How do I do multivariate testing on a website?

Multivariate testing on a website means testing multiple elements at the same time to learn which combination performs best.

1) What to test

Pick elements that matter to your goal, for example:

• Headline
• CTA button text/color
• Hero image
• Form length
• Pricing layout

Example:

• Headline: 2 versions
• CTA: 2 versions
• Hero image: 3 versions

That creates 2 × 2 × 3 = 12 combinations.

2) Make sure multivariate testing is appropriate

Use it when:

• You have high traffic
• You want to understand which element matters most
• You have enough conversions to measure differences reliably

If traffic is low, a simple A/B test is usually better.

3) Create variations

For each element, define variants clearly:

• Headline A / B
• CTA A / B
• Image A / B / C

Keep everything else the same so results are attributable.

4) Set a clear metric

Choose one primary metric, such as:

• Conversion rate
• Click-through rate
• Add-to-cart rate
• Form completion rate

Avoid changing the main metric mid-test.

5) Use a testing tool

Common tools:

• Optimizely
• VWO
• Adobe Target
• Convert
• Google Optimize is discontinued, so don’t use that

These tools can randomly assign users to combinations and track performance.

6) Split traffic randomly

The tool should show visitors different combinations evenly and randomly.
Example:

• 1/12 of users see each combination

This helps ensure results are unbiased.

7) Run long enough

Let the test run until:

• You reach statistical confidence
• You’ve collected enough sample size
• You cover normal traffic patterns, including weekdays/weekends

Don’t stop early just because one variant looks good.

8) Analyze results

Look at:

• Overall winning combination
• Which element had the biggest impact
• Interaction effects

Example:

• CTA color may matter only when paired with a certain headline

Good tools often show main effects and interaction effects.

9) Implement the winner

Once you have enough evidence:

• Roll out the best-performing combination
• Monitor post-launch performance
• Save learnings for future tests

Important tips

• Don’t test too many elements at once unless you have lots of traffic
• Keep design changes meaningful
• Make sure tracking is accurate
• Avoid overlapping experiments that interfere with each other

Simple example

You want to improve signups on a landing page:

• Headline: 2 versions
• CTA text: 2 versions
• Image: 2 versions

That’s 8 combinations. The test shows:

• Best headline: “Start Free Today”
• Best CTA: “Get Started”
• Best image: product screenshot

You then deploy that combination and measure signup lift.

If you want, I can also help you with:

1. a step-by-step plan,
2. sample size calculation, or
3. how to design a multivariate test in Optimizely/VWO.