> For the complete documentation index, see [llms.txt](https://docs.abtasty.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.abtasty.com/adaptivecx/getting-started/activate/adaptive-a-b-tests.md).
# Adaptive A/B Tests
Adaptive A/B Tests let you run experiments that compare different variants while accounting for predicted visitor behavior, ensuring you measure true impact across different intent levels.
### Overview
The Adaptive A/B Tests page is where you create and manage experiments. Unlike traditional A/B tests that split traffic randomly, adaptive tests can factor in prediction scores and audience membership when analyzing results, giving you a clearer picture of what works for different visitor segments.
The page has two tabs:
* **Ongoing Adaptive A/B Tests**: Experiments currently running on your site.
* **Archived Adaptive A/B Tests**: Completed or stopped experiments stored for reference.
You can filter by **Device Type**, **Operating System**, and **Channel**.
### Key Concepts
| Term | Meaning |
| ---------------------------- | ------------------------------------------------------------------------------------------------------------------ |
| **Variant** | A specific version of an experience shown to a subset of visitors (e.g., Variant A vs. Variant B). |
| **Control** | The baseline experience against which variants are measured. |
| **Statistical Significance** | The confidence level that an observed difference in performance is not due to chance. |
| **Adaptive Analysis** | Breaking down results by predicted behavior segments to understand which variant works best for each visitor type. |
### Getting Started
{% stepper %}
{% step %}
### Create a New Adaptive A/B Test
Click **Create New Adaptive A/B Test** to begin.
The setup flow covers:
1. **Schedule settings:** Configure your schedule settings
2. **Live QA:** Trigger live QA
3. **Validate JS code**: Validate your JS code to move to the next section
4. **Choose targeting**: Run the test for all visitors or limit it to specific audiences, devices, or channels.
{% endstep %}
{% step %}
### Target and split
* **Select success metrics**: Pick the KPIs that determine which variant wins (conversion rate, revenue per visitor, engagement, etc.).
* **Set traffic allocation**: Decide what percentage of traffic goes to each variant.
{% endstep %}
{% step %}
### Monitor Results
Return to the Adaptive A/B Tests page to track performance. The platform reports results broken down by:
* Overall conversion metrics per variant.
* Performance by predicted behavior segment (e.g., high-intent vs. low-intent visitors).
* Statistical significance indicators.
{% hint style="info" %}
Let tests run until they reach statistical significance before making decisions. Stopping a test too early can lead to unreliable conclusions.
{% endhint %}
{% endstep %}
{% step %}
### Apply the Winner
Once a test reaches significance, you can promote the winning variant to become the default experience for all visitors, or for specific audience segments.
{% endstep %}
{% endstepper %}
---
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