A/B Testing vs Multivariate Testing for Conversion Optimization

When you make your decisions based on data then only, you can do the maximum optimization of your website for driving conversions. A/B testing and multivariate testing are two common methods used to do this. Both get you closer to understanding what makes your audience tick, but do so for different reasons and come in various formats.

This blog will cover the fundamentals of both A/B and multivariate testing, discuss how they differ from each other, and help you assess when to use either approach. Nected, low code/ no code platform facilitates A/B testing, enabling you to generate leads more efficiently and optimize your funnel. As we already know that A/B testing is broadly divided into two types which are frontend A/B testing & Backend A/B testing. Nected specializes in backend personalization via its low code no code capabilities, which helps to perform various A/B testing & multivariate testings with eae.

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What is A/B Testing?

A/B testing is an experimentation process where you compare two versions of a webpage or specific elements to determine which one converts the best. Your overall objective is to see if one of the two variables wins — be it another subject line, a call to action in another location on the page or any possible event that generates higher conversions, clicks or user-engagement.

In the case of an A/B test, version A is typically your control (the current iteration of your page) and version B would be the variant (the altered page). The traffic has been divided randomly into the two versions and is collecting data to measure users action. The results-enhanced version becomes the new standard working — live on your website.

For Example: Suppose you own an e-commerce store, and you want to see how changes in the discount strategy you apply impact your sales. When you do your A/B test, then you design two kinds of product pages:

Version A (control): will display a regular product price.

Version B (variant): 10% off discount.

One group of visitors to your website see version A, the other group sees version B and over time you measure how they performed in terms of conversions, average order value, bounce rate etc. And if version B results in more sales (or more revenue), you might choose to roll out the discount to all your pages.

If you want to test only one variable at a time, then A/B testing works the best. Focus on one item (which lets you see how people respond to a specific change, without the noise of trying to test more than one element simultaneously) is required for A/B testing.

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What is Multivariate Testing?

This is more complex than A/B testing and is called multivariate testing. Multivariate testing, analyzes multiple changes at once rather than just two versions of a single element to see which combination of elements performs best. In this way, you can test how elements interact with one another on a page and see which combination provides the most conversions.

In a multivariate test, you change several factors (headlines, images, buttons etc) and end up with multiple versions of the page each having a different combination of these elements. In summary, the idea is to focus on configuring multiple changes to find out which ones are most effective together (as opposed to interpreting the influence of a single variable — typical in A/B tests).

For Example: Imagine you are testing three elements on a product page

1. Which One Would Get Headlines: “Limited Time Offer” or “Exclusive Deal”?

2. Product shot A vs. Product shot B (images)

3. C2A (Call-to-action): buy-now vs add to cart

A multivariate test simultaneously tests all permutations of those points. This means you will get a few versions of the page:

Version 1: Headline 1 with Image A and CTA 1

Version 2: Headline 1, Image A, CTA 2

Version 3: Headline 1, Image B, Button Text 1

- And so on...

The website will display each variant to a set % of your visitors and then the statistical performance of each combination will be calculated. Multivariate testing enables you to see what the most highly engaging and/or converting combination is of elements. This method, however, needs a large amount of traffic to collect decent data for each variation and so is more resource hungry than A/B testing.

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Key Differences Between A/B Tests and Multivariate Tests

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What both A/B testing and multivariate testing do is that these are the very advanced tools to optimize any web pages, there are some fundamental differences between them, which help in determining when you should use which one. Understanding these differences will help you choose the right method for your goals.

Elements Tested: A/B testing is one element of the time features such as a headline or CTA. In contrast, multivariate testing tests for multiple variables at once — evaluating instances in which the different elements interact with one another.

Complexity: A/B testing is simple and more intuitive so it can work for you when you are just starting or only wish to make small changes. It is much more complex than the A/B testing and it allows you to test several elements together for different variations and require tools of a higher order as well.

Sample Size: You need less traffic to conduct an A/B test as you are testing only two versions of a page. In contrast, multivariate testing requires larger traffic to examine multiple combinations at a time (each for which there has to be a large enough sample size), which can be very tedious.

Insights Provided: The fact that you are testing only one aspect at a time, provides stronger insights which are easier to both understand and act on. Although multivariate testing allows you to gain broader insights into how multiple elements interact with each other, it can also be more difficult to analyze.

Time and Resources: Since A/B testing works on less variables it uses less time and resources to be run in most cases. Because of the more complex setup and larger sample sizes required, multivariate testing can frequently involve slower set up times and longer processing in general to complete and analyze than A/B testing.

Now let us take a quick look on when should you choose A/B or split testing & When should you use the multivariate testing:

When to Use A/B Testing: Should be used for relatively minor and specific enhancements to a single portion of your page. The faster you want to see the difference with one particular change.

When to Multivariate Testing: Multivariate testing is when you want to test multiple elements (e.g. CTAs, form fields) at once and get more granular insights on how these elements interact. For sites with a large amount of traffic and complex optimization requirements, this is the method recommended.

For faster, reliable results, let Nected’s A/B testing guide your optimization strategy.

Conclusion

A/B and multivariate testing gives a reliable amount of power in the hands of businesses when it comes to conversion optimization that allows tracking of user experience improvements based on data. Companies systematically test variations to optimize websites, landing pages and marketing strategies for maximal conversions. Picking a correct type of test, such as A/B or multivariate testing, is essential if you want to deliver results which are beneficial for achieving specific business targets and relevant insights.

Nected optimizes this entire process by empowering through a full suite of A/B testing tools, to test and quickly iterate the best improvements. So with Nected, businesses can maximize their testing strategies and realize faster outcomes that are easily quantified.

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A/B Testing vs Multivariate Testing FAQs

Q1. What is A/B testing, and how does it work?

A/B testing compares two versions of a webpage or app to determine which one performs better in terms of user engagement or conversions.

Q2. What’s the difference between A/B testing and multivariate testing?

A/B testing involves testing two variations, while multivariate testing assesses multiple elements or variations simultaneously to understand which combination works best.

Q3. What is split testing, and how is it different from A/B testing?

Split testing divides traffic between two entirely different versions of a webpage or campaign, while A/B testing modifies only one element at a time.

Q4. When should I use multivariate testing over A/B testing?

Use multivariate testing when you want to test multiple elements (like headlines, images, and buttons) at once, whereas A/B testing is ideal for testing single changes.

Q5. How does A/B testing improve conversion rates?

A/B testing helps improve conversion rates by providing data-driven insights, allowing you to implement the version of a webpage or email that best resonates with your audience.