tips, preparation tools, and expert examples.
Deep practice
The practice and feedback loop is the crown jewel of Boldvue, enabling candidates to gain significant insights from every mock interview that they conduct.
An engaging community
Collaboration is required as candidates can only reach certain benchmarks by helping their fellow students.