E-commerce

Checkout & Discovery Optimization

Comparative teardown of Amazon, Myntra and Flipkart on product discovery, PDP and checkout. Surfaced one structural finding: Myntra's ad revenue is masking an FY25 net loss.

North Star Metric

Conversion rate from PDP view → completed checkout

Framework

AARRR + ICE

Executive Summary

Across three Indian e-commerce leaders, the biggest unrealized conversion gains live in PDP signal density and address-step latency — not in the cart itself.

Problem Statement

Where in the discovery-to-checkout flow are the highest-leverage UX gaps across Amazon, Myntra and Flipkart?

Business Goal

Recommend prioritized interventions a PM team could ship to lift purchase conversion within one quarter.

User Research

Heuristic walkthroughs of 12 representative purchase journeys, instrumented with manual timing.

Competitor Research

Direct comparison across discovery, PDP, cart, address, payment, order confirmation.

Personas

The Deal Hunter, the Fashion Browser, the Repeat Re-orderer.

User Journey

Home → category → PDP → add to cart → address → payment → confirmation, instrumented per step.

Pain Points

PDPs bury size/return signal below noisy upsells; address step asks for too many fields; payment failures lose state; Myntra's 'try & buy' messaging is inconsistent.

Opportunity Identification

Compress the address step, surface returns/size policy above the fold on PDP, retain cart state across payment retries.

Root Cause Analysis

Each platform optimizes its top-line metric in isolation; cross-team UX debt accumulates at handoffs (cart→address, address→payment).

Success Metrics

Primary: PDP→checkout conversion. Supporting: payment retry success, return-policy click-through, address completion time.

North Star Metric

Conversion rate from PDP view → completed checkout.

Product Strategy

Trim the funnel, not the catalog. Win the handoffs.

Feature Ideas

1-screen address, sticky size+return widget, payment retry state preservation, smart default payment method.

Prioritization

ICE ranks payment retry preservation #1 (high impact, low effort).

Framework Used

AARRR for funnel diagnosis, ICE for ranking, plus a small business-model audit.

Wireframes

Placeholder[Insert Wireframe / User Flow]

Expected Business Impact

Modeled 1.5–3% conversion lift per intervention. Separately: surfaced Myntra structural risk where ad revenue is masking an FY25 net loss.

Risks

Address-step compression may hurt edge cases (multiple landmarks, rural pincodes). Mitigation: progressive disclosure.

Trade-offs

Less upsell real estate on PDP in exchange for clearer trust signals.

Future Scope

Personalized PDP layouts; saved checkout for repeat reorders.

Lessons Learned

A good product teardown should also stress-test the business model behind the UX.