/ 1.1  Project Background

Masters' Union is a tech-first business school that scaled rapidly - but its internal operations couldn't keep pace. Before Dinero, two disconnected systems managed the entire admissions and fee cycle:

Neither system talked to the other. Every handoff was manual. Every status update was a spreadsheet entry. Students clicking a payment link in an email - for a Rs.3,50,000+ transaction - were landing on an unbranded external page they had never seen before.

/ 1.2 Research Goals

/ 1.3  Research Questions

/ 1.4  KPIs & Success Metrics

/ 1.5  Methodology

/ 1.6  Participants

/ 1.7  Usability Test Script

/ 1.8  Study Schedule

/ 2.1  Stakeholder Interviews

Before talking to any end users, we ran alignment sessions with the Product Manager and two Admin Leads. The goal was not to gather requirements - it was to understand the business context, the constraints and how each stakeholder defined success.

/ 2.2  Competitive Analysis

We mapped the tools the team was actually using - NPF for admissions tracking and Pinelab (alongside Flywire and Blackbaud as market alternatives) for payments - against what the team actually needed. The gap became the design brief.

Unique Value Proposition

What makes this company unique?

Company Advantages

What are the things that provide a leg up?

Company Disadvantages

Where might drawbacks exist?

1. A lead tracking platform that helps institutions manage student applications and financial processes.
2. Primarily a lead management system, helping institutions handle student inquiries, applications and enrolment.
3. Focuses on CRM-style automation for student recruitment and communication.

1. Handles lead tracking and applicant approvals.
2. May include basic financial tracking for student payments.
3. Automates admissions and lead funnel management with CRM-style tracking.
4. Provides real-time applicant status updates for universities.
5. Integrates AI-driven analytics for student recruitment trends.
6. Reduces manual follow-ups by automating communication workflows.

1. Limited admin-side financial tracking (refunds, reports and approvals).
2. Lacks post-admission features, making it only useful for lead management.
3. No fee tracking, refund approvals, or payment integration.
4. Requires third-party integrations for financial & engagement tools.

1. A secure global tuition payment platform that simplifies university transactions, loan processing and refunds.
2. A global education payment solution, allowing universities to accept international and domestic tuition payments securely.
3. Focuses on fraud prevention and currency conversion for global students.

1. Provides secure fee payments & refunds.
2. Supports loan approvals and payment verification.
3. Supports multi-currency transactions with localized payment methods.
4. Offers secure, institution-approved fee collection with built-in fraud detection.
5. Provides detailed financial reporting dashboards for universities.
6. Ensures compliance with financial regulations in different regions.

1. No lead tracking or interview process.
2. No student engagement features (meetings, clubs, help desk, etc.).
3. Not an internal tool-relies on external payment providers.
4. Lacks post-admission features, making it only useful for lead management.
5. No fee tracking, refund approvals, or payment integration.
6. Requires third-party integrations for financial & engagement tools.

/ 2.3  Card Sorting

Information Architecture Discovery

Before sketching a single screen, we ran open card sorting with all 11 participants to let users define the information architecture. We weren’t going to impose a structure - we were going to discover the one that already existed in users’ minds.

/ 2.5  User Personas - 3 Research-Backed Roles

These personas were built directly from interview data - not from assumptions. Every goal, pain point and JTBD below was mentioned by at least 2 of the participants in that role group.

Aditya Verma

MBA Student - Age: 22  |  Location: Pune, India

Aditya is a driven MBA student focused on securing a great job post-graduation, but he finds the admission and financial process confusing. He struggles to track interview progress, fee payments and counselor feedback - often missing important updates. He prefers digital solutions but gets frustrated when he has to check multiple platforms. He wants one place where everything just works.

Goals

→

Track interview progress and feedback in real time - no more waiting for email updates

→

Pay fees quickly without worrying about third-party links or whether payment went through

→

Access counselor reports and meeting history in one place

→

Join clubs and events without long approval processes or scattered notifications

Pain Points

×

Confusing interview process - unclear next steps, no visibility into stage

×

Third-party payment issues - external link felt untrustworthy, no receipt

×

Scattered feedback from counselors - difficult to access reports from previous sessions

HEARS

→

You need to pay your fees via this third-party link.

→

Your interview status will be updated soon.

