What is A/B Testing?

Definition and explanation of A/B testing

• A/B testing, also known as split testing, is a method of comparing two versions of a landing page to determine which one performs better.
• A/B testing involves creating two versions of a page, A and B, and testing them against each other to see which one yields the highest conversion rate.
• A/B testing is an ongoing process that involves making incremental changes to a page in a bid to fine-tune a campaign for maximum conversions.

How A/B testing works

• A/B testing works by randomly assigning traffic to each page variant based on a predetermined weighting.
• For example, if you’re running a test with two landing page variants, you might split the traffic 50/50 or 60/40.
• The main factor that decides how much weight to ascribe to page variants is timing.

Benefits of A/B testing for your landing page

• A/B testing can lead to higher conversion rates and greater ROI from all traffic sources.
• A/B testing can help you de-risk design layout and messaging updates.
• A/B testing provides valuable insights into user behavior and helps you better understand your customers and visitors.

Why Do We Do A/B Testing?

Enhanced user experience

• A/B testing helps you identify problem areas on a landing page and adapt to create a more free-flowing user experience.
• Confusing copy, jarring color schemes, and hard-to-find sign-up buttons are all potential stumbling blocks that could detract from the user experience.

Low-risk, high-reward approach

• Since A/B testing is an incremental process, the risk of a conversion rate falling off a cliff during any given test is relatively minimal.
• If a change causes a significant dip in conversions, you can simply change it back and use that knowledge moving forward.

Understand your audience better

• The discoveries you make by running A/B tests will improve your understanding of what drives a target audience’s behavior.
• A/B testing helps you identify problem areas on a landing page and adapt to create a more free-flowing user experience.

Increase conversion rates and revenue

• Even small changes can have a massive impact on conversion rates—sometimes by as much as 300%.
• A/B testing is an ongoing process that involves making incremental changes to a page in a bid to fine-tune a campaign for maximum conversions.

Examples of Successful A/B Testing

Case studies of A/B testing success

• A/B testing can be an extremely powerful method for reliably improving landing page conversion rates.
• A/B testing helps you identify problem areas on a landing page and adapt to create a more free-flowing user experience.

How to Plan an A/B Test

Identify key metrics and goals

• Before starting an A/B test, you should get super clear on the outcome you’re hoping to achieve.
• Formulating a hypothesis is a crucial step in the A/B testing process.

Form a hypothesis

• A hypothesis is a statement that predicts the outcome of an A/B test.
• A good hypothesis should be specific, measurable, achievable, relevant, and time-bound.

Choose a testing approach (A/B, multivariate, or split testing)

• A/B testing is the most straightforward and robust approach to compare two versions of a landing page.
• Multivariate testing builds on the core mechanism of A/B testing to test for a higher number of variables on a page.

A/B Testing Ideas for Your Landing Page

Headline and copy optimization

• Headlines are a crucial element in A/B testing.
• You can test different headlines and see which ones work best.

Image and video testing

• Images and videos are critical elements in A/B testing.
• You can test different images and videos and see which ones resonate more with your audience.

Opt-in form and CTA button testing

• Opt-in forms and CTA buttons are critical elements in A/B testing.
• You can test different opt-in forms and CTA buttons and see which ones work best.

Countdown timer and price point testing

• Countdown timers and price points are critical elements in A/B testing.
• You can test different countdown timers and price points and see which ones work best.

Page length and layout testing

• Page length and layout are critical elements in A/B testing.
• You can test different page lengths and layouts and see which ones work best.

A/B Testing Terminology 101

Variant, control, champion, and challenger

• A “variant” is a new version of a landing page, ad, or email included in an A/B test.
• A “control” variant refers to the original or existing version of a webpage, email, or marketing material.

Statistical significance and confidence levels

• Statistical significance is a crucial concept in A/B testing that determines the reliability of the results.
• Confidence levels are used to determine the reliability of the results.

Common A/B Testing Mistakes

Failing to account for past results

• Failing to account for past results can lead to inaccurate conclusions.
• You should always consider past results when interpreting A/B test results.

Not running the test for long enough

• Not running the test for long enough can lead to inaccurate conclusions.
• You should always run the test for a statistically significant amount of time.

Testing too many variables at once

• Testing too many variables at once can lead to inaccurate conclusions.
• You should always test one variable at a time.

How to Run an A/B Test

Create variants and set up the test

• Creating variants involves developing at least one new version of the content or element you want to test.
• Setting up the test involves determining the sample size, test duration, and test goals.

Run the test and collect data

• Running the test involves launching the test and collecting data.
• Collecting data involves tracking key metrics and analyzing results.

Analyze results and declare a winner

• Analyzing results involves interpreting the data and determining the winner.
• Declaring a winner involves determining which variant performed better.

A/B Testing Metrics to Measure

Conversion rate metrics

• Conversion rate metrics include metrics such as conversion rate, click-through rate, and bounce rate.

User experience and visitor behavior signals

• User experience and visitor behavior signals include metrics such as time on page, pages per session, and exit pages.

Marketing campaign, funnel, and business metrics

• Marketing campaign, funnel, and business metrics include metrics such as cost per acquisition, customer lifetime value, and return on investment.

Analyzing A/B Test Results

Review goal metrics and related signals

• Reviewing goal metrics and related signals involves analyzing the data and determining the winner.

Confirm or reject the hypothesis

• Confirming or rejecting the hypothesis involves determining whether the results support or reject the hypothesis.

Come up with new questions and ideas

• Coming up with new questions and ideas involves using the results to inform future A/B tests.

Landing Page Testing Across Channels

Testing on different devices and browsers

• Testing on different devices and browsers involves testing the landing page on different devices and browsers.

Testing on social media and email channels

• Testing on social media and email channels involves testing the landing page on social media and email channels.

Top Landing Page Testing Software

Overview of popular testing tools

• Popular testing tools include tools such as VWO, Unbounce, and Optimizely.

Creating a Winning A/B Testing Strategy

A/B testing and multivariate testing approaches

• A/B testing and multivariate testing approaches involve using A/B testing and multivariate testing to inform the testing strategy.

Using data to inform your testing strategy

• Using data to inform your testing strategy involves using data to determine which elements to test and how to test them.

Conclusion

Recap of key takeaways and best practices for A/B testing your landing page

• A/B testing is a powerful method for improving landing page conversion rates.
• A/B testing involves creating two versions of a page, A and B, and testing them against each other to see which one yields the highest conversion rate.
• A/B testing is an ongoing process that involves making incremental changes to a page in a bid to fine-tune a campaign for maximum conversions.