As the intelligence layer for Iterable’s platform, Nova helps teams make better decisions and act on them fast. It learns from real-time data to predict what will work, to create content, and to take action, so you keep pace with your customers and can easily evaluate what’s working and fix what isn’t.
Nova Intelligence features fall into three areas: decisioning (when, how often, and where to message), insights (who’s engaged, who’s likely to convert, and who’s ready for a fresh touch), and agents (natural language turned into answers and actions across the platform using your Iterable data).
# In this article
# Before you use Nova Intelligence features
Nova 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 Nova Intelligence
If you’re just getting started with Iterable's AI features, Nova Agent is a great place to start. Simply ask the agent a question or for help with a specific task, and get guidance immediately. It's the easiest way to simplify your workflows and get more done in less time.
Then, if you want help deciding how to best optimize your campaigns, consider using 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 (with an STO-specific experiment).
When you’re ready to further optimize user engagement and gain valuable insights about your users, 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.
# Nova Agent
Nova Agent interprets your natural language prompts to make it easier for you to review campaigns, ask analytics-based questions, create and review experiments, and create and validate Handlebars.
You can use it to:
- Review a template before you send it
- Learn about campaign analytics
- Set up experiments and get useful insights
- Create and validate Handlebars
- Get answers to general questions about Iterable
For more information, see Using Nova Agent.
# Decisioning
Decisioning features tune delivery for each person based on engagement patterns, so you spend less time manually balancing send times, channels, and frequency caps.
Send Time Optimization helps ensure messages go out when each user is most likely to engage with them. It can be used with blast campaigns to improve the Email Open Rate, Email Click Rate, and Push Open Rate campaign metrics.
Frequency Optimization chooses a personalized cap for how many email, SMS, and push notifications each user receives in an Iterable project, so everyone gets the right volume for each channel and message type.
Channel Optimization sends messages on the channel each user is most likely to engage with. It is helpful when you want to alert users to time-sensitive or in-the-moment messaging on the channel where they’re most likely to see it.
# Insights
Insights-related features label and rank users from your first-party data so you can segment, trigger, and retarget with confidence.
Brand Affinity™ generates labels for each user that reflect their level of engagement with your brand. You can use those labels in segmentation, campaigns, journeys, data feeds, and Catalog collections to send relevant, personalized messages that support retention, nurture relationships, and mitigate churn.
Predictive Goals identifies which customers are most likely to convert on the business goals you define, so you can build experiences that match their interests and drive the outcomes you care about. It analyzes relevant user properties and first-party data (such as purchase, system, and custom events) and surfaces segments you can use across Iterable. You can also review Predictive Goals’ Explainable AI data to understand what’s driving predictions and inform next steps.
Next Best Action helps you engage customers who are strong candidates for retargeting with a fresh version of a campaign they’ve seen before.
# AI-assisted content and journeys
These features don’t replace your voice or strategy—they help you draft and structure work faster inside the editor.
Copy Assist enhances and speeds up writing copy for 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.
Journey Assist makes creating new journeys and updating existing ones easier. Describe the experience you want for your users or choose a prompt, review or customize the suggested journey flow, and when you’re happy with it, generate a customizable journey with a single click.
# Want to learn more?
For more information about some of the topics in this article, check out these resources. Iterable Academy is open to everyone — you don't need to be an Iterable customer!
Iterable Academy
Support docs