Jon Miller (Search Engine Land): "Your landing page is a key part of any successful paid search campaign, and by now, the value of testing and optimizing your landing pages has become accepted wisdom. However, many testing methodologies—especially multivariate testing—are complex and are only appropriate for sites that get hundreds of conversions a day. Small- and mid-sized companies simply do not have the volume required to achieve statistical significance in a timely fashion except using simpler A/B testing approaches."
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2 Comments
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Great article, Jon.Testing is very important in landing page marketing, but it’s only one piece of the puzzle. Good strategy, the ability to quickly create and deploy new pages, matching different landing experiences with your different ad campaigns, focusing on respondent segmentation -- these are just as important too.A/B testing is fast and easy to do, simple to analyze the results, and thereby very effective for quick learning in a campaign.Far better to do several A/B tests across different campaigns -- learning within the context of each -- than to get mired in complex MVT configurations for just a single page that may take you weeks or months to reach a clear conclusion.
Couple of things to addWhen A/B testing make sure your two variations have distinct differences. This increases the chances that you will see very different conversion rates and decreases test time by increasing confidence levels that one version is providing X% lift or decrease over the other version. The one big disadvantage of A/B testing however is that you will not know with certainly what value is providing the biggest lift or decrease in conversion rates. As an example if you are testing two different pages with different headlines, images, layout, etc what specifically is causing one page to perform better than the other? You dont know. Often times in the early stages of testing one value is the difference. Enter MVT - you can pin point which values are making the difference. As mentioned the big hurdle is traffic and tiem constraints. I would like to also stress the importance of never stopping your tests. Outside variables such as changing traffic sources, seasonal trends, publicty etc will all effect conversion rates. This changing landscape means your users will be responding differently. Also the author mentions Test & Target, GWO but leaves out Optimost? weak...Full factorial is flawed, taguchi is also flawed. But thats another subject for another day. Sphunn because of the great Tiger Woods analogy. :)