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description: "Glossary of terms used in Dalton and A/B testing — multi-armed bandits, conversion goals, statistical significance, and more."
---

# Glossary

Key terms used throughout Dalton and this documentation.

## A

### A/B Test
A method of comparing two versions (A and B) of a page to see which performs better. Dalton uses a more advanced approach called multi-armed bandits, but the goal is similar.

## B

### Baseline
Your original page without any Dalton modifications. By default, Dalton keeps 20% of traffic on the baseline to measure experiment performance against. This split is adjustable in settings.

### Brand Context
Settings where you define your brand voice, restricted words, and compliance requirements. The AI uses these when generating suggestions.

## C

### Certainty
A percentage (0-100%) indicating how confident Dalton is that a variant performs differently from the baseline. Look for 95%+ certainty before making decisions.

### Conversion
When a visitor completes a desired action (purchase, signup, form submission, click). This is what Dalton optimizes for.

### Conversion Goal
The specific action you want visitors to take. Set this in the experiment settings so Dalton knows what to optimize.

### Conversion Rate
The percentage of visitors who complete your conversion goal. Calculated as: (conversions / visitors) x 100.

## E

### Experiment
A test running on your page with one or more variants. Dalton automatically distributes traffic and measures results.

## H

### High Performer
A variant that has reached statistical significance and is outperforming the baseline. Shown with a green indicator in the dashboard.

## M

### Multi-Armed Bandit
The algorithm Dalton uses to optimize experiments. Unlike traditional A/B tests that split traffic 50/50, bandits automatically shift traffic toward winning variants while still exploring alternatives. See [How the Algorithm Works](/optimization/how-the-algorithm-works).

### Multi-Page Experiment
An experiment that runs across multiple URLs simultaneously. Changes apply to all pages in the experiment.

## P

### Prompt
Instructions you give the AI to generate or modify content. Better prompts lead to better results. See [Prompting Best Practices](/editor/prompting-best-practices).

## S

### Statistical Significance
The point at which results are unlikely to be due to random chance. Dalton shows this as "certainty" percentage. 95%+ is generally considered significant.

## T

### Traffic Allocation
How Dalton distributes visitors between your baseline and variants. The algorithm automatically adjusts this based on performance.

## U

### URL Split Test
A test comparing completely different page URLs rather than element-level changes. Used for major redesigns or testing features Dalton can't modify directly.

## V

### Variant
A modified version of your page being tested against the baseline. Each experiment can have multiple variants.

### Visitor
A unique person viewing your page. Dalton tracks visitors (not page views) to ensure accurate experiment data.