Datalynn

Background

The tech industry is constantly evolving, presenting job seekers with the challenge of aligning their skills with the demands of top companies. Traditional job preparation methods often fall short, lacking the targeted, practical resources needed to bridge the gap between aspiring tech professionals and their ideal roles.
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DataLynn identified this gap and sought to transform the job-seeking process through innovative AI-driven tools. This case study delves into the design and development of DataLynn's platform, with a focus on enhancing user experience (UX) at every stage of the job search journey.‍

Market research

As education levels rise and more international students enter the tech industry, career services are becoming essential. These services include skill training, resume writing, interview coaching, job placement, and networking.The number of university graduates is expected to grow from 137 million in 2013 to 300 million by 2030. In the U.S., there were 18.66 million college students in 2021, with international enrollment up 12% in the 2022/23 academic year.The U.S. career service industry, valued at $2.7 billion in 2022, grew by 4.5%. This indicates an increasing need for career support in tech.

Impacts and Results

Successful MVP Launch

Contributed to the design of DataLynn's MVP, resulting in a successful product launch that attracted USD 300k in initial investment and facilitated connections with over 15 venture capital firms for future funding.

Accelerated Design Efficiency

Contributed to developing a scalable design system that reduced design-to-development handoff times by 40%, significantly speeding up feature releases and product iterations.

User Research

To bridge the gap between users and job market expectations, we conducted interviews with 16 new graduates and 10 career switchers, and had insightful conversations with over 20 hiring managers, founders, and tech leads. This discovery phase was designed to help DataLynn's teams better understand and empathize with our target users.

Insights

High Costs 💸: Professional development and certification in tech fields are costly, making it challenging for users to remain competitive.
Interview Challenges 🤔: Translating theoretical knowledge into practical, interview-ready skills is difficult, creating anxiety around technical interviews.
Job Description Confusion 📄: Users find it hard to decipher job descriptions, leading to uncertainty about roles that match their skills and goals.
Preparation Gaps 📝: The platform may lack targeted resources like mock interviews and personalized feedback, hindering comprehensive interview preparation.

Synthesis

Persona

We than created persona based on the insights gathered from these interviews.

What are the job market expectations?

DataLynn's team engaged in discussions with over 20 Hiring Managers, Tech Founders, and Tech Leads at major tech companies, uncovering significant gaps between new graduates and the demands of the job market.

Hands-On Experience
Employers want practical skills, but grads often have only theory.

Soft Skills
Limited experience with teamwork, conflict resolution, and leadership, which are key in interviews.

Applying Knowledge
Grads struggle to use theory in real scenarios during technical interviews.

Key challenges

Interview Challenges
Difficulty translating theoretical knowledge into practical skills for technical interviews.

Insufficient Preparation Tools
The platform may lack focused resources such as career advice and interview preparation tips.

Job Description Confusion
Users find it challenging to interpret job descriptions and match them to their skills.

Key wants

Affordable Learning Paths
Clear pricing and Cost-effective options for ongoing education and certifications.

Effective Interview Prep
Practical tools to bridge theory and practice for technical interviews.

Clear Job Matching
Features that simplify understanding job descriptions and align with users' skills and goals.

Comprehensive Prep Resources:
Tailored preparation options, including interview tips, and guidance

Design approach

I was responsible for optimizing the design of the home page and pricing page, where users first learn about the product. To address the needs identified from previous interviews, I incorporated sections such as user stories, career insights, and interview tips and guidance.
These updates provide valuable resources to help users navigate job roles after reviewing the pricing.

Brainstorming

We started by building wireframes for the mid-fidelity prototype, focusing on key sections like the live copilot, services, pricing, and testimonials. After finalizing the structure, we moved to high-fidelity, improving visuals, adding interactions, and polishing the interface.

For the pricing page of our AI copilot interview product, we explored two design options.

The first option featured a separate pricing comparison table with basic information and detailed product features, complemented by a section below for user stories and FAQs to build credibility and address common questions.

The second option integrated pricing and product features side-by-side for a clearer and more intuitive view. It also included a call-to-action for email subscriptions beneath the pricing chart, aiming to engage users and build an email list. Additionally, this option offered a blog section with career insights and interview tips to provide extra resources and guidance.

We chose Option 2 because it presents pricing and product features in a combined view, which enhances clarity and makes it easier for users to compare all relevant details at once. Additionally, the design includes a call-to-action for email subscriptions below the pricing chart, which engages users and helps build an email list. This approach keeps users informed and connected. The blog section with career insights and interview tips provides valuable resources that support users in their decision-making process.