{"id":2466,"date":"2018-11-15T22:07:50","date_gmt":"2018-11-15T15:07:50","guid":{"rendered":"https:\/\/blog.travelpayouts.com\/en\/?p=2466"},"modified":"2021-10-02T20:51:26","modified_gmt":"2021-10-02T17:51:26","slug":"a-b-and-split-tests","status":"publish","type":"post","link":"https:\/\/www.travelpayouts.com\/blog\/a-b-and-split-tests\/","title":{"rendered":"A\/B Tests \u2013 What Are They and How to Perform Them Properly"},"content":{"rendered":"

What Are A\/B Tests?<\/h2>\nA\/B tests or split testing \u2013 is the research method where you compare the baseline data with the test one.\n\nFor example, having the search form for the last-minute offers (option A) you suppose the form\u2019s loud color should increase your sales. To clarify the more efficient variant, you should practice both of them and then make a comparison on the basis of statistically significant traffic. That\u2019s A\/B tests.\n\nTwo options are tested, as a rule. However, no one can stop you from testing several assumptions, for example, to check a flight ticket search form in various colors. You check two options, and then you test the winner plus one extra option.\n\nNote that there\u2019re no gold standards in marketing. If you ever see or hear that one variant works for somebody, it could be nothing for you and your target audience. It\u2019s better to rely on your own test results but not on theoretical information, that generates income for others.\n

Why You Should Do Split Tests?<\/h2>\nNow you make $5 from 1000 visitors, but you probably can get $10 or even more. To find out the most profitable strategy you should perform tests.\n\nIt\u2019s necessary to determine the purpose before testing. Suppose your aim is to convert more leads into flight tickets sales. For this purpose, you try to place a calendar widget instead of the traditional search form. To find the best option you must measure the results.\n\nNot all tests deal with an increase in income. You can test the arrangement of the affiliate tools and watch the changes in such behavioral factors as length of time spent at the site, the percentage of \u201creads up\u201d. Ultimately, it can influence the number of visitors that come back to your project within a month.\n\nRegardless of your objectives within A\/B tests, you should define the goal before you start.\n

What Should You Test on the Page?<\/h2>\nYou check your assumptions and forecasts in order to see how it could be better than it is now. That\u2019s why you make the following changes in your project:\n