Conversion in Issuing fell after a redesign. How would you investigate

Problem Statement Description

Product context: Stripe is financial infrastructure for internet businesses; its products include payments, Checkout, Billing, Connect, Radar, Issuing, Terminal, and tax tools.

Stripe Issuing lets businesses create and manage physical or virtual cards through APIs and dashboard workflows. After a recent redesign of the Issuing experience, the team observes a meaningful drop in conversion. In this context, “conversion” may refer to developers or business users moving from initial interest into account setup, compliance steps, card program creation, API integration, test mode usage, or live card issuance.

You are asked to investigate the drop as a product manager at Stripe. The focus is not to jump to a redesign recommendation, but to structure a root-cause analysis that separates measurement issues from real user behavior changes, identifies where the funnel degraded, and determines whether the issue affects all users or specific segments.

The investigation should account for Stripe’s environment: developer-first workflows, regulated financial products, onboarding and compliance requirements, API documentation, dashboard UX, and the reliability expectations of businesses evaluating financial infrastructure.

The experience should consider:

- How to define the affected conversion metric, including numerator, denominator, time window, and baseline period before the redesign.

- Which funnel steps to inspect across discovery, signup, eligibility, compliance/KYC, dashboard setup, API key usage, cardholder creation, card issuance, and first successful transaction.

- How to segment the decline by user type, geography, business size, traffic source, device, integration path, new vs. returning users, and test-mode vs. live-mode usage.

- What instrumentation, tracking, experiment assignment, or data pipeline issues could falsely indicate a conversion drop.

- Which redesign changes could have introduced friction, confusion, latency, missing information, compliance dead ends, or developer workflow interruptions.

- What qualitative and quantitative evidence would help validate hypotheses, such as session replays, support tickets, sales feedback, documentation searches, API error logs, and user interviews.

- How to assess severity, business impact, and urgency while protecting financial reliability, compliance, and user trust.

- What short-term mitigations, monitoring, and longer-term prevention mechanisms should be considered once the cause is understood.

The goal is to demonstrate a structured RCA approach that can isolate the most likely causes of the post-redesign conversion decline, identify the affected user cohorts and funnel stages, and guide Stripe toward evidence-based mitigation without compromising developer experience, compliance, or platform reliability.