Understanding Your AB Split Test Results Dashboard

Running an A/B test is only half the battle. The real value comes from reading your results correctly. The AB Split Test dashboard gives you a clear view of how each variation is performing, but if you’re new to testing the numbers might look confusing at first.

Here’s a breakdown of what each part of the dashboard means and how to use it.

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1. Status Banner

At the top of the results screen, you’ll see a status indicator. This tells you what stage your test is in:

• Collecting data – The test is live and visits/conversions are being tracked.

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2. Goals Dropdown

Every test can have one or more goals (conversions). For example:

• A button click

• A form submission

• A “thank you” page view

• A piece of text appearing on a page

The dropdown lets you switch between goals to see how each variation performs against different metrics.

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3. Results Table

Let’s break down each column:

• Variation – Each row represents a version of your page or post. The first is usually the control (original), and the others are variations.

• Visits – How many people saw this variation.

• Conversions – How many times the selected goal was completed.

• Conversion Rate – Conversions ÷ Visits, shown as a %.

• Chance of Winning – A probability estimate that this variation would continue to win if the test ran longer.

• Uplift – The relative improvement (positive or negative) compared to the control.

👉 In the example screenshot:

• Both variations show a 100% conversion rate because every single visit converted.

• With such a tiny sample, uplift is 0% and “Chance of Winning” isn’t meaningful yet.

The takeaway? Don’t end a test too early. More data = more reliable results.

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4. Conversion Graph

Below the table you’ll see a graph plotting visits (x-axis) against conversions (y-axis).

• The steeper the line, the better the conversion rate.

• Over time, you’ll be able to see which variation is trending ahead visually, not just in the numbers.

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5. A Note on Statistics: Bayesian vs. Multi-Armed Bandit

You might notice that your tests can run in two different modes: Bayesian or Multi-Armed Bandit.

• Bayesian gives you a probability (“Chance of Winning”) after collecting enough data to reach significance.

• Multi-Armed Bandit (Dynamic Traffic Steering) shifts traffic automatically toward the best-performing variation as conversions come in, so you capture more wins while testing.

Both methods are powerful but serve slightly different purposes. We cover this in detail in our post: Bayesian vs. Multi-Armed Bandit: What’s the Difference?

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Wrapping Up

The AB Split Test results dashboard is designed to be straightforward:

• Status tells you what stage the test is in.

• Goals let you measure different outcomes.

• Results Table + Graph show you how each variation is performing.