Cyrus Shepard, former director of SEO at Moz, has recently released his 100+ Google SEO Success Factors, Ranked article, which title speaks for itself. Considered a masterpiece by SEOs and enthusiasts, the article’s strength lies in its objectivity in providing a comprehensive amount of information in a way that is well-organized and easy to follow.
This kind of buzz is understandable for a work that delivers useful content with simplicity, especially when it comes from big shots in the industry like Shepard. He divides what he calls SEO Success Factors into five categories, according to their level of impact for getting traffic and ranking well on Google. The most critical factors are called – guess what – Critical Factors. According to Shepard, “sites at the top of Google search results typically score well in most, if not all, of these critical SEO success factors”. They are as follows:
- Content that Targets User Search Queries
- Crawlable + Accessible to Search Engines
- Quality & Quantity of Links
- Satisfies User Intent
- Uniqueness of Content
- Expertise, Authoritativeness, and Trustworthiness (EAT)
- Click-through Rate (CTR)
- Built for Multiple Devices
I’ve been working as a search engine evaluator for Google for over three years and by quickly scanning through this list I was able to notice many concepts that, as a search evaluator, are very familiar to me: “EAT”, “freshness”, “satisfies user intent”, “unique content” that “targets user search queries”. Half of what he regards as critical factors for a successful SEO campaign refers to aspects that are well-known by Google raters when determining a relevance rating for a search result. But there is more to that.
There are factors and issues that are not explicitly mentioned on Google’s guidelines, but that seasoned raters learn to spot while scrutinizing the result to assign a rating. One example in many that I put together on my search engine evaluator course is what I call Extraneousness issue.
The Extraneousness issue occurs when the object of the query is dividing attention with unrelated content in the result. I will illustrate with an example:
Let’s take the query California demographics. The user is looking for demographic information from the state of California in the United States. Now, how relevant do you think this Wikipedia article about California is for the query California demographics?
More or less, right? And why is that?
The issue, in this case, is that the relevant piece of content for this query, which is found in the middle of the article, is dividing attention with a lot of unrelated content on the page. To find the information that is helpful to what the user is looking for, some digging would be required, which would lead to a non-ideal user experience.
Although it’s correct to say that “the content should target user search queries” and “satisfy the user intent”, by including a specific aspect like the Extraneousness issue to the analysis, it becomes much more obvious why your current content might not be living to its potential for certain queries. Of course, it also becomes much easier to work on a solution that is quick, easy and straightforward to deploy.
For example: Imagine that, instead of a Wikipedia article, that page is from a blog owned by you. Let’s assume you realized that “California demographics” is a very popular keyword for which you’d like your content to receive more traffic and rank better on Google.
What could you do to improve the relevance of that same piece of content for that keyword?
Well, an alternative would be to place the content more prominently on the page. By doing so, you’d be able to reduce or even eliminate the content’s extraneousness issue for that keyword.
Another alternative would be to create an article that would specifically target those keywords and where that same piece of content would be king. With this approach, no extraneousness issue would occur for that keyword.
Although these alternatives may sound common knowledge to many, they become even more obvious when you approach the problem through the lens of an experienced search evaluator. In other words, it gets a lot easier to grasp what the problem of your content is when you assess the result with a list of specific relevance attributes in mind.
Another example of result issue is what I call Accuracy issue. If you were the owner of a website that provides information on the demographics of California, you would want to provide content that is not just fresh but, primarily, accurate. It doesn’t matter how comprehensive your content is. If the information provided is incorrect, it’s worthless as, ultimately, it would not “satisfy the user intent”.
You see, in the end, it all comes down to “satisfy the user intent”, but by adding specific attributes like accuracy or extraneousness to the analysis, it becomes possible to evaluate the content on its most basic relevance components. It gives you a better perspective of everything that makes up the idea of satisfying the user intent in terms of content.
Now, do this exercise yourself: Come up with a list of promising keywords for which you think your content is not living up to its potential. Now, try to identify if there is some sort of accuracy, freshness or extraneousness issue with your content for those keywords. If there is, then go ahead and fix them.
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