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O. Pagya

Business Analyst  ·  Product Thinker  ·  AI Enabler

I turn ambiguous business problems into scalable product solutions that drive measurable impact.

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I don't just document requirements.
I shape product direction.

I'm a Business/Product Analyst with 4 years at IDP Education, one of the world's largest international student placement platforms. My work spans the full product lifecycle — from discovery workshops and stakeholder alignment to BRD/FRD documentation, API integration specs, UAT, and post-launch analytics — across multi-country web, mobile, CRM, CMS, and payments platforms.

What sets me apart is the techno-functional bridge I build between business and engineering. I don't just translate requirements — I challenge assumptions with data, identify automation opportunities through As-Is/To-Be analysis, and lead AI-driven initiatives that reduce manual workload and scale operational impact. I've designed and shipped custom LLMs, WhatsApp chatbots, and internal AI portals that changed how teams work.

I measure success by outcomes: a 30% conversion lift, $450K/month in revenue leakage stopped, 40% reduction in manual workload. If the number didn't move, the work isn't done.

4+ Years in BA & Product
$450K Monthly Revenue Protected
40% Manual Workload Reduced
3 AI Solutions Shipped

Numbers that tell the story

📈
+30%

Conversion Rate Improvement

Drove a 30% uplift in conversion across IDP's eCommerce and student service funnels through requirements analysis, A/B testing, UX collaboration, and targeted customer-centric enhancements.

Product Analytics · A/B Testing · UX
🛡️
$450K/mo

Revenue Leakage Mitigated

Performed root-cause analysis on reconciliation gaps, vendor mismatches, and API integration failures. Drove cross-functional corrective measures that stopped ~$450K/month in silent revenue loss.

Root Cause Analysis · API · Finance Ops
🤖
-40%

Manual Workload via AI

Designed and launched 3 AI-powered solutions — a custom LLM, WhatsApp chatbot, and internal AI portal — that cut manual workload by 40% and significantly improved operational turnaround time.

LLM · Chatbot · AI Automation
+25% / +18%

Journey Completion & CSAT

Increased journey completion by 25% and boosted customer satisfaction scores by 18% through user research, journey mapping, and cross-functional UX alignment across global platforms.

User Research · Journey Mapping · CSAT

How I solve hard problems

Three real engagements. Full decision-making transparency.

01 Revenue Operations

Stopping $450K/Month in Revenue Leakage

How I identified silent reconciliation failures across IDP's payment ecosystem and led the cross-functional fix that closed the gap.

Problem Statement

Finance flagged a growing discrepancy between invoiced amounts and actual payments received across IDP's multi-country platform. The gap had reached ~$450K/month but was being dismissed as "system noise." No one had traced it to a root cause.

Context

IDP's payments infrastructure spans multiple countries, currencies, and third-party payment providers. Reconciliation between the CRM, payment gateway, and finance systems was partially manual — creating blind spots whenever vendor data or API responses were inconsistent.

My Role

Lead Business/Product Analyst. I owned the investigation end-to-end — from data analysis and root-cause workshops to requirements definition, cross-functional alignment, and UAT sign-off.

Approach

  1. Data investigation: Used SQL and BI dashboards to cross-reference payment gateway responses against CRM records. Identified 3 recurring failure patterns: reconciliation gaps, vendor data mismatches, and silent API integration errors.
  2. Root cause workshop: Facilitated a cross-functional session with Finance, Engineering, and Payments vendors to map the full transaction flow and pinpoint where data was being lost or misrouted.
  3. Stakeholder alignment: Quantified the impact and presented findings to senior leadership. Secured prioritisation on the next sprint cycle.
  4. Requirements definition: Wrote BRDs and user stories covering automated reconciliation logic, vendor mismatch alerting, and API error handling with retry mechanisms.
  5. UAT & compliance: Designed test scenarios for all failure modes. Validated GDPR alignment for cross-border payment data handling before go-live.

Solution

Automated reconciliation logic with real-time discrepancy alerting, vendor mismatch detection, and corrective API retry flows. Paired with a BI dashboard giving Finance full visibility into payment status across all markets.

