Go back
Calyptus: Scaling from <10K to 120K Users
Leading the Product Design Turnaround that Drove 12X+ User Growth and Realigned Market Fit for a Recruitment Platform.
Project Context & Problem:
Before summer 2023, Calyptus was a buggy platform with <10k of users and a failed product-to-market fit. The team pivoted on its core hypothesis, and I was hired to lead the design and create a second MVP in 6 months for two user roles: candidates and recruiters.
Our goal: acquire 80,000 candidates after launch to attract more recruiters and companies to the app's commercial side. This case study focuses on the candidate-facing product.
My Role & Influence:
I owned the end-to-end product design, from user research to developer hand-off, throughout my time at Calyptus. I also led the branding update. This included improving the branding's visual and tone-of-voice languages, which contributed to 120k followers on LinkedIn and 6.8k on X. I collaborated closely with:
- Three co-founders
- A Product Manager (who mainly led the engineering team)
- Back-end and front-end engineers
User Pains I Worked to Solve:
Being Ignored: Users were often ghosted by recruiters or didn't get feedback after applying.
Slow Hiring: The process of finding a job took too much time.
Constant Proof: Users had to prove their skills and experience repeatedly.
Early Mismatches: It was hard to know early on if a company was a good fit, wasting time.
My Challenges in the Process:
Time & Budget Constraints: With minimal research and developers hurrying, I prioritized core flows and key screens, leaving extra states for later.
Minimal User Access: I had very little direct access to users, meaning minimal data on their wants, needs, or feedback during the process.
Simultaneously Designing for Two User Personas: This meant constantly switching focus between candidate and recruiter needs. I compensated for limited candidate research with external sources and used our internal recruitment team's experience for the recruiter side.
Balancing a Small Cross-functional Team: Working with co-founders, a Product Manager, and engineers, I had to balance listening with making independent decisions.
I learned to process feedback with an open mind, noting valid points, then taking time to analyze and respond. This helped me combine diverse perspectives with my own design insights, prioritize, and make decisions benefiting the project's top priority .
Sole Designer Advocacy: As the only design expert, I was responsible for advocating for product design. I presented my recent scope of work, outlining specific, logical arguments for or against particular decisions. This helped keep discussions factual, moving beyond emotions to focus on reason and logic.
Strategic Research & Insights
Initial Research
My initial research involved talking to 2 users from the previous product version and analyzing 3 other pre-conducted interviews to discover user pains. Because I couldn't talk to many users directly, I found information from other places:
- Case studies of successful recruiting products.
- Academic papers on candidate behavior
- Personal job hunting stories shared on LinkedIn.
Competitors Analysis
I also analyzed competitors. This revealed that the "match" feature, intended as our new version's core attractive element, was already used by 3 of 7 competitors. Based on this insight, we shifted our unique value proposition from emphasizing the matching feature to highlighting verified skills and experience.
Mapping Core Structure
Next, I mapped out the product's core structure by working on the user flow and information architecture, keeping the identified problems in mind and understanding the overall scope.
Ideation & Design Process:
I began designing wireframes section by section, iterating on ideas and providing clear visual explanations of the mechanics to developers. Wireframes for both candidate and recruiter personas were completed within ~6 weeks.
At the same time, because this version had a new product-market fit idea, and I was the only designer, I updated the company's branding. Based on this, I initiated work on a design system. This system ultimately reduced idea-to-hand-off time by at least 5 times and helped the front-end development team work 2x faster post-launch due to its reusability.
I then worked on UI and user-tested flows with internal team members, gathering feedback in Excel. While this system reduced the need for calls by 50% at least, it was flawed. During these tests, I encountered biases such as:
- Social Desirability (e.g., co-founders praising my work, and therefore It was challenging for me to continue upgrading the experience even when I felt it wasn't optimal).
- False-Consensus bias (common in small teams, where co-founders believed their experiences were universal). Using Hotjar later helped the team observe the fallacy of these beliefs.
Post-Release. Problems & My Solutions:
Onboarding Overload: The onboarding process, designed to gather basic user info for our matching algorithm, became excessively long (2 + 9 steps), leading to a significant Hotjar drop-off rate of ~60% and a profile completion rate of only 31%.
I shortened onboarding to 4 steps, made it appear in context, and showed it after giving immediate value - top job positions. This boosted 100% profile completion from 31% to 49%, reducing drop-off to ~25%.
Low Match Rates & Churn: Users experienced very low job matching rates, which discouraged them and contributed to high user churn.
Increasing profile completion also positively impacted the general match score. But the biggest gain came from removing "low match" labels, showing only the percentage.
Failed Verification Hypothesis: Our hypothesis that users would send requests to verify their experience (especially current workplace experience) failed, with only 28% completing verification.
I added self-experience verification, which increased the amount of experience verification from 28% to 65%, further impacting the general match score.
Result:
We exceeded the goal of 80k new users within 6 months post-release, reaching 90k, and then 120k new candidates within a couple of weeks. While the initial focus was on acquisition, future iterations would prioritize retention.
What I Would Do Differently:
I would have conducted user testing of the main flows with uninvolved users before release. Independent data would have gone a long way, problems being much cheaper to fix, and making it easier to move on from certain ideas early on.
I would have first worked on the recruiter side of the app to identify their pain points and fully integrate this information into the candidate site. This is because the candidate side is free, and all revenue and product-market fit success should ultimately come from the recruiter side. This approach caught up with the company two years later, forcing the team to downsize significantly and change the product-market fit hypothesis to attract more paying business customers.
Get in touch
I’m always interested in exploring new opportunities, collaborating, or exchanging ideas with like-minded individuals. Feel free to email me or connect on LinkedIn if you'd like to discuss an open product designer or ux/ui designer position or a potential project.