Define success metrics for inventory forecasting panel serving agency owners

Problem Statement Description

You are evaluating an inventory forecasting panel used by agency owners who manage inventory planning across multiple clients, stores, suppliers, or sales channels. The panel depends on connecting external systems, ingesting inventory and demand data, and producing forecasts that agency teams can use to guide replenishment, allocation, and client communication.

The primary business goal is integration success: agency owners should be able to connect the panel to their existing tools, maintain reliable data flow, and reach a point where forecasts are usable in their operating workflow. Your task is to define the metrics that would show whether the product is succeeding, where the funnel is breaking, and what decisions the team should make based on the data.

Focus on a metrics framework rather than a product redesign. Be clear about metric definitions, denominators, time windows, instrumentation, cohorts, guardrails, and how each metric helps diagnose adoption, reliability, or business value.

Your metrics framework should consider:

- The primary success metric for integration success, including its numerator, denominator, and measurement window.

- Key funnel stages such as setup started, connector authorized, data mapped, first sync completed, first forecast generated, and ongoing sync maintained.

- Instrumentation for integration attempts, failures, retries, sync freshness, data completeness, forecast availability, and user actions after forecasts are shown.

- Cohorts by agency size, number of managed clients, integration type, inventory category, geography, and new versus existing customers.

- Usage quality after integration, including whether agency owners view, export, share, or act on forecast outputs.

- Guardrail metrics for reliability, latency, data quality, forecast accuracy, support tickets, churn risk, and user trust.

- Decision usefulness, including how the metrics would help distinguish onboarding friction, technical connector issues, poor data quality, or lack of forecast value.

The goal is to demonstrate how you would build a practical measurement system that helps a product team understand whether agency owners are successfully integrating the inventory forecasting panel and deriving enough value to continue using it.