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Testing Ad Copy Is Effective If You Give It Enough Time

http://www.morevisibility.com/semblog/testing-ad-copy-is-effective-if-you-give-it-enough-time.html February 16th, 2009 by

Testing your ad copy is a very important component of any online advertising campaign.  What you feel is a good message about your products and brand isn’t always as well received by your potential customers.  In order to make sure your ad copy message is enticing to your customers, it is important to develop different messages for your audience and then test them over time to find out which are best.

I’d like to give some examples regarding the ad copy messaging you may want to evaluate. One ad might offer a free brochure, another offers free samples, while yet another offers free shipping. An effective marketing campaign should incorporate some kind of testing process to determine what message is most appealing to your searchers.  This leads to higher click through rates, and higher conversion rates, which of course is the goal for any website. 

One dilemma I am consistently up against is making sure that while conducting these tests, we are giving enough time to allow users to view the ads, and click on them (or not click on them).  Depending on the number of visitors a website gets on a daily basis, the ad copy testing time period varies.  The more visitors a website gets, the shorter the testing cycle.  A website that gets 10,000 clicks daily should have a good idea of how searchers are reacting to the ads in one week.  On the other hand, a website that receives 3,000 clicks daily should consider a longer testing period of perhaps 3 weeks, in order to get enough visits and make a determination of how searchers are reacting to the advertisement’s offer. 

I encourage all advertisers to test, and test often.  But be sure that you don’t get too excited and end the ad copy test before you know conclusively which messages are performing better than others. Remember, testing ad copy takes patience and persistence.

Posted in Search Engine Optimization

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