Are there any best practices for implementing & analyzing A/B tests with Google Website Optimizer to maximize SEO?

Running A/B tests with Google's Optimize tool can provide great insights for improving your site's user experience and conversions. However, you'll want to follow some key best practices to maximize the SEO benefits while minimizing potential risks:

Use Canonical Tags

When running tests, use rel="canonical" tags pointing the different variations back to the original page's URL. This helps avoid running into duplicate content issues with search engines.

NoIndex Test Variations

Add a "noindex" robots meta tag to all of the test variation pages themselves. This prevents those alternate versions from potentially getting indexed while still allowing Googlebot to render and evaluate them.

Monitor Crawl Stats

Keep a close eye on your crawl stats in Google Search Console throughout testing periods. Sudden spikes in pages crawled or bandwidth consumed could indicate crawl budget issues developing.

Limit Test Duration

Don't just let tests run indefinitely. Put reasonable time limits on them to minimize how long those duplicate-ish variations are out there.

Test Gradually

Rather than massively different full-page variations, try testing smaller elements individually. This lets you isolate which specific changes are truly impactful.

Analyze Engagement Metrics

Look at metrics like bounce rate, pages/session, and conversion rate alongside the variations. This data provides a fuller picture of which versions offer the best overall user experience.

Implement Winners Permanently

Once you've identified a winning variation, actually implement that permanently on your site rather than just leaving the test running unnecessarily.

Update XML Sitemaps

After launching a winner, update your XML sitemaps to include the new updated page content to aid rediscovery and indexing.

Monitor Rankings/Traffic

Closely monitor your rankings and organic traffic after implementing winners to ensure there's no negative SEO impact from the changes made.

Use Data Layers

Leverage standardized data layers to capture more robust A/B test data and pipe it into your analytics for deeper analysis.

The key is using proper technical safeguards like canonical/noindex tags to control the duplicate content aspect, limiting test scope/duration, and doing your due diligence analyzing quality signals before launching anything drastically different.