๐Ÿ‘‹๐Ÿป Introduction
โœ๏ธ Context for prototype task
Text Statement
๐Ÿงช Please familiarize yourself with [Design A]
Prototype Task
โ“ How do you feel about the overall page?
Emoji
โ“ How is the amount of information provided in the page?
Numerical Scale
โ“ How likely do you want to learn more about the provided content?
Numerical Scale
๐Ÿงช Please familiarize yourself with [Design B]
Prototype Task
โ“ How do you feel about the overall page?
Emoji
โ“ How is the amount of information provided in the page?
Numerical Scale
โ“ How likely do you want to learn more about the provided content?
Numerical Scale
๐Ÿ‘‹๐Ÿป Thank you
Copy testing

A/B test variations of landing pages

Have multiple multiple landing page design variations? Use this A/B testing template to import prototypes and get user feedback to make data-driven decisions.

Study objectives

  • Measure the impact of landing page variations on user engagement metrics such as time on page, scroll depth, and interaction with interactive elements (e.g., videos, sliders, quizzes). Understand which elements contribute to increased user engagement and interest.
  • Determine whether variations that closely match user expectations result in higher conversion rates and better user satisfaction.
  • Test variations of design elements such as color schemes, imagery, typography, and layout to determine which combinations enhance visual appeal and facilitate user navigation and comprehension.
  • Use insights from A/B testing to iterate on landing page designs, continuously refining and optimizing performance over time. Implement incremental changes based on data-driven learnings.

A/B test your landing page variations

Determine which design aligns best with your users with A/B testing

Best practices for A/B testing landing pages

  • Focus on one variable at a time: Test one variable (e.g., headline, call-to-action, layout) at a time to isolate the impact of each change on user behavior. This allows for clearer interpretation of results and more targeted optimization efforts.
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  • Counterbalance your designs: To minimize any potential bias in the ordering effect, make sure that half of your participants engage with design A first and vice versa.
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  • Iterate based on insights: Analyze the results of each A/B test and draw actionable insights to inform future optimization efforts. Use the findings to iterate on landing page design, messaging, and user experience to continually improve performance.
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Getting started

1

Create an account and log in to your Hubble account.

2

Find and select the template to use.

3

Import Figma prototypes and edit the questions as you see fit.

4

Run pilot tests with internal users (ideally, people that are not a part of your project).

5

Preview the study and check if you need to make any last minute changes.

6

Publish the study and wait for the results to come in.

Frequently Asked Questions

Why is A/B testing landing pages important?

Landing page sets the first impression of your product. A/B testing allows you to identify and implement changes to landing page elements, such as headlines, images, calls-to-action (CTAs), and page layout, that can lead to improved conversion rates and overall campaign effectiveness.

What elements of landing pages can be tested?

Various elements of landing pages can be tested, including headline variations, CTA button colors, CTA button text, form length and fields, images or multimedia content, page layout and design, and overall messaging.

How frequently should I conduct A/B tests for landing pages?

The frequency of A/B testing for landing pages depends on factors such as campaign objectives, traffic volume, and the rate of change in your target audience's preferences. It's generally recommended to test regularly to identify and capitalize on optimization opportunities, but the exact frequency may vary based on your specific circumstances.

How many variations can I test in an A/B test for a landing page?

While A/B testing typically involves comparing two variations (A and B), you can test multiple variations simultaneously using multivariate testing or sequential testing methodologies. However, it's important to maintain statistical rigor and avoid testing too many variations at once to ensure reliable results.

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A/B test your landing page variations

Determine which design aligns best with your users with A/B testing