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  • Introduction
  • Basics
    • How ContextDecision Works
    • How ContextPush Works
    • Getting Started
  • Context Decision
    • Logging Conversions
    • Revenue Outcomes
      • Logging Revenue with RevenueCat
    • Adding Entry Points
    • Release Checklist
    • Advanced
      • Custom Signals
      • Alternative Outcomes
      • Custom Outcome Metadata
      • Listening for Good Moments
      • Model Distribution Methods
      • Custom A/B Test Segmentation
      • Analytics & Reporting
  • Context Push
    • Integrating ContextPush
    • Push Notification Providers
      • OneSignal
      • Customer.io
      • Simple Web Request
    • Release Checklist
    • Analytics & Reporting
  • Discover By Use Cases
    • Multivariate Monetization
    • Inline Banners
  • Other Information
    • Glossary
    • Updating Your SDK
    • Minimum SDK Requirements
    • FAQ
    • Get Help
    • Changelog
  • Advanced
    • Custom Configuration
    • Capturing Context In Key Moments
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  • Overview
  • How It Works
  • Integration Overview
  • Privacy Considerations

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  1. Basics

How ContextDecision Works

Optimize in-app offer timing to maximize conversions.

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Last updated 5 days ago

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Overview

ContextDecision helps you increase your app's revenue by showing the right prompts and messages at the right time. By analyzing on-device signals through Edge AI, it identifies user contexts that are best for engagement, increasing revenue and user satisfaction.

How It Works

  • ContextDecision determines the best moments to present in-app offers using real-time, on-device machine learning.

  • Your app collects device signals before showing an offer and logs whether the user converts or dismisses it.

  • Our team trains a machine learning model tailored to your app, using the data we collected from it. This ensures that the model performs the best for your app and your user base.

  • The model suppresses offers when conversion probability is low and surfaces them at optimal moments, increasing the conversion rate.

Integration Overview

  1. with minimal code additions — no new app permissions required.

  2. (successful conversions and dismissals).

  3. Identify new entry points to balance the number of offers shown. To learn more, see Adding Entry Points.

  4. Allow time for the (approximately 1,000 positive interactions collected).

  5. After calibration, a custom model is trained and deployed automatically, optimizing offer timing in real-time.

Privacy Considerations

ContextDecision prioritizes user privacy by processing data on-device, ensuring that no personally identifiable information (PII) is collected or stored. This approach maintains compliance with privacy regulations and fosters user trust.

By leveraging ContextDecision, your application can deliver in-app offers and messages at moments that align with user readiness, thereby enhancing engagement and driving revenue growth.

Integrate the SDK
Start logging user interactions
Calibration Phase