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Matt Cutts Warns on Duplicate Meta Descriptions

duplicate meta descriptions
Credit: Moz

Mountain View, California–Duplicate meta descriptions should be avoided, says Matt Cutts in a recent Google Webmaster Help video. Cutts states that duplicating meta data is unnecessary and that it is preferable to Google to leave these fields blank rather than copy the information from one page to another.

Cutts goes on to state that even on his own blog, he leaves the fields blank, allowing the search engines to automatically render snippets. This advice follows the roll out of a new manual penalty for what Google calls “image mismatch”, or the practice of uploading one image to search engines while displaying another image on a website.

The advice as comes after Cutts explained in previous videos that no-follow tags will not hurt SEO and the algorithm Penguin 2.1 went live at the beginning of October.

Duplicate Meta Descriptions Just One Piece of the SEO Puzzle

In several Google Webmaster Help videos, Cutts addresses a number of issues and theories about search engine optimization. In mid October, the chief webspam engineer stated it’s better to create quality content rather than to try and reverse engineer the search engine’s algorithmic signals.

The search engine has also issued a warning about sites with thin content, stating that duplicating content across multiple pages and just changing a few words will invite manual actions against a site. Cutts likewise cleared up a misconception that more Google +1’s will result in higher organic ranking.

Best Practices for Success

Google has stepped-up its efforts to combat webspam and take action against sites that have little or no added value. The search engine posted a warning on participating in link schemes back in July. Cutts has also stated it is best to no-follow infographics and widgets because there is a possibility that spam links will be contained in the code.

The search engine debuted Hummingbird in late September, a new part of the algorithms which seeks to interpret context in user queries to deliver more accurate search results.

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