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Metric

As explained in Automating API Delivery

A business metric is a quantitative measure of an organization's commercial performance, customer outcomes, quality, or cost.

A metric is a quantitative measure used to judge whether an API product is meeting a goal. A business might target a 10% increase in active subscribers. Its API team then tracks product metrics that could contribute to that outcome, rather than treating API traffic alone as proof of success. The proposed cause-and-effect relationship is a hypothesis to test over successive Plan–Do–Study–Act (PDSA) cycles. section 11.1.1

Choose and use metrics in this order:

  • Select a high-level focus, or north-star, metric that provides value to customers and the business. Identify lower-level measures that might improve it or show whether the product remains healthy. section 11.1.1
  • Map the developer journey from discovery and evaluation through build, production usage, and scaling. Identify touchpoints where the developer’s experience can be measured. section 11.1.2
  • Track relevant API product measures across discovery, engagement, acquisition, activation, retention, and experience. Capture and share the results with product managers and the API team, then use them to decide what to improve next. section 11.1.3 section 11.4

Discovery versus product adoption

Unique visitors to developer landing pages and referrals by traffic source help show how prospects find an API. New user sign-ups, daily active users, retention, and conversion rate provide other views of product performance. For these measures, developers are the primary users: calls made through an application’s API key are attributed to its developer, even when many end users use the application. section 11.1.3 section 11.4

Keep product outcomes distinct from technical health. Infrastructure measures include CPU, memory, and network use; service-level measures include latency, error rate, throughput, and uptime. Dashboards and alerts help teams detect and diagnose operational problems, while product analytics helps them judge the API experience and improvement goals. The RED method narrows technical monitoring to request rate, error rate, and duration. section 11.2 section 11.4

How Automating API Delivery covers it

How deep it goes
Explains metric selection through PDSA, developer-journey touchpoints, and product categories; treats lower-level measures as hypothesized leading indicators.
Examples
Uses active-subscriber goals, landing-page visitors, referrals, sign-ups, daily active users, retention, and conversion rate.
What it assumes
Assumes familiarity with PDSA while explaining developer-journey stages and touchpoints.
What you can do after
Apply it via developer journey mapping and product analytics to choose, capture, share, and review API improvement measures.
How it connects
Connects metrics to PDSA, developer journey mapping, product analytics, API monitoring, and the RED method.

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