Prioritize Checkout Metrics Under Time Pressure

Business Context

ShopNow, an e-commerce marketplace, saw same-day revenue fall 9% after a mobile checkout update. The GM needs a recommendation by end of day, but the analytics team can only validate a small number of metrics before the executive review.

Metric Scenario

Yesterday, mobile traffic was stable at 1.2M sessions (+1% vs prior 7-day average), add-to-cart rate was 11.8% vs 12.0% baseline, checkout start rate fell from 68% to 61%, payment success rate fell from 92% to 88%, and completed order conversion dropped from 3.1% to 2.5%. Average order value stayed flat at $64. Customer support tickets tagged "payment" increased 35%, but app crash rate only increased from 0.8% to 1.0%.

Leadership asks: if you can only review a few data points quickly, which metrics would you prioritize, how would you justify that prioritization, and what recommendation would you make today?

Requirements

1. Define the primary KPI you would use to frame the problem and explain why.
2. Identify the 3-5 highest-priority supporting metrics to review first under limited time.
3. Explain how you would distinguish leading indicators from lagging indicators in this case.
4. State what recommendation you would make today based on the available numbers, including confidence level and key caveats.
5. Name the guardrail metrics you would monitor if the team rolls back or patches the checkout update.

Data Available

• session_funnel_daily: sessions, add_to_cart, checkout_start, payment_submit, orders by platform and app version
• payment_attempts: payment_method, processor_response, success_flag, latency_ms
• app_events: crash events, screen load time, error codes, checkout step abandonment
• support_tickets: ticket timestamp, issue_tag, platform, app_version