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A/B Testing: 
A/B testing which is also knows as split/bucket testing is a method of comparing two versions of a web page or to see which one performs better. For instance, you can compare two web pages by showing the two variants (which we will call A and B) to similar visitors at the same time. So, the one that gives a better conversion rate, wins!

In marketing and business intelligence, A/B testing is basically a term for a controlled experiment with two variants, A and B. It can be regarded as a form of statistical hypothesis testing with two variants resulting to the technical term, two-sample hypothesis testing, used in the field of statistics.

As the name entails, two versions (A and B) are being compared, which are the same except for one variation that might affect a user's behavior. Version A might be the currently used version (control), while version B is modified in some respect (treatment).

A/B testing as a philosophy of web development contributes the field into line with a broader movement toward evidence-based practice. One of the benefits of A/B testing is that it can be performed constantly on almost anything, particularly since most marketing automation software now, naturally, comes with the ability to run A/B tests on an on-going basis. This allows for updating websites and other tools, using current resources, to keep updated with changing trends.

A/B Testing Process: 

The following is an A/B testing processes you can use to start running tests:

Collect Data: This is deep information gathering stage. It is done in order to have an insight of what pages you can begin optimizing on your site. You can begin with high traffic pages of the website or web-app, and then move to track pages with low conversion rates that need to be improved.

Identify Goals: Identifying goals has to do with conversion, meaning you have to test how your website pages or web apps are converting to profit, such as anything from links, submit buttons, signup pages, pop-ups, newsletters, sales pages, e-mail signups, product purchases, feedback forms, surveys etc.

Generate Hypothesis: This is the process of generating A/B testing ideas, hypotheses or design that will be well-planned and structured to fully optimize the pages with low results and then prioritize these ideas in terms of difficulty of implementation and expected impact.

Create Variations: A/B testing software (like Optimizely), can help make desired changes to an element of your website or mobile app experience. In order words variations are for instance customizing the order of page elements, making changes to color of a button, making dynamic forms behavior, swapping or hiding navigation elements etc. There are many other leading A/B testing tools that comes with dynamic visual editor for easy page customization.

Run Experiment: This is also known as Test-running and wait for visitors to engage! At this point, the pages are being monitored. Visitors interaction and experience with each page is measured and statistically compared to determine their performance.

Analyze Results: Over here, we analyze the results of the experiment. Your A/B testing software used here will analyze the data from the results and show you the difference between how the two versions of your pages performed, and whether there is a statistically significant difference in order to make the best decisions.

A/B Testing Certification: http://scholarsglobe.com/p/certification.html .

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