Create a metric dashboard for the executive team reviewing Amazon Shopping

Problem Statement Description

Product context: Amazon is a commerce, logistics, media, devices, and cloud company; its products include Marketplace, Prime, Prime Video, Alexa devices, ads, fulfillment, and AWS.

Amazon’s executive team wants a dashboard to review the health and performance of Amazon Shopping across the end-to-end customer journey, from discovery and search through product detail pages, cart, checkout, delivery promise, post-purchase support, and repeat engagement. The dashboard is intended for senior leaders who need a concise but decision-ready view of whether the shopping experience is improving customer trust, convenience, selection, and business performance.

This is a metrics-focused question. You should define what the dashboard should measure, how metrics should be structured, and how executives would use it to diagnose performance, compare cohorts, and make decisions. The scope should reflect Amazon Shopping’s scale, including web and app usage, Prime and non-Prime customers, marketplace sellers, fulfillment dependencies, and operational quality.

You are not being asked to design visual UI details alone. The emphasis is on selecting meaningful metrics, defining them precisely, explaining denominators and instrumentation, identifying leading and lagging indicators, and ensuring the dashboard avoids vanity metrics or misleading rollups.

The experience should consider:

- The executive decision context: what leaders need to know daily, weekly, monthly, or quarterly.

- The customer journey stages that should be represented, including discovery, consideration, purchase, fulfillment, and retention.

- Clear metric definitions, including numerator, denominator, time window, and event source.

- Cohorts and segmentation such as geography, device, Prime status, new versus returning customers, category, seller type, and fulfillment method.

- Guardrail metrics for trust, delivery quality, returns, customer service contacts, defects, latency, fraud, and customer dissatisfaction.

- Instrumentation and data quality risks, including event tracking gaps, delayed logistics data, attribution issues, and bot or abuse filtering.

- How the dashboard should surface anomalies, trends, benchmarks, and drill-down paths without overwhelming executives.

- How the metrics would support trade-off decisions across growth, profitability, customer experience, marketplace health, and operational excellence.

The goal is to create a dashboard framework that helps Amazon’s executive team quickly understand whether Amazon Shopping is delivering value to customers and the business, identify where performance is changing, and decide where deeper investigation or action is needed.