Testing 123: Ad Copy Testing Techniques

Ah, early summer, that time when the sun re-emerges and fills us with the energy to do things like…test ad copy! As PPC’ers, we love testing. Paid search is very reactive and fluid, allowing us to keep testing and learning all the time, so we had better take advantage of it! We can not only learn more about our paid search audience from ad testing, but we can gather important insights about our audience in general by using paid search as a testing tool. By continually testing variations of ad components, you can gain insight into your audience and research some of your own best practices. Like, does your audience prefer a formal or informal tone? Knowing this can help you to build better site content in addition to better ads. Do ads perform better with a headline that includes the registered symbol next to my brand name (theoretically improving brand trust), or should I stick with a dynamic headline (improving quality score and relevance)? Does my display URL make a difference? Maybe it does, maybe it doesn’t – but you’ll never know unless you test. In order to gain magical insights from your ads, the tests must be done properly. Something that is often overlooked in ad testing is a mantra that I hold close to my heart: “One thing at a time!” Without isolating your variables, there is no clear way to determine what caused the results of your test. Pick one variable (headline, call to action, display URL, etc.) to test at a time. Over a few months, you will begin to compile a veritable haystack of insights and data. Some basic tips for designing an ad copy test:

  • Pick your variable – dynamic vs. static headline, call-to-action, display URL, etc.
  • Lay out your ad copy carefully – create 2 ads to compare against each other that ONLY differ in the variable you picked (in this example, the headline is the variable):

  • Let the ads gather enough clicks to make a good decision. A good rule of thumb is to gather at least 200 clicks per ad before making any decisions.
  • Analyze the data – determine which variation had the better click-through-rate (or conversion rate, depending on what your goals are!)
  • Don’t stop here – now build your next test!

 

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