Search Engine Optimization Is Different After Panda Algorithm
Building the Right Environment to Support AI, Machine Learning and Deep Learning
After being an important aspect of web development and online business for well over a decade, search engine optimization (SEO) as we know it has been changed. Google's Panda algorithm updates over the last year have hit websites and SEO practices hard, but it has improved search results and altered the way developers approach SEO.
Most of the traditional SEO practices of the past--such as using META keyword and description tags, title tags, inbound links from other, like-minded sites, H2 tags which use keywords, content which also uses those keywords--are still valid factors involved with the process of obtaining higher rankings. Panda, however, counts other factors as equally, if not more important, than those old standbys.
The time a user spends on a given site, the site's bounce rate, social signals such as shares, likes and +1's, pageviews per visit--all of these things are used by the Panda algorithm to rank websites. It's a way for Google to allow users, those who use Google to search for relevant content on the web, to evaluate the sites they visit, and have their evaluations taken into consideration the next time they, and other users, search for similar content.
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