UX RESEARCH • BRANDING • AI • PRODUCT DESIGN • TESTING
Margg App - A Roadmap Based Learning App
The objective was to create a learning platform where learning doesn’t feel broken but flows seamlessly. Rather than letting the learner wonder what's next, why is learning this important? We aim to provide them with a whole roadmap to their future self.
Time
6 months
Role
Product Designer
Collaborations
Tech team, product designers, tech lead
Context
There's a huge gap between earning a bachelor's degree and getting employment in IT. This gap is generally filled by acquiring certificates from different platforms, but no one is very clear on what is necessary and what is not. We aim to close this gap by teaching what's necessary to land a job and how their learning is applied to real-life problems.
Vision
We wanted to build a comprehensive career-steering platform to help students identify their professional callings and equip them with the tools required to get there. We wanted to stand out in the market, and we knew what to offer users-
• Roadmap to a successful career
• All-time accessible learning material
• Career mentorship
• Interview Preparatory material.
A whole guide to help them through their learning journey to landing a job.
User Research
The first step was to make sure the market needs this product. The team performed a user survey in multiple universities to understand how clear students are about what they want to become. I analyzed quantitative data from an extensive user survey. The goal was to uncover critical friction points in how modern learners discover content, track their progress, and prepare for high-stakes interviews.
Our team approached students for in-person interviews (for qualitative analysis) and a form-based survey (for quantitative analysis).
This helped us in understanding whether the features we have in mind are required for the user. And what are the essential features for our MVP?
Key Insights
The Discovery Driver: 81.2% of users enroll in online courses with a highly specific skill goal in mind. They seek targeted relevance rather than open-ended exploration.
The Structured Expectation: A massive 77.5% of students strictly prefer a sequential learning path, and 75.4% express a strong interest in a module-based learning model. Moving out of sequence only occurs if the concepts feel redundant or irrelevant.
The Progression & Doubt Chasm: Tracking progress and resolving doubts are major structural failures in existing tools. 93% of users are unable to clear their doubts, while a vast majority struggle with tracking their advancement.
The Interview Preparation Playbook: 85% of users prioritize mock interviews and analyzing company-specific interview patterns above all else. When reviewing their performance, 81.2% rely heavily on comparing their solutions with sample answers or seeking external mentorship.
The Content Medium Preference: The most impactful formats for technical preparation are interactive exercises, video tutorials, and live workshops. Static textual guides are the least effective.
Market Validation
The survey provided overwhelming quantitative proof of a market gap, validating our hypothesis that students face an urgent need for an all-in-one ecosystem that bridges static learning with targeted career execution.
The Unified Ecosystem Demand: 85.5% of respondents state that it is extremely important to have a platform that seamlessly integrates course curriculum with technical interview preparation resources.
High Adoption Intent: Over 80% of surveyed users expressed immediate interest in a platform that addresses both skill development and career roadmap milestones simultaneously.
Design
Data is only useful if you can execute it quickly. With our user insights locked in, we designed the platform with a disciplined mobile-first mindset.
To supercharge our timeline, I integrated AI directly into my design workflow. I used it to rapidly brainstorm feature permutations, draft initial sitemaps, and identify hidden friction points in our user journeys. By offloading the initial structural heavy-lifting to AI, I freed up my time to focus on what matters most: running deep visual explorations and polishing high-fidelity micro-interactions that make the platform feel alive and intuitive.
Intent-based Onboarding
A personalized, intent-based onboarding flow where users select their precise target role or skill gap up front.
Guided Roadmap
A clean, highly visual roadmap interface that chunks dense engineering curriculums into digestible, progressive milestones.
Concept Related Flash Notes
Highlight and save quick notes to go through before exam/interview
Solve Real Problems
With over 100+ real world coding problems and in-built coding environment, test your skills to generate creative solutions.
Open Community
Connect with community of students to share & learn from peers
AI backed courses
Courses that prepares you to utilise AI abilities in your daily tasks
The Outcomes
Increase in Time Spent on Website
84%
Improved Onboarding Process
35%
Increase in User Retention
25%
From behind the scenes
With aggressive launch deadlines on the horizon, velocity was our highest priority. I led a lean, fast-moving team consisting of one other Product Designer and two Design Interns. To deliver a comprehensive, native ecosystem across both web and mobile platforms without breaking our timeline, I established an AI-augmented design workflow.
• Accelerated Mentorship: I used AI to quickly generate structural benchmarks, which allowed me to onboard and guide the interns efficiently, keeping our design standards unified.
• Parallel Tracks (Web + Mobile Native): By leveraging AI for rapid wireframing and initial copy drafting, we bypassed traditional layout bottlenecks. This allowed the senior team members to split and focus concurrently on the complex interactions required for native mobile and responsive web layouts.
• The Result: We moved from raw user survey data to production-ready design assets in record time, turning what should have been a months-long architecture phase into a hyper-efficient, collaborative design sprint.
