OntoSearch

The search engine optimization (SEO) business continues to grow everyday. In just the past 3 years, SEO spending has increased in the neighborhood of 400%, and this trend is forecasted to boost even far more in the near future. This year alone, over trillion will be allocated to on-line advertising efforts.

Yet whilst search engine optimizers (SEO’s) have continued to use many of the same strategies to increase the visibility and positioning of their clients’ web sites in search outcomes, the search engines themselves have continued their evolution. Now SEO’s should do the same in order to maintain up with the continually evolving search engine algorithms of Google, Yahoo, MSN, and a number of others.

Within the past year, several companies have no doubt noticed big relevancy fluctuations in the search engine rankings. Although most SEO’s keep scratching their heads and wondering what happened, others study and test to identify the cause of these changes. Then they use these findings to alter their on the web optimization methods. But just how have these algorithms evolved? Far more importantly, what can we as SEO’s do to retain top positioning?

1 reason for this shuffling of results has been attributed to the inclusion of latent semantic indexing (LSI) technology into the search engine algorithms. Google, in fact, implemented LSI into its algorithm a few years ago and has continued to use it since.

But what is LSI and how does it affect page rank? LSI is a system that enables search engines to identify what a page is about beyond matching the specific search query text. In other words, LSI looks for word relationships within page content, just like a human being would do. It determines the keywords of a page and then looks for related words that are semantically close. Therefore, LSI grants related words within page content a higher significance and value, while lowering the value of pages that only contain specific keywords and lack related terms.

Yet whilst LSI technologies don’t understand the meaning of any of these words, the phrase relationships they identify between words are a main determinant of search engine positioning. For example, a page about McDonald’s will naturally contain terms such as “hamburgers” or “Happy Meals.” For this reason, pages that target a range of related keywords within the page content frequently have higher and more stable rankings for their primary keywords.

But how do we know what words or phrases Google would consider to be related? The very best way to discover these semantic relationships is to perform a search of Google with the tilde (~) character in front of your query. For example, type “~hamburgers” into the search box and Google will return pages with bolded related terms. A search for “~hamburgers” returned the related terms “fast food,” “ground beef,” “burger,” and even “quick food restaurant.” Thus, Google expects to see related words like these within the contextual content of a page targeting the term “hamburger.”

As you can see, when performing search engine optimization, it is advantageous to error on the side of too much data than not enough due to the fact that LSI expects to see related words and phrases.

This is particularly true since Google uses LSI to evaluate the relevancy of your website’s link profile. This means that Google identifies how relevant every of your external and internal links are to your keywords and internet site as a entire. This reality is another excellent reason to mix the anchor text of your links. If all your links are based around a particular phrase and never mention any related or similar phrases, your site’s ranking will suffer thanks to Google’s LSI algorithm.

As search engine algorithms continue to evolve and come ever closer to mimicing human behavior in order to return the most relevant results, we as SEO’s must do our very best to present page content in a way that is most useful to users. The power of latent semantic indexing to identify relationships between words, within content, and even between pages is changing the way search engines decide relevancy outcomes and position. As SEO’s, we must utilize the power of latent semantic indexing to diversify our pages or we’ll be forced to watch them slowly fade away.