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Leverage message optimization in a campaign

Learn how to leverage message optimization in action or API triggered campaigns. You’ll see how to target sub-audiences, create message variations by location, enable fallback content, and run multiple experiments within a single campaign. This tutorial also covers how to manage multi-channel campaigns while maintaining message consistency.

Transcript

Hey everyone, here’s a quick demo of the campaign optimization features.

Here in the campaign UI, you can target sub audiences. This button enables you to create these targeting variants. Let’s say, for example, I want to send a particular message to individuals in San Francisco and another unique message to individuals in Chicago. For anyone who doesn’t qualify for either of these audiences, and I want to ensure they still get a message, I’ll go ahead and toggle on this Enable Fallback Content.

I also want to point out that a single campaign can now have multiple experiments. You can see here that I can create experiments that are tied to each targeted sub-audience. Maybe we’re running a few different promotions for our Chicago folks to see which one performs best for that geographic region. I’ll go ahead and hit Create and on to the last step of this demo, authoring the actual content of these messages that will be sent to the respective sub-audiences we’ve identified.

Here you can see we have a multi-action campaign. You’ll see that this experiment spans across both of the actions we’ve specified, the sub-channel and the code-based experience channel.

I’ll click into each of these messages to author the content and then go ahead and review to activate.

In summary, campaigns can now have multiple actions, multiple targeted sub-audiences, and multiple experiments all within a single campaign. Perhaps the most compelling aspect is that these features, when used together, help brands to ensure message consistency across multiple channels, all while simultaneously helping to optimize the best message with the use of experimentation.

Thanks everyone!

For more information about this feature, please see the product documentation.

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