SEO Copywriting

If you are the kind that likes to keep your ecommerce website up to the latest SEO techniques, you have certainly come across fancy terms such as:

• Latent Dirichlet Allocation (LDA)
  
• Latent Semantic Indexing (LSI)
  
• Term Vector Analysis (TVA)

These concepts related to SEO copywriting are truly complex from the search engine's point of view. But as an ecommerce website owner you can implement them by keeping one basic best practice in mind: make sure that your textual content includes terms related to the main idea of the page.

• Keep Your Language Natural
  Since the content of a page is an important on-page SEO factor, search engines have made great strides in figuring out the real meaning of textual information. Research into the structure and composition of language has assisted search engines in evaluating the natural patterns of language.
  
  Gone are the days of exacting keyword density requirements. Today, search engines try to "read" text in much the same way as a human being would. If you look at the complex text-processing algorithms of search engines, it would seem like something right out of science fiction.
  
  So the recommendation is to write without keeping search engines in mind. That should take a load off your shoulder.
  
  
• Make the Language Context-Rich With Related Terms
  Though keyword density based SEO is a thing of the past, an analogous strategy has become quite important. While the keyword density approach recommended stuffing keywords into the text, cutting edge ecommerce SEO involves ensuring that your text contains terms related to the overall theme of the page.
  
  A corollary of the related-terms approach is that text written by an expert will include terms related to the topic. For instance, if the article was about Michael Jackson, it would probably also include some of the following terms:
  • Wacko Jacko
    
  • King of Rock
    
  • Neverland
  Without research, a copywriter who does not know much about Michael Jackson would not know the association of these terms with the singer. That is one of the principles on which the related terms approach is based.

Is the Related Terms Approach an Advanced Form of Keyword Stuffing?
It could seem that the related-terms approach is not much different from the keyword density approach. After all, both rely on stuffing terms into the text of the page with the intention of influencing the search engine rankings of the page.

While there are obvious similarities, the related terms approach is a far more evolved animal. Remember the strange sounding terms, such as "Term Vector Analysis," that I mentioned at the beginning of this article. Well, researchers have determined that all terms have a relationship with all other terms. These relationships are not merely restricted to one term being a synonym of another. Instead the analysis of terms attempts to discern the context of the content based on the usage of terms and their inter-relationship.

If you have a book listed on your ecommerce website, and the description page uses the terms:

• Utility
  
• Demand
  
• Supply curve

the search engine would know that the book is about some aspects of microeconomics. When a user searches for a term related to microeconomics, which you may not even have considered, the search engine could determine that your webpage is a relevant match for the search term.

So Which One Is it: Natural Language Text, or Text Stuffed With Related Terms?
In the ideal case, there would not be any difference; natural language should automatically incorporate related terms. But we do not live in an ideal world. At this point of time, it does seem like the deliberate usage of related terms might influence search rankings. That could spawn a new generation of search engine spam.

But search engines are getting smarter every day, and hopefully they will be ready for the new spam.