Impact

~$450K/moRevenue leakage mitigated
-50%Manual reporting effort
GDPRCompliant across all markets

Learnings

Revenue leakage at this scale is almost always a data visibility problem before it's a technical one. SQL fluency and BI ownership gave me the evidence to move stakeholders fast. I've since made reconciliation analysis a standard part of any payments-adjacent discovery.

02 AI & Automation

Building AI-Powered Solutions That Cut Manual Work by 40%

How I led the design and launch of a custom LLM, WhatsApp chatbot, and internal AI portal to transform how IDP's teams operate.

Problem Statement

IDP's operations teams were spending significant time on repetitive, document-heavy workflows — student query handling, internal knowledge retrieval, and manual data processing. The volume was growing faster than headcount could scale.

Context

IDP serves students across multiple countries with complex, document-intensive processes. The business needed intelligent automation that could handle high-volume queries, surface institutional knowledge, and reduce turnaround time — without compromising accuracy or compliance.

My Role

Lead BA and product owner for all three AI initiatives. I defined the problem space, wrote requirements, coordinated with Engineering and UX, managed stakeholder expectations, and tracked post-launch impact metrics.

Approach

  1. As-Is process mapping: Documented current workflows for student query handling and internal knowledge retrieval. Identified the highest-volume, highest-friction tasks as automation candidates.
  2. Solution scoping: Defined 3 distinct AI use cases — a custom LLM for internal knowledge, a WhatsApp chatbot for student-facing queries, and an AI portal for operational teams. Wrote FRDs for each.
  3. Cross-functional build: Collaborated with Engineering on LLM fine-tuning requirements, UX on conversation design, and Compliance on data handling and GDPR alignment.
  4. Phased rollout: Launched the WhatsApp chatbot first (highest volume impact), followed by the internal AI portal, then the custom LLM. Monitored deflection rates and turnaround time after each release.
  5. Iteration: Used Heap and Hotjar analytics alongside user feedback to identify gaps in chatbot coverage and refine LLM response quality.

Solution

Three production AI solutions: a WhatsApp chatbot handling student queries at scale, a custom LLM surfacing institutional knowledge for internal teams, and an AI portal consolidating operational workflows — all GDPR-compliant and integrated into existing systems.

Impact

-40%Manual workload reduced
3AI solutions shipped
FasterOperational turnaround time

Learnings

AI initiatives fail when BAs treat them as tech projects. The real work is process mapping — understanding exactly which human decisions can be automated and which can't. I now start every AI engagement with a workflow audit before touching a single requirement.

03 Conversion Optimisation

30% Conversion Lift on IDP's Student Journey

How user research, funnel analysis, and cross-functional UX alignment turned a stagnant funnel into a measurable growth driver.

Problem Statement

IDP's student service funnel was underperforming. Users were dropping off before completing key actions — application submissions, counsellor bookings, and payment flows. Previous UI changes had moved nothing.

Context

IDP's website and eCommerce platform serves students across multiple countries navigating complex decisions about studying abroad. The funnel spanned web and mobile, with significant drop-off at multiple stages. The product team needed a data-backed diagnosis, not more design opinions.

My Role

Lead BA embedded in the product squad. I owned discovery, requirements, A/B test design, and cross-functional coordination across UX, Engineering, and Data teams.

Approach

  1. Funnel analysis: Used Google Analytics, Heap, and Hotjar heatmaps to build a step-by-step drop-off map. Identified the exact screens and interactions where users were abandoning.
  2. User research: Conducted user research and journey mapping sessions to understand the "why" behind the data. Uncovered friction points around information clarity, trust signals, and mobile UX gaps.
  3. Prioritisation: Ran a MoSCoW workshop with stakeholders to rank findings by impact and effort. Focused the first release on the highest-leverage fixes.
  4. A/B testing: Designed and ran A/B tests on key funnel steps. Used results to validate hypotheses before committing to full implementation.
  5. Iterative delivery: Shipped improvements across multiple sprints, tracking conversion metrics after each release to confirm impact before proceeding.

Solution

A series of targeted, data-validated enhancements across the student journey — improved information architecture, stronger trust signals, mobile UX fixes, and streamlined payment flows — all grounded in user research and A/B test evidence.

Impact

+30%Conversion rate
+25%Journey completion
+18%Customer satisfaction

Learnings

The previous team was optimising the wrong things. Heatmaps and session data told a completely different story than stakeholder assumptions. I now treat analytics tools as the first input to any discovery — not a post-launch afterthought.

