Intelligent Delivery

For more on Campaign Delivery, check out our Campaign Set Up course on LAB!

When scheduling a campaign, you have the option of using Braze’s Intelligent Delivery feature, delivers your message to each user at the time which Braze determines that individual is most likely to engage. We calculate the optimal send time based on a statistical analysis of the user’s past interactions with your app.

To use this feature, simply select Intelligent Delivery when scheduling a campaign. The only difference between this option and “Send at a designated time” is that the time of day each user receives your message will be determined by Braze. You can still choose the day(s) on which your message will send and create a recurring campaign.

You also have the option of specifying a certain time range during which your message should send. This is useful if your campaign pertains to a specific event, sale or promotion.

Optimal Send Time

If you’re using Intelligent Delivery, Braze recommends that your campaign’s segment filters allow for at least a 3-day window. For instance, instead of using the filters “first used more than 1 day ago” and “first used less than 3 days ago,” we recommend using the filters “first used more than 1 day ago” and “first used less than 4 days ago.” This is because time windows of less than 3 days may result in some users falling out of the segment before their optimal send time is reached.

It is also important to be aware of the limitations of using Intelligent Delivery within the first week of a user’s lifecycle. A new user will have limited data for Intelligent Delivery to use in determining the optimal time to send a message. It can, however, still be valuable. Consider a user that has recorded only one session. The time in which that user recorded their session could very well be the best time to attempt to engage them. Intelligent Delivery would only use data from the user’s first session, and as such would engage the user at that time. In general, Intelligent Delivery can more effectively calculate the optimal send time later in a user’s lifecycle.

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