Maximizing Conversion Optimization Through A/B + Multivariate Testing

Traffic arriving to your site must convert for positive ROI:

A/B + Multivariate Testing

What is the difference between A/B and multivariate testing?

Testing different versions and design combinations for your web pages can improve click rates and conversions.

A/B testing – also known as split testing – compares two or more versions of a live webpage to reveal which messaging performs better. When running an A/B test, you will split your web traffic among the different versions. It is typically used when making large changes, such as a redesign. A/B testing allows you to sample alternative text, images, or calls to action to see which elements garner the highest conversion rates. 

Multivariate testing is similar to A/B testing but compares more variables simultaneously. Slight changes can be made to various sections. This will provide data about how visitors interact with the site and which combination of variables, such as the color, font, and size of a button, performs best. Multivariate testing works better with high-traffic sites – since more changes are being tested, traffic will be divided among more options and it takes time to gain enough data.

When to A/B test

  • Before and after redesigning your website.
  • Following a change in a website feature such as the shopping cart.
  • When evaluating online offers or product descriptions.
  • To improve conversion rates.

How to evaluate an A/B test

  • Check how users interact with your site.
  • Look at which design improves conversion rates.
  • Find which design or feature attracts the most traffic to your site.

When you should do a Multivariate Test

  • If your webpage generates a high number of unique visitors per month.
  • To learn more about how design affects the interaction between variables.
  • To discover which design element is getting the best results.

Multivariate Testing Analysis

You can analyze the multivariate statistics assuming there are no interactions or with interactions. Multivariate testing can help you identify where to focus resources in the future.

 

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