Terminal engagement dropped 20% in two weeks among enterprise merchants. Diagnose the issue

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 Terminal is used by enterprise merchants to accept in-person payments through Stripe-integrated readers, point-of-sale systems, and backend payment infrastructure. A 20% drop in Terminal engagement has been observed over the last two weeks specifically among enterprise merchants, raising concern about payment reliability, merchant operations, and potential revenue impact.

Your task is to diagnose the issue as a product manager leading an RCA. You should frame what “engagement” could mean in this context, validate whether the drop is real, identify where in the merchant or payment workflow the decline is occurring, and build a structured set of hypotheses across product, technical, merchant, market, and operational causes.

The investigation should consider:

- How to define and validate the engagement metric, including denominator, time window, seasonality, and whether the 20% drop reflects merchants, devices, locations, transactions, or active sessions.

- Segmentation by enterprise merchant type, geography, integration method, reader model, app/POS version, payment method, location count, and account tenure.

- Instrumentation checks to rule out logging delays, event schema changes, dashboard bugs, data pipeline issues, or changes in metric definitions.

- Merchant workflow points where engagement could drop, such as reader pairing, checkout initiation, payment authorization, failed transactions, device connectivity, reconciliation, or staff usage.

- Product and technical hypotheses, including firmware releases, API changes, SDK regressions, reader availability, latency, error rates, compliance changes, or outage patterns.

- External and business factors such as merchant seasonality, store closures, competitor migration, pricing changes, support issues, or enterprise contract changes.

- Evidence needed to prioritize hypotheses, including quantitative cuts, merchant support tickets, incident logs, release timelines, cohort analysis, and merchant interviews.

- Mitigation and prevention planning, including immediate containment, merchant communication, monitoring improvements, and long-term safeguards.

The goal is to demonstrate a clear RCA approach: confirm the anomaly, localize the impact, generate and test plausible hypotheses, identify the most likely root cause, and outline how Stripe should mitigate merchant impact while preventing recurrence.