Create test plans

[CXL (CXL Playbooks)]

47 Playbooks

Use existence testing in CRO

Find out which elements help and hurt your conversion rate.

Run marketing experiments

Create better A/B testing programs by running a pre-registration process.

Test your checkout process

Ensure that everything is working correctly before you launch your web shop.

Planning AB testing

16 Playbooks

Develop an A/B test hypothesis

Increase the effectiveness of your website by solving problems that prevent users from using the website to the fullest potential.

Use A/B testing and personalization together

Increase customer conversion rates by talking to their needs on an individual level.

Choose ecommerce A/B test ideas

Determine what changes you can make to help your ecommerce users shop more easily, and buy more.

A/B test landing page opt-in forms

Improve landing page opt-in form conversion rates.

Prioritize your A/B tests

Increase your testing efficiency to generate a better return on investment.

Run A/B tests in a small company

Improve user experience and engagement on low-traffic sites.

A/B test transactional emails

Make data-based improvements and generate more revenue.

Run Split Path tests to optimize customer journeys

Convert visitors and improve UX.

Use UX research to create A/B tests

Improve A/B test conversion results by optimizing tests beforehand.

A/B test content headlines

Find winning variations that drive more traffic and increase user engagement.  

Choose a number of variations for A/B/n tests

Create tests that strike a good balance between data quality and efficiency.

Get A/B testing right

Get a better return on investment on your A/B tests and increase revenue.

QA your A/B tests

Get better results with your tests and reduce wasted effort.

Prepare an A/B test for websites with low traffic

Improve your conversion rate.

A/B test forms to reduce abandonment

Find ways to increase conversion rates on your web forms.

Establish a baseline for A/B testing goals

Define a starting point for website conversion goals against which you can assess progress and outcomes of future A/B testing efforts.

Apply testing logic to the hypothesis creation

Create hypotheses that have a higher likelihood of being true.

Write test hypotheses

2 Playbooks

Structure a hypothesis

Use a scientific approach for experimentation and create consistency in your experimentation processes.

Translate a substantive hypothesis into a statistical hypothesis

Design A/B tests that give you the important answers your business needs to change and grow.

Set up a landing page testing framework

Increase the conversion rate of your landing pages.

Test optimization

5 Playbooks

Track and mitigate uplift decay

Access the chart properties on the right side of the panel and use the search option to find your new blended data set.

Move past the local maximum

Generate more website traffic and increase the user retention on your website.

Choose a strategy for running multiple tests

Determine how your goals align with different test methods.

Increase your testing velocity

Calculate key testing metrics to test faster and speed up your company’s growth.

Prevent Validity Threats

Prevent your business getting wrong data that can affect your long term goals.

Test prioritization

8 Playbooks

Prioritize multiple hypotheses using PXL model

Create a clear roadmap to guide your work and know what hypotheses to test first.

Prioritize conversion tests

Get the biggest testing gains with the least amount of effort.

Focus testing efforts on increasing revenue

Focus your optimizing efforts on increasing revenue on your website.

Decide what to test next

Make better choices to improve funnel conversions.

Decide what to test when you have no data

Deliver the most impact when you have no data on current performance.

Use experiment canvas in CRO

Formulate a clear hypothesis that is ready to be tested and run effective and efficient experiments in a common language.

Build and maintain a testing roadmap

Improve your resource planning and ensure a holistic approach to optimization. 

Prioritize hypotheses based on ICE model

Prioritize growth experiments with a structured scorecard.

Test sample playbooks

3 Playbooks

Avoid sample pollution

Get statistically significant and relevant data for your A/B test analyses.

Estimate required sample size for an experiment for difference in means

Design A/B tests based on continuous metrics which are usually more informative than conversion rate tests.

Estimate required sample size for an experiment for difference in conversion rates

Design A/B tests based on binomial metrics like conversion rate per user, subscribe rate per user, and others.