Avoiding Common PPC Ad Testing Mistakes

The effective ability to specifically target unique potential customers based on interest and location alongside being able to control your ads allocation and accurately measure results have made Pay-Per-Click or PPC as the most viable and cost-friendly advertising technique that businesses have ever known. And most online marketers consider PPC as easy and straightforward.

Despite that, a lot of online marketers still seem to commit some mistakes when testing their PPC ads. Some of the common testing pitfalls are:

    • Not Knowing When an Ad Test is Conclusive. Most online marketers tend to draw conclusions from ad testing even without substantial and statistically significant amount of data. Testing of Ads should be made on split or multiple test parameters in order to draw a more conclusive analysis. A landing page layout may show fantastic test data on a few days of testing and show totally contrasting results in other days.

 

    • There are tools that would help you analyze data from your campaigns. Either you get familiar with the A/B Testing or use abster.com’s calculator to get the right numbers for your testing results. In principle though, you only want to be able to be 90% confident that your test ad results are conclusive so you gather statistics to lead you to that direction. By testing multiple ad copy over a defined duration, you should be able to draw some solid conclusions from the test results.

 

    • Not Knowing the Key Metric. This is one major testing problem – deciding which key metric to use. It could be a choice between a conversion rate and click-through rate (CTR). Google allows these two options where you can automatically adjust ad targeting settings. Some PPC experts consider Google’s auto-optimizing drawback as not having sufficient data to base its optimization judgment.

 

    • Going by ad Group. This is another testing mistake, when you conclude your ad test based on an ad group. There is an option to conclude your ad test by pooling a lot of data over multiple ad groups and campaigns (bringing the ad groups together). Instead of judging each test on an ad group, you can pool all data from all ad groups and make your judgment across all ad groups. By aggregating your testing, it makes it easier to keep your ads nicely ordered within your account, and it reduces the chances of irrelevant keywords affecting your overall ad copy plan. On the other hand, because the ad groups are carefully segmented, each ad messaging will perform differently in each ad group. If you pool all the data from all ad groups, you are reducing the gritty testing you were running on individual ad copy.

 

In summary, the best approach when testing PPC ads is to get enough data; allow time before making judgment on your testing results; and record and aggregate your results enough to give you sensible basis on your next course of action.

If you want to know more on how your PPC campaigns are performing or how PPC Management will help you increase your ROI, please click on this link.

Images from Google Images

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