A/B Experiments
To see if certain changes can help you optimize your ads better, the
best approach would to be to run an A/B experiment. An A/B experiment
for an ad lets you compare the original settings for that ad against
variations of those settings which you can choose from. You can then
evaluate their performance. These experiments don't need you to change
your ad or webpage code.
You can do a lot with these ads. For example, you can compare your
text-only ads to text-and-display (graphics) enabled ads, and see which
performs best. Again, this detail is subjective, and could vary from
site to site. For example, text-only ads might help an article base
website more, whereas gaming websites might benefit more from visual
ads.
You can also check out visual settings for your ads. For example, test
what color schemes attract more clicks, or what sort of borders work
best. Or, analyze the effect of changing the color of ad text on ad
performance.
Using A/B Experiments
24 hours after setting up an experiment in your account, you’ll see a
confidence score for the two ad units settings. This score will tell you
how likely either of the two settings (original vs variant) are to
perform better in the long run.
As the experiment progresses, these confidence scores may change. So
it's probably a good idea to wait a while for the score to mature, and
let one of the scores reach 95% before making a decision as to the
setting you're going to select. Upon selection, the experiment ends, and
the new setting is applied automatically.
Please note that while an experiment is running, our system will
automatically optimize the traffic split between the two ad unit
settings. The better one setting performs, the more traffic it will
receive, helping you maximize your revenue potential even during the
experiment.
Give A/B experiments a try using this new feature to ensure you’re
getting the most out of your ad units. And then share your experiences
with us in the comments section below. Cheers :)
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