Creating Hypothesis And Running A/B Testing

Creating a Hypothesis

A hypothesis is created when here is a problem you need solved. When there is an issue on your website, a hypotheses is created to help improve your site. Hypotheses need to be backed up by data in order to make sure it can actually help improve things. This data comes from Google Analytics which gives you multiple options of data. If the data found, doesn’t match the hypothesis, it will need to be changed in order to ensure improvements to the website. Google analytics will show you the certain parts of the website that need to be improved. A very common example that all sites could potentially look at is page scrolling. If a site created a page scrolling hypothesis, they could use the data from Google Analytics, to see how far users are scrolling. This helps determine where information on the site can be put. If theirs a video at the bottom, but people are not scrolling down there, a hypotheses could be created. This hypothesis could simply be, ” Moving the video to the top of the page”. You could use google analytics to determine if this actually worked.

A/B Testing!!

A/B testing is used when trying to see what format is the best fit for you’re website. Tests are set up, so different users see different things. Depending on what percentage is used, different people will see different formats of the website. These tests will test the original (A) and the new (B) and shows a comparison. A certain action needs to be set be tested, but this really helps the website owner determine which format to use. Google gives a step by step outline on how to do this and it is shown below.

  1. Go to your Optimize Account (Main menu > Accounts).
  2. Click on your Container name to get to the Experiments page.
  3. Click CREATE EXPERIMENT.
  4. Enter an Experiment name (up to 255 characters).
  5. Enter an Editor page URL (the web page you’d like to test).
  6. Click A/B test.
  7. Click CREATE.

Read More!!

I have provided an article below that shows more about A/B Testing

https://vwo.com/ab-testing/

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