→

You missed the deadline for your counselor feedback session.

SEES

Multiple emails from admissions with unclear instructions. Screenshots and spreadsheets to track interview progress. Other students discussing the process in WhatsApp groups.

SAYS & DOES

→

Where do I check my interview status?

→

Did my payment go through? How do I get a receipt?

→

Asks peers for updates. Logs into multiple platforms.

THINKS & FEELS

→

I wish there was one place to track everything.

→

Why do I need to use third-party payment links?

→

Am I missing important deadlines?

Priya Sharma

Admissions & Finance Administrator - Age: 42  |  Location: New Delhi, India

Priya is responsible for managing student admissions, financial records and interview tracking. She works with multiple tools daily to approve applications, verify transactions and track refund requests. The lack of a centralized system makes her job exhausting - she handles 2-4 data discrepancy errors daily across NPF, Pinelab, Excel and email.

Goals

→

Streamline the admission approval process to reduce manual work

→

Get real-time insights into student finances, transactions and interview status

→

Automate fee processing and refunds to avoid delays and student complaints

→

Ensure data accuracy in reports without switching between multiple platforms

Pain Points

×

Too many manual approvals - time-consuming and error-prone

×

Scattered data across NPF, Pinelab, Excel and email - hard to get a complete student picture

×

Delayed fee verification and refund processing - leading to daily student complaints

×

No single dashboard for managing student interactions across all touchpoints

HEARS

→

We need to approve 50+ applications today

→

How many students have completed fee payments?

→

Students are complaining about missing payment confirmations

SEES

Multiple spreadsheets tracking student fee payments. Unorganized email requests for refund approvals. Confusion about fee statuses across different platforms.

SAYS & DOES

→

I need to check multiple systems to track student applications

→

Tracks counselor interactions separately from financial records. Compiles manual reports each morning.

THINKS & FEELS

→

There must be a better way to manage all of this.

→

 I spend 4 hours a day just reconciling data.

→

 Why can't I see a student's full journey in one place?

Dr. Rajeev Menon

Faculty & Student Counselor- Age: 40  |  Location: Bangalore, India

Dr. Rajeev Menon has been mentoring students for over a decade, helping them navigate academic and career paths. Without a structured system, his feedback gets lost in emails. He struggles to track student engagement across counseling sessions and has no way to flag at-risk students early.

Goals

→

Provide timely and structured feedback to students after interviews and sessions

→

Have a centralized system to track student history, progress and counselor interactions

→

Improve student engagement in career mentorship and academic guidance

→

Reduce the need for manual note-keeping and fragmented communication

Pain Points

×

No centralized student tracking system - feedback often gets lost in email drafts

×

Manual documentation is inefficient and takes too much time between sessions

×

Hard to ensure students are following up on counseling sessions and interview feedback

HEARS

→

Can you check in on this student? I think they're struggling

→

Your session notes weren't attached to the student record

→

A student from last month missed their follow-up.

SEES

No structured view of students he has counseled. Emails as the only record system. Students re-explaining context he should already know.

SAYS & DOES

→

My session notes live in my professional email drafts.

→

I have to reconstruct context from memory each time

→

Manually tracks follow-ups in a personal notebook.

THINKS & FEELS

→

I'm losing context between sessions - I can't be an effective mentor this way.

→

I want to flag at-risk students but there's no channel

→

This should all be in one place.

/ 2.6  Experience & Journey Mapping

We mapped the emotional arc of the full 8-step journey for each role - not just the tasks, but how users felt at each stage. This is where the design priorities became undeniable.

/ 2.7  Wireframing - Lo-Fi

With card sorting results defining the IA and research findings defining the priorities, we moved into solution space. The rule: generate first, judge later.

/ 2.8  Usability Testing - Two Rounds

Two rounds of moderated usability testing - Round 1 on mid-fidelity prototype before any iteration, Round 2 on hi-fidelity after design changes. Testing early meant failing cheaply. Testing again proved the iteration worked.

