When to use AI Optimize

Traditional tests and manual personalizations give you direct control over how experiences are delivered.

AI Optimize doesn’t replace either one. It adds an adaptive layer that uses machine learning to learn from visitor behavior and available signals, then changes which variations visitors see over time.

Test

AI Optimize for tests

Personalization

AI Optimize for personalization

Use AI Optimize when you:

• Have several ideas or combinations to explore
• Want delivery to adapt as performance changes
• Want to reduce exposure to weaker-performing variations
• Have lower traffic and may struggle to reach significance with a traditional test
• Don’t need to stop and declare one permanent winner

The optimization type still matters: you’re still testing or personalizing. AI Optimize changes how variations are delivered.

What you’ll configure

AI Optimize still starts with familiar building blocks:

AI Optimize with testing

A traditional test uses the traffic split you configure to compare variations and determine which performs best overall.

AI Optimize has a different purpose: continuously adapt variation delivery to maximize conversions as visitor behavior changes.

Imagine you’re exploring three homepage headlines:

1. A benefit-focused headline
2. A feature-focused headline
3. A proof-focused headline

At first, AI needs to explore the different options. As it gathers data, it can adjust delivery based on which variations are more likely to drive the target goal for different visitors.

That means weaker-performing variations can receive less exposure while stronger-performing variations receive more. That allocation can continue changing as AI learns.

AI Optimize with personalization

Manual personalization depends on rules you define:

Enterprise audience → Enterprise variation

With AI Optimize, you don’t need to manually define every audience-to-variation match. Instead, AI learns which variations are more likely to work for different visitors based on the signals available to it.

The goal is still personalization: different visitors may respond best to different experiences. What changes is who decides which variation they receive.

The audience still determines who is eligible for the optimization. AI Optimize determines which variation an eligible visitor sees.

Build and launch with AI Optimize

The setup should feel familiar because you’ve already built a traditional test and a manual personalization. You’ll:

1. Create your AI Optimize experience. Choose the page or experience you want to optimize.
2. Build your variations. Give AI meaningful options to explore.
3. Choose the target goal. AI Optimize uses this outcome to decide what to optimize toward.
4. Set an audience, if needed. Limit the optimization to a particular group of visitors.

Now that you know what changes when AI Optimize takes over variation delivery, use the walkthrough below to practice building an AI-optimized experience from start to finish.

Give AI useful options

AI Optimize works best when the variations give it meaningful differences to learn from. If every variation says essentially the same thing, there isn’t much for the system to explore.

Give it ideas that reflect real hypotheses, such as:

• Feature-focused vs. benefit-focused messaging
• Short vs. detailed copy
• Different value propositions
• Different imagery
• Different calls to action

The same principle from earlier still applies: start from a real opportunity and give each variation a reason to exist.

Ready to continue?

Continue on to the next section where you’ll learn how to interpret the results of traditional tests, manual personalizations, and AI-optimized experiences — because each one asks you to look at performance a little differently.