Great content is essential to SEO and to PPC. Too many websites are filled with keyword stuffed pages that read like they were written in 1999 and feature a Call-To-Action that matches the needs of the site owner but not the user’s query or desires; I don’t want to buy, I want learn more so offer what I want. My query is all about ME!
The art of content development is to understand that search engines are learning from click behavior to understand what users are looking for and relying on statistical co-occurrence in place of semantics to derive meaning from pages. This is how they deliver relevance.
The best way to understand Google’s statistical approach is to look at how Google Translate managed to create an effective tool to translate between hundreds of different languages without having any subject matter experts or native speakers on the team for Mandarin or many of the other languages. Here is Google’s official explanation:
Because we want to provide everyone with access to all the world’s information, including information written in every language, one of the exciting projects at Google Research is machine translation. Most state-of-the-art commercial machine translation systems in use today have been developed using a rules-based approach and require a lot of work by linguists to define vocabularies and grammars.
Several research systems, including ours, take a different approach: we feed the computer with billions of words of text, both monolingual text in the target language, and aligned text consisting of examples of human translations between the languages. We then apply statistical learning techniques to build a translation model. We have achieved very good results in research evaluations.
This model of translation didn’t arrive by accident. The approach of statistically determining relevance is built into Google’s DNA and is an enormously important aspect of how search engines judge content. Some tools make this much easier to understand and visualize. For example, the Google Wonder Wheel gives you the ability to understand related searches as well as the subsequent user behavior, be it click behavior or query refinement.
Co-Occurrence engines link Quintura provide visual insight into what keywords are commonly associated with the target query term.