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Statistical Significance In Pay Per Click Ad Testing

Statistical Significance In Pay Per Click Ad Testing

In determining how effective a pay per click ads effectiveness as far in converting

page views to actual clicks on the ad, its curious to know many people dont have a great handle on when to hold, fold em, walk away or run.

As a quick prelude, Pay Per Click administrators like Google and Bing have deep marketing metrics which are a tremendous help to the analytic marketer, which you should be if you want to compete online or anywhere else.

The truth is you can track your marketing in pay per click almost as deeply as youd like, from the minute some unknown surfer types some favorable keywords into the Google search bar, all the way to the point where they purchase something right off your website, if you have an e-commerce site.

Lets just talk about converting impressions to actual clicks on our site. This is known as a click through rate (CTR). A CTR is determined by dividing the number of impressions into the number of people of those impressions who actually clicked on our ad.

Example: Lets say you bid on the keyword phrase Los Angeles VA Refinance, 15 or 20 websites will show on the first page of the search results when someone types in Los Angeles VA Refinance. Each time your ad shows up, you get an impression or page view. With enough page views, eventually someone will click on your ad. Of course, the goal is to get as many clicks relative to page views or impressions as possible.

In the process of testing one Ad against another (A:B testing), most people are waiting far too long before dumping the lesser performing ad to test the better one against a new ad. Unless, the two ads are performing extremely similarly, which most ads dont, and assuming you are getting a reasonable number of impressions and clicks, you can normally burn through poor performing ads in a matter of days rather than weeks or months as some are doing.

Statistical significance occurs at much smaller numbers than most people think. If you want a good tool to help you make a quick determination, go to splittester.com.

by: Matt Vanrock
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