Optimal Send Time

Optimal Send Time is an algorithm that determines the best hour for optimal engagement activity — when each individual member of your audience is most likely to receive and act on your message.

Take the guesswork out of scheduling messages and let Airship's predictive models optimize send times for you.

Send time predictions update weekly and are exposed as tags for audience segmentation, analysis in Performance Analytics, and exposed as events in Real-Time Data Streaming.

 Note

  • Optimal Send Time is an add-on predictive feature. Contact Airship Sales to enable predictive features for your account.

  • Optimal Send Time is available for iOS, Android, and Amazon only.

The Optimal Send Time Model

"Best Time" is determined from recent engagement history. To start, app opens are localized to the user’s time zone and aggregated to the hour over the last 60 days of app activity. Best hour is determined by striking a balance between the user's engagement patterns and a generalized model of engagement patterns across the app audience. The model also outputs a general best hour which is applied to dormant or low-activity users. The general best hour aggregates opens across app users and selects the best hour based on more frequent opening time for each app platform.

After enabling the feature, Airship runs the predictive model for your iOS, Android, and Amazon audience members. Then you can target them using the optimal send time model.

Optimal Send Time Use Cases

Schedule notifications without having to guess the optimal time for user engagement. By delivering a message to your users at the best time for them, you can optimize for a higher open rate.

  • Send an important update to all users at the time they are most likely to read your message.
  • Deliver a coupon to your users at a time when they are most likely to engage.
  • Send a long form story to you readers at the best time for them.
  • Distribute user engagement across the day to meter traffic flow to the app.
  • Compare performance between regular scheduled messages and messages sent using Optimal Send Time.
  • Analyze Optimal Send Time user level distribution across hours of the day.
  • Analyze correlation between churn risk and user’s best send time.

Optimal Send Time Data and Analytics

Performance Analytics' Predictive Send Time Optimization dashboard provides a deeper look into the best time model, including a distribution of best hours across your audience, and the generalized best hour for your audience by platform and day of week.

You can also use Real-Time Data Streaming to observe changes in optimal send time as TAG_CHANGE events for the ua_send_time_prediction tag group.

Use Optimal Send Time

Select Optimize during the Delivery step in the Message composer. If using the API, schedule your message using best_time.