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Candy875

: Is it possible to A/B test SEO using Google Experiments? I've read that A/B testing does not have a negative impact on SEO, but is it possible to A/B test to improve SEO? My thought is to

@Candy875

Posted in: #ABTesting #Google #Seo #SplitTesting

I've read that A/B testing does not have a negative impact on SEO, but is it possible to A/B test to improve SEO?

My thought is to track each visitor's referring domain and create an event when any visitor whose initial referrer was google.com signs up; and serve different templates to each segment. I can't find any information on it here; would this work?

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@Angie530

Everything Stephen says is correct - I covered some of the methodology towards the end of this presentation (slide 136 onwards) - including linking to some great resources on the mathematical side of figuring out which group is winning in a "noisy" environment where individual pages can appear to skew the results.

If you're interested in reading more, we recently announced a private beta of a new platform we are building that is designed to make this kind of testing easy to do on any site - by acting in a similar way to a content delivery network and applying changes to groups of pages on the fly.

Happy to answer any more questions you might have about it.

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@Megan663

A/B testing for SEO can't use Google Experiments or other methods that change pages on a per-user basis. You need to make sure that Googlebot and users each see a set of pages from group A and another set from group B. I generally pick half the pages on my site to change, and half to leave "as is".

This only works if you have a large number of similar pages on your site and are able to split them in half randomly. For example, I've done SEO experiment based on the database ID of the landing page. If the ID is divisible by 2 it goes into group A, otherwise it goes into group B.

This works particularly well with page title experiments and other on page factors. Group A gets one template for the title, Group B gets another.

Even then you may need to be careful to exclude your top pages when analyzing your results. For example if you have one page that goes viral when the experiment is running, a single page may be enough to tip the balance in favor of whichever group it is in.

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