Gamebeast

Game and app studios need to understand player behavior, but traditional analytics stacks require separate tools for events, A/B testing, attribution, and community sentiment, forcing teams to reconcile numbers across dashboards that often disagree. Answering a simple question like which feature is moving retention typically requires SQL knowledge or a data team, creating a backlog for product managers, designers, and marketers who need fast answers. Studios also struggle to measure the true impact of changes on retention and revenue by player segment rather than just top-line averages, and to know which acquisition channels actually bring back high-value players rather than just installs. Community feedback is scattered across channels, making it hard to catch churn-driving issues before they show up in the metrics.

Gamebeast unifies analytics, experiments, LiveOps, deeplink attribution, and community sentiment into one event model so every chart and dashboard reconciles against the same data. Users can slice any metric by native cohorts and segments without pipelines or SQL, or ask the Gamebeast AI agent in plain language to build the query, propose a hypothesis, or draft an experiment. The experiments feature runs A/B tests on remote config values and breaks down lift by cohort rather than just averages, with winners rolled out in seconds. Deeplinks attribute clicks through conversion to lifetime revenue by source, creator, and geography, while Community Pulse clusters player sentiment across channels by topic and lets the agent act on the signal. The platform ships with SDKs for JavaScript, Node.js, Roblox, Unity, Unreal, and Godot, plus an HTTP API and MCP server support for tools like Claude and Cursor.