How ContextPush Works
Deliver non-time-sensitive notifications at the best moment to increase open rate and maximize engagement.
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Deliver non-time-sensitive notifications at the best moment to increase open rate and maximize engagement.
Last updated
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ContextPush optimizes the delivery of non-time-sensitive push notifications to maximize engagement. By leveraging machine learning, it determines the best moment within a given time window to deliver notifications when users are most likely to interact.
Your push notification infrastructure sends a request to ContextPush’s servers, which then manage the delivery.
Here the "push notification infrastructure" can be any system you already use today, such as CRM platforms like Braze, Customer.io, OneSignal, Iterable, etc., or your own custom backend.
Background push notifications periodically wake your app for a few seconds to assess the user’s real-world context.
During the calibration phase, notifications are sent at random times within the specified window to gather insights on user engagement patterns.
The duration of the calibration phase depends on the volume of push notifications your app sends. This could be as fast as just 1 day for apps that send a lot of notifications.
Once the custom model is trained, it is deployed to your app, enabling real-time optimization of notification timing.
From that point forward, ContextPush ensures notifications are delivered at the most opportune moment for the highest open rate.
You define the time window in which notifications can be shown (e.g., within a 12-hour period).
Integrating ContextPush requires minimal effort and can be completed in just a few steps:
Provide your push notification certificate
Create a license key for your app and integrate the iOS SDK (less than 10 lines of code)
Deploy your app
Allow time for data collection (roughly one week). During this period, ContextPush collects push tokens as users interact with your app.
Modify your existing push notification logic to send requests to ContextPush’s server instead of delivering push notifications directly. This step varies depending on your current provider but typically requires only a few minutes to configure.
Wait for the Calibration Phase. ContextPush begins analyzing user engagement by delivering notifications at randomized times within your specified window.
Custom Model Deployment: once calibration is complete, your first custom machine learning model is shipped, enabling optimized push notification delivery.
ContextPush is ideal for non-time-sensitive notifications, such as news updates, promotional offers, and general reminders.
Time-sensitive notifications, such as chat messages, transactional notifications, or urgent promotions, should continue to be handled by your existing push notification provider.
Use ContextPush to offload re-engagement campaigns and other notifications that benefit from optimized delivery timing.