What I bring to the table

🔍

Business Analysis

Requirements Elicitation BRD / FRD / User Stories Use Cases & Acceptance Criteria Stakeholder Management As-Is / To-Be Modelling Gap & Market Analysis Process Optimisation UAT Planning & Execution Change Management Workshop Facilitation
💡

Product Thinking

User Journey Mapping Agile / Scrum GTM Strategy Roadmap Planning A/B Testing Funnel & Path Analysis MoSCoW Prioritisation API & System Integrations CRM / CMS Implementation Microservices Analysis GDPR & Compliance UI/UX Collaboration
🛠️

Tools & Platforms

Jira Confluence SQL Power BI Tableau Google Analytics Heap Hotjar Figma Miro SAP CRM Contentful HubSpot Workato Azure Genesys

Career progression

Business / Product Analyst

IDP Education Pvt. Ltd.  ·  Chennai  ·  EdTech / B2B & B2C

Mar 2022 – Present

Embedded across IDP's core product squads, owning requirements end-to-end for multi-country platforms spanning Student Services, CRM, CMS, Payments, and Partner Integrations. Act as the techno-functional bridge between business stakeholders and engineering teams globally.

  • Improved conversion rates by 30% through A/B testing, UX collaboration, and customer-centric enhancements
  • Mitigated ~$450K/month in revenue leakage via root-cause analysis on reconciliation gaps and API failures
  • Designed and launched 3 AI solutions (custom LLM, WhatsApp chatbot, AI portal) — reduced manual workload by 40%
  • Increased journey completion by 25% and customer satisfaction by 18% through user research and journey mapping
  • Built BI dashboards (MRR, funnel, path analysis) cutting manual reporting by 50% and saving 10+ hours/week
  • Delivered GDPR-compliant API integrations with financial and healthcare providers across global markets
  • Improved delivery timelines by 20% through structured stakeholder workshops (SWOT, MoSCoW, story mapping)

How I think

The mental models and frameworks I apply to every engagement.

01

Problem Structuring

Before writing a single requirement, I decompose the problem space.

What's the symptom?
What stakeholders are reporting
🔎
What's the actual problem?
Data-backed root cause
🎯
What does success look like?
Measurable outcome definition
📋
What's the solution space?
Options, constraints, trade-offs
02

Root Cause Analysis

I use a layered "5 Whys + Data" approach to avoid solving symptoms.

Surface What stakeholders report
Process Where the workflow breaks
System Technical or data root cause
Root Incentive or structural cause

Most teams stop at layer 2. I go to layer 4.

03

Decision Framework

When facing competing priorities or trade-offs, I use a structured decision matrix.

High Impact Low Impact
Low Effort Do Now Fill-in
High Effort Plan Deprioritize

I add a third axis: strategic alignment. Impact alone isn't enough.

04

Stakeholder Alignment Model

I map stakeholders on two axes before any major decision or presentation.

Manage Closely
High power, high interest
Keep Satisfied
High power, low interest
Keep Informed
Low power, high interest
Monitor
Low power, low interest
← Power → Interest ↕

What colleagues say

Pagya has a rare ability to walk into a room full of conflicting opinions and walk out with a clear, agreed-upon direction. The revenue leakage work alone saved us more than we'd budgeted for the entire quarter — and it started with her asking the right questions in a data review.
PM

Product Manager

IDP Education — Student Services Platform

Working with Pagya changed how our engineering team thinks about requirements. We used to get vague specs and figure it out ourselves. Now we get clear, testable user stories with edge cases already mapped — especially on API integrations. It's a completely different experience.
EL

Engineering Lead

IDP Education — Payments & Integrations

Pagya doesn't just document what stakeholders ask for — she challenges assumptions and pushes back when something doesn't make sense. The AI portal initiative is a great example: she reframed the entire problem before we wrote a single requirement, and the outcome was far better for it.
PO

Product Owner

IDP Education — Digital Transformation

Let's work together

I'm open to Business Analyst, Product Analyst, and product consulting roles — particularly in EdTech, FinTech, or digital transformation. If you're building something complex and need someone who can own the problem space end-to-end, let's talk.