Holistic content: A new approach to SEO in 2017
According to a recent Searchmetrics white paper, the center of gravity of SEO has now shifted away from keyword-frequency and toward “content relevance” (as well as “user intent”). In terms of content relevance, Searchmetrics identified two types of terms that Google is now looking for: proof terms and relevant terms.
These terms are essential to the topic at hand, proving to Google that you are addressing the topic directly. Roughly speaking, synonyms fall into this category. Therefore, proof terms are not much different than the keywords content creators have been using to optimize, and occasionally “stuff,” their pages with for years.
These terms, by contrast, are non-essential to the topic at hand. Nonetheless, they are related and relevant to it. Relevant terms belong to the closely-knit family of keywords and phrases that naturally cluster around the topic. They are evidence of a holistic, well-rounded, comprehensive piece of content with enough depth to cover most, if not all, of a topic’s relevant aspects and relations.
Here are a few tips to help you find both proof terms and relevant terms:
- Try dictionary and thesaurus sites and tools that generate not only synonyms, but near-synonyms and related terms.
- Scroll down to Google’s “Searches related to” section at the bottom of the search results page for your topic.
- Look over the list of topics and terms in Wikipedia’s See also section of the article for your topic.
- Examine high-ranking articles and blog posts from influencers covering your topic, and see what family of terms and phrases they’ve chosen.
Avoiding “keyword stuffing” in 2017
Search engines, such as Google, now automatically check sites for evidence of keyword stuffing and penalize sites that appear to practice it. In other words, this practice has exactly the opposite of the effect that content creators are trying to accomplish when they aim for keyword-density in their SEO efforts. Altogether, it may no longer be the case that there is an “optimal keyword density” or magic number that your page should aim for. And this arises from the shift away from narrow content in favor of deeper, richer, broader content.
Staying away from the danger zone
Matt Cutts, former head of the web spam team at Google, last directly addressed the issue of keyword-stuffing in a short video way back in 2011. However, what he had to say then likely still holds equally today. In short, Cutts emphasized that the first time your page mentions a keyword is the most important because it gets Google’s attention and associates your page with that keyword. The second time may also give you a genuine boost. However, as Google finds more and more instances of the same keyword, you quickly run into “diminishing returns.” And if you’re using the same keyword or phrase “over and over again, then you’re in danger of getting into keyword stuffing.”
Avoiding short, narrowly-focused content
This is content, roughly speaking, that may have a high-frequency of the same keyword or phrase, but lacks contextually relevant terms. Content of this kind is a narrow, shallow, quick-pass that only covers the topic’s most obvious elements. Naturally, more comprehensive posts and articles will tend to be broader and longer treatments of your topic.
Walking the fine line
Altogether, there is no final rule to follow that will guarantee you great Google rankings and zero penalties. However, based on Searchmetics’ findings, you will greatly increase your odds of success if you focus on producing holistic, deep treatments of your topics that are rich in relevant terms. At the same time, you can avoid the dangers of “keyword stuffing” by resisting the temptation to force loads of identical keywords and phrases into your content. Guarding both flanks in this way, you can now focus on the task of providing the rich content that users want to read and search engines want to find.
Be sure to contact us for more on what to aim for, and what to avoid, as you fine-tune your content in 2017.
Written by Terry Rajaram
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