The Conversion Rate Optimization Process – Part 2/3

The Conversion Rate Optimization Process – Part 2/3
The Conversion Rate Optimization Process – Part 2/3
Hypothesis Development

Launching a test without a hypothesis is like starting a journey without knowing where you’re heading. It’s likely you won’t get what you want out of all your hard effort, time, and money. If you have zero ideas about what your hypothesis should be, our suggestion is to ponder the CRO research topics in Part 1 again and take a closer look at collected data.

Just like your journey, the success of the test depends strongly on how viable your hypothesis is. Then, how can you develop a strong hypothesis? That’s exactly the question we’ll answer in this article.

I. What is a hypothesis?

A hypothesis is an educated guess or prediction, a tentative assumption you make before running a test.

It is important that your hypothesis states clearly what could be changed, the result you’re expecting, and your reasoning. A hypothesis follows this simple formula:

If X, then Y, because of/due to Z.

In CRO, you would follow this syntax:

If A is changed to ….. , (conversion metric) will be improved/harmed because….

Characteristics of a winning hypothesis:

  • It aims to trigger people’s reactions to the on-site changes, either negatively or positively, to see how people perceive your brand. For example, a title informing the event of a sale will create urgency and hypothetically increase conversion.
  • It should be easily tested.
  • It is insightful and provides learning.

Please watch the video below to understand the four different types of buyers and how to sell to them.

A verified hypothesis will determine whether your assumptions are correct. It allows you to make informed decisions about any intended site changes.

Proponents of a hypothesis

A hypothesis includes 3 main parts: the variable, the result, and the reasoning.

1. The variable: an element that can be modified, added or taken away to produce the desired outcome

To find out the appropriate variable, you could consider the following common factors:

  • CTA and CTA button.
  • Product or service information.
  • Value communication.
  • Page copy.

Try to isolate a single variable for A/B testing by studying data collected from Part 1. You choose from the highest valued variables ( for example the most visited page, most viewed items, etc.).

2. The expected outcome: this is normally a measurable conversion metric, CTA or other KPI you are trying to influence

This can be decided by using the current performance data; you have to predict what you expect your experience result to be. Obviously, the ultimate purpose of the CRO process is to increase conversion, but a hypothesis and changing one element can be useful for identifying ways to influence a specific factor.

Please watch this video the get an idea of the right conversion rate optimization mindset.


Learn how you can also increase your store's eCommerce conversion rate today

Learn how you can also increase your store's eCommerce conversion rate today

II. The 3 – step hypothesis development

1. State the problem

You need to first be clear on your conversion goal, what CTA you are expecting, and what’s going wrong that prevents people from reacting to your site in a way that helps you realize your goal.

You can then form a problem that you are looking to solve through testing. After you have a problem in mind, you can start to form a hypothesis. Common problems can be:

  • CTA which is not clear and not visible CTA button.
  • Lack of product or service descriptions.
  • Miscommunicated product/ service value.
  • Page copy which doesn’t speak the clients’ language.

2. Propose Solutions

Based on your research, you should be able to come up with at least one solution about what you should change (reason can be based on customer interviews, user testing, heat map analyses, etc):

  • Choose one isolated variable from the problem-stating step.
  • Brainstorm several changes that can be made with that variable and analyze ways to create the best outcome.
  • Double-check if your research data supports those solutions or not.

3. Impact statement

Consider how the proposed change might impact your problem. This should take into account what you want to test and how it will affect your conversion problem.


A solid hypothesis does not necessarily guarantee a win, but it will guarantee a lesson learned about your clients, no matter what the outcome. Here’s one more learning tip: categorize your results by device, browser, traffic source, and visitor type, so that you’ll have the best chance of determining a winning combination. This also supports your learning process.

Read next: The Conversion Rate Optimization Process - Part 3/3

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