Pay per click advertising, PPC search engine articles

If have an AdWords account, you know that increasing your click-through rate (CTR) will lower your overall cost per click. So, why on earth would anyone want to decrease CTR? If you have a problem with people clicking on your ads but then not following through with a purchase or other desired action, you do want to lower your CTR–at least as it pertains to non-qualified leads!

How do you ensure that the right people are clicking on your ads? Quality ad copy! You've only got a limited number of words to play with, so make them count by selecting them carefully to pre-qualify your PPC-generated leads.

Carefully crafted ad copy will weed out unwanted clicks but also has the unwanted side effect of lowering your CTR, which can in turn cause your cost per click to go up and your ad positioning to go down. AdSense uses a formula that is based on high CTR equating relevance, but this trusty algo fails to take conversions into account. I suspect that Google will continue to tweak the technology behind AdSense to overcome this limitation, but until then it will be up to savvy marketers to strike a balance between maximizing the performance of CTR and conversions while also attaining a profitable ROI.

There's plenty of information out there about what A/B split testing is, but the ultimate success of your testing will be largely determined by what you test. So, how do you know where to start with your testing?

First, identify which pages of your website you will test. Choose pages that have a specific focus or single goal for users–these will be much easier to test than your home page or other pages that have multiple paths of action. Next, decide on which page elements to test. Examples of page elements are: headings, introductory copy, graphics and photos, main copy and testimonials. Start with elements that appear "above the fold" or near the top of the page, and place extra focus on promotional and limited time messages.

By knowing what to test, you'll be able to design more effective A/B split tests, ultimately improving your click-throughs and sales.