Spieltests und Telemetrie

Playtest Questions and Gameplay Evidence

Start with a specific design uncertainty and the decision the evidence will inform. Define participant context, build/configuration and an observable scenario before adding metrics.

• Separate observed action, player explanation, designer inference and unknown cause. A completion or abandonment count does not by itself explain motivation.
• Choose a few metrics tied to the hypothesis: time to first meaningful action, failed attempts by cause, resource flow, choice frequency, recovery or encounter outcome. Define denominators and observation windows.
• Keep event semantics and units stable, with build/config version and a bounded session identity where appropriate. Distinguish repeated attempts from distinct participants.
• Use the existing analytics setup and collect only what the task needs. Adding external collection, identifying players or contacting/recruiting participants needs the appropriate explicit scope.
• Treat biased samples, missing events, small cohorts and changed build conditions as limitations. Do not claim causality or broad retention improvement from an uncontrolled comparison.
• Turn findings into a small next experiment with expected observations, preserving useful counterexamples rather than selecting only favorable sessions.

Deliver scenario, observation notes, metric definitions, findings and uncertainty. A scripted agent run can reveal mechanics defects but is not a substitute for human experience evidence.

Reference: the adapted upstream level-design workflow. No external analytics service or playtest outreach is activated by this skill.