Iterable AI offers a number of features to help you reach audiences in extremely personalized ways. The insights from each feature provide unique value, and when used together, they support a robust view of your customers that you can use to evaluate existing campaigns and build successful future communications.
Features include:
Brand Affinity™ generates labels for each user that reflect their level of engagement with your brand, for use in various parts of Iterable.
Channel Optimization sends messages to each user on the channel that they are most likely to engage with.
Copy Assist enhances and expedites the process of writing copy for your campaigns. When you're creating a campaign or template, enter text as you always do, and Copy Assist generates alternative suggestions for you to consider.
Predictive Goals identifies which customers are most likely to convert on your business goals in the future, so you can create experiences that match their interests and promote the outcomes you seek.
Send Time Optimization helps ensure that messages are sent when each user is most likely to engage with them.
Before you use Iterable AI features
Iterable AI features provide the best insights for projects that have at least three months of active user data. To ensure that you get the optimal results, familiarize yourself with each feature’s data recommendations before you use it.
Getting Started with Iterable AI
If you’re just getting started with Iterable AI, you might start with Send Time Optimization to send messages to users when they are most likely to engage with them, or Channel Optimization to send messages where they are most likely to engage.
After you start using these features, Iterable sends messages based on historical engagement data that it reassesses weekly, weighting the newest project data most heavily. To evaluate the impact of each feature, you can compare campaigns that use them against those that don’t in Campaign Analytics and Experimentation.
When you’re ready to further optimize user engagement, consider using Brand Affinity to generate labels for each user that reflect their sentiment toward your brand. You can use these labels in segmentation, campaigns, journeys, data feeds, and Catalog collections to send relevant, personalized messages that maximize retention, nurture customer relationships, and mitigate churn before it happens.
And, if you’re looking to take the next step to optimize future conversions, add Predictive Goals to your plan. Using criteria you define, Predictive Goals analyzes your project's relevant user properties and first-party data (like purchase, system, and custom events) and returns an interactive chart where you can select user segments for use in other parts of Iterable. You can also review Predictive Goal's Explainable AI data to gain additional insight into your prediction and further inform next steps.
Want to learn more?
Check out these articles for more information about Iterable AI features:
Comments
0 comments
Article is closed for comments.