GAME ANALYTICS KNOWLEDGE BASE
Practical, evidence-led guides for event design, Steam demo measurement and production-safe game telemetry.
Every guide starts from a real decision, defines metric denominators, separates fact from inference and includes an implementation path. We update material when the product or measurement contract changes.
A practical framework for game analytics: define decisions first, design trustworthy events, measure funnels and retention, and turn telemetry into better builds.
A measurement plan for Steam demos and Playtests: separate builds and channels, instrument first-run funnels, find exact exits and evaluate changes without misleading lifetime averages.
How to implement reliable Unreal Engine game telemetry with explicit gameplay semantics, asynchronous delivery, bounded offline queues, privacy controls and verifiable event health.
Compare GameAnalytics and G-Less by workflow, event model, engine support and team fit. A neutral guide for studios choosing game analytics software.
A factual comparison of Unity Analytics and G-Less across SDK setup, pricing model, engine strategy, gameplay event design and Steam build analysis.
Compare PlayFab's broad backend and analytics ecosystem with G-Less's focused game telemetry workflow for Steam demos and PC builds.
Evaluate PostHog for game analytics against G-Less across event flexibility, game-native semantics, session replay, feature flags, engine SDKs and Steam build workflows.
A developer-focused event taxonomy for game analytics: lifecycle events, naming rules, shared context, cardinality limits, versioning and a practical review checklist.
Define game retention cohorts correctly: eligibility, day boundaries, exact vs rolling return, build segmentation, small samples and actionable diagnostics.
A practical Unity game analytics tutorial covering consent, application sessions, run lifecycle, progression events, build context, offline delivery and verification.
A production checklist for testing game analytics SDKs: lifecycle, offline queues, retries, duplicates, clock skew, schema rejection, privacy controls and metric reconciliation.
