What metrics would you use to evaluate a new Checkout feature for enterprise merchants

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 is evaluating a new feature within Checkout for enterprise merchants—large businesses with meaningful payment volume, complex integrations, multiple markets, and high expectations around reliability, conversion, compliance, and reporting. These merchants may operate across geographies, payment methods, currencies, business units, and customer segments, so a feature that looks successful in aggregate may still create risk or uneven outcomes for important cohorts.

In this metrics interview, you are being asked to define how Stripe should evaluate whether the new Checkout feature is working. The focus is not on designing the feature itself, but on choosing metrics that would help product, engineering, sales, risk, and merchant success teams understand adoption, merchant value, end-customer outcomes, payment performance, and operational impact.

Your answer should make clear what success means, how metrics would be calculated, what denominators matter, how you would instrument the funnel, and how you would avoid being misled by volume, seasonality, merchant mix, or enterprise-specific implementation differences.

The experience should consider:

- How to define the primary success metric for an enterprise Checkout feature and why it is decision-useful.

- The relevant denominator for each metric, such as eligible merchants, activated merchants, checkout sessions, payment attempts, completed purchases, or processed volume.

- Adoption and activation tracking across enterprise merchant workflows, including configuration, integration, rollout, and usage by business unit or market.

- Checkout funnel instrumentation from session start through payment completion, abandonment, authorization, failure, refund, dispute, or post-payment issue.

- Cohorts and segmentation by merchant size, geography, industry, payment method, device, new versus returning customers, and integration type.

- Guardrail metrics around reliability, latency, payment failures, fraud, chargebacks, compliance issues, support burden, and merchant operational overhead.

- How to distinguish feature impact from external effects such as traffic quality, promotions, seasonality, merchant-side experiments, or payment network changes.

- How metrics would support go/no-go decisions, iteration priorities, and enterprise merchant conversations after launch.

The goal is to propose a clear, practical measurement framework that Stripe could use to determine whether the new Checkout feature improves outcomes for enterprise merchants while preserving trust, reliability, and payment performance at scale.