Mobile Gaming Use Cases/Data ScienceData Scientist

Does the ML-based push suppression model reduce opt-out rates by more than 25% while maintaining open rates within 5% of unsuppressed baseline, achieving an F1 score above 0.75?

Evaluate the performance of an ML model that predicts and suppresses pushes for users showing fatigue signals to prevent opt-outs

Metrics & KPIs

Opt-out reductionopen rate maintenanceF1 scoreprecision/recallsuppression rate

Required Data

Model predictionssuppression eventsopt-out ratesopen ratesmodel performance metrics

Data Sources

CRM PlatformData WarehouseTelemetry

Works with tools like

BrazeCleverTapOneSignalLeanplumAirshipSnowflakeBigQueryRedshiftDatabricksClickHouseMixpanelAmplitudeGameAnalyticsFirebase AnalyticsdeltaDNA

How Bruin answers this

Bruin

Bruin AI Data Analyst

Does the ML-based push suppression model reduce opt-out rates by more than 25% while maintaining open rates within 5% of unsuppressed baseline, achieving an F1 score above 0.75?

Bruin connects to your CRM Platform, Data Warehouse, Telemetry and runs the analysis automatically.

It tracks Opt-out reduction, open rate maintenance, F1 score and delivers the answer in seconds, in Slack, Discord, Teams, Google Chat, WhatsApp, Telegram, email, or your browser.

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