Product · Case studies
Case studies
Deeper strategy and teardown work, each framed by the problem, what I did, and what changed.
Payments Ops · Build
PayOps Copilot: payment reconciliation
A reconciliation workspace for payment-ops teams: rule-based settlement numbers, AI limited to investigation drafts, and a full audit trail.
Problem
Payment-ops teams reconcile across three inconsistent sources: internal orders, gateway exports and bank settlement reports. When numbers don't match, it's unclear whether an exception is real or just a schema mismatch, who owns it, and when it's due. The workflow is spreadsheet-based, with no accountability.
Approach
- Ingest and normalize multi-gateway CSVs (Razorpay, Cashfree, PayU, generic) without silently dropping rows.
- Match on order IDs and gateway references, compute net settlement after fees and GST, and flag seven exception types: missing or duplicate captures, missing settlements, amount mismatches, refunds and chargebacks.
- Keep the math rule-based; AI only drafts the investigation notes, and never calculates the settlement numbers or moves money.
- Turn exceptions into org-scoped cases with RBAC, SLA timers and a full audit ledger.
Product Strategy
Airbnb India: Flexi-Booking
A strategy to solve host revenue instability and guest booking inflexibility, built around tiered insurance and a rewards / credit system.
Problem
Hosts faced unstable, unpredictable revenue while guests wanted more flexible cancellation options. That tension eroded trust and hurt conversion on both sides of the marketplace.
Approach
- Designed a tiered insurance layer (AirCover) plus a rewards program to reduce host revenue risk.
- Introduced flexible-cancellation incentives via a credit system to build host–guest trust.
- Prioritized the roadmap with RICE to focus on the biggest opportunities.
Product Teardown · Product Space
Zepto: AOV & Retention Teardown
A teardown analyzing how to lift average order value and retention through better product discovery and engagement.
Problem
Zepto needed to raise order values and improve a ~45% retention rate without compromising its fast-delivery promise.
Approach
- Analyzed purchase behavior to find levers to move AOV from ₹460 toward ₹600.
- Proposed enhanced product-discovery and engagement mechanics to deepen retention.
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