Create a Hypothesis
Creating a hypothesis must result from a problem that you are trying to fix by improving your site in some way. A hypothesis must be backed by data to ensure that the result you are predicting is beneficial to the company and yields improvement. If your data does not coincide with your hypothesis, you would need to change your hypothesis. This data can be viewed through Google Analytics, which will help give you insights on many different parts of your site and visualize what parts need attention. An example of a hypothesis could be based on page scrolling. If you notice users are only looking at 1/3 to 2/3 of your page and there is important information at the bottom you want them to see, then you may have to change the layout or remove parts of it. If your page had a recipe on it, but the recipe was at the bottom then the hypothesis could be, “Moving the recipe to the top of the page and implementing a ‘Read More’ button in order to still provide additional information to the user.” The next step is to test the hypothesis using A/B testing.
A/B Testing?
According to Google’s help center, “A/B testing is a randomized experiment using two or more variants of the same web page (A and B). Variant A is the original. Variants B through n each contain one or more elements that are modified from the original.” This will help introduce customers or users a more wider variety of experiences while not forcing the business to create a whole new site from scratch. It saves a lot of time and money while also giving necessary data out to the business to better understand what customers are favoring compared to other variations.
Creating an A/B test starts with figuring out something that you can test, whether it is changing something small like the size of a picture or parts of text, that gives you a variation that is testable. This also may require creating a hypothesis in order to understand what result you are expecting to get from the tests. After you begin to fully understand what you can test, your variations can become larger and more in-depth. Google gives step by step directions for how to create an A/B test:
In this experiment, we’ll test changing the color of a button:
- Go to your Optimize Account (Main menu > Accounts).
- Click on your Container name to get to the Experiments page.
- Click CREATE EXPERIMENT.
- Enter an Experiment name (up to 255 characters).
- Enter an Editor page URL (the web page you’d like to test).
- Click A/B test.
- Click CREATE.
Harvard Business Review gives a bit more insight about A/B testing and how it is utilized and analyzed by businesses that I attached here if you would like to learn more about A/B testing.