Task Difficulty Scores

Task

Round 1 Difficulty

Round 2 Difficulty

Key Change Made

Student: Pay semester fee

4.2 / 5 (hard)

1.9 / 5 (easy)

Pinelab embedded inside Dinero + itemised fee breakdown + trust signals

Admin: Update student status

2.4 / 5

1.6 / 5

Simplified dropdown + inline confirmation modal

Faculty: Log session note

4.1 / 5 (hard)

2.1 / 5

Dedicated Log Session CTA + autosave + follow-up reminder inline

Report export (added R2)

N/A

1.8 / 5 (easy)

One-click export with 3 pre-built templates

/ 2.9  User Interviews - Laddering Technique

11 semi-structured interviews across 3 user roles. Sessions were 45–60 minutes each. We used laddering: start with behaviour, move to consequence, then feeling, then the underlying need. This is where the real insight lives.

Laddering Example - How One Question Unlocked the Payment Trust Insight

Student Interview Areas

Admin Interview Areas

Faculty / Counselor Interview Areas

/ 2.10  Data Collected

/ 3.1  Identify Patterns

Synthesis is where raw data becomes design direction. With 200+ observations, 11 interviews, 2 observation sessions and card sorting results, the risk was finding patterns that weren't really there - or missing the ones that were. This is how we separated signal from noise.

Step 3 - Triangulation Gate

Before a pattern became a design decision, it had to pass through a triangulation gate: corroboration by at least 2 independent methods. This prevented a single vivid interview quote from driving a design decision.

Visibility Anxiety

User interviews

(41 notes)

Journey mapping

(peak frustration at Stage 1)

Card sorting

(students separated Journey from Money)

Payment Trust Deficit

User interviews (phishing 3/5 unprompted)

Laddering (L4: want official portal, not external link)

Usability test R1

(Task 1 hardest: 4.2/5 difficulty)

Admin Fragmentation

User interviews

(1-2 hrs self-reported)

Contextual observation (real: 3-5 hrs)

Usability test R1 (admin status update: 2.4/5 difficulty)

Counselor Invisibility

User interviews

(32 notes, all 3 faculty)

Usability test R1 (session log: 4.1/5 hardest task)

Card sorting (faculty grouped by student, not by task)

/ 3.2  Key Findings

5 Findings, Severity-Rated

Findings rated by severity. Critical and High findings drove v1.0 priorities. Medium findings shipped in v1.5.

/ 4.1  Sprint planning

v1.0 → v1.5 → v2.0 · Research Drove Every Release

/ 4.1  UI Screen

• 30 components Atomic Design: atoms -> molecules -> organisms
• Token-based: colour, spacing, typography fully tokenized for consistency across 3 dashboards
• Figma Dev Mode handoff to 8 frontend engineers zero post-handoff design questions
• Component library: buttons, inputs, cards, pipeline chips, status badges, modals, tables, toast notifications

Admin Login Role-based entry point. Admin authenticates with institutional email.

Finance Dashboard Aggregate financial view. Three primary metric cards: Total Applications | Fee Collected | Offers Pending. Replaces the daily manual Pinelab export + Excel reconciliation. Previously 45 minutes - now visible on login. (Note: Values shown are representative. Actual cohort data not shared due to institutional confidentiality.)

Student Detail: Status Timeline Individual student view. All 8 stages with timestamps as a persistent header - visible on every tab. Shows admin what happened and when without reconstructing from email threads. In-app + email notification fires automatically on stage change - replaces manual admin emails.

Finance Overview: Revenue Tracking Total revenue, collected, pending, refunds and adjustments in one screen. Auto-synced from Pinelab - no manual calculation. Replaced the 30-minute morning Excel compilation.

(Note: Values shown are representative. Actual financial data not shared due to institutional confidentiality.)

Student List: Full Payment Table Full-cohort view with payment amounts, dates and status per student. Sortable, filterable, one-click exportable. The table that replaced the NPF + Pinelab manual reconciliation entirely - report that took 30–45 minutes now takes 10 seconds.

/ 4.3  Results & Impact

/ 4.4 HEART Framework - UX Quality Post-Launch

5 Dimensions · All Targets Achieved

/ 4.4 Core Learnings

After organising data by role, cross-role synthesis revealed 5 patterns that cut across all three user groups. Each appeared in at least 2 of 3 roles.

/ 4.4 Core Learnings

After organising data by role, cross-role synthesis revealed 5 patterns that cut across all three user groups. Each appeared in at least 2 of 3 roles.