Search has changed a lot in the past decade. There was a time when search engine optimization (SEO) was all about keyword stuffing. When people used to search for something on the internet, content with the right keywords used to come up on top. However, the search landscape has changed. Users have changed the way they perform their search query. Online search now has evolved from keyword search to being conversational. Consequently, search engine algorithms too have evolved. Algorithms now do not rank content based on just keywords anymore, but on how relevant and contextual it is to the reader. It is no more the era of keyword optimization but about human readability and semantic optimization.
The way people search has changed
Just a few years ago, a search query by a user would typically be usually fragmented terms. However, with the rise of mobile and voice searches, search queries have become more conversational. People today use complete sentences as well as complex questions to perform an online search. Google’s roll out of Hummingbird in 2013 specifically focused on understanding these kinds of queries using natural language processing. The new algorithm started understanding phrases instead of simply relying on keywords alone.
Search engines are evolving
Just the way users have changed the way they perform search, search engines too are evolving in the way they process and evaluate content. For example, when Google released Panda in 2011, a majority of websites took a hit as they were pushed down the rankings due to lower quality content. The Penguin update in 2012 targeted and caught websites deemed to be spamming search results, especially those which bought links from link networks primarily to boost search rankings.
Moreover, there has been a lot of debate around the credibility of keyword rankings as a metric, as keyword rankings depend on the context of search. As a result of this, the earlier metrics of SEO success are not reliable anymore.
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The rise of Machine Learning
As the search queries moved away from simple words towards conversations, search engines needed a way to understand the intent behind these queries. Google launched its machine learning system RankBrain in 2015 with the primary focus of helping Google understand queries and process search results. RankBrain has been specifically useful to Google in understanding conversational queries. It is considered another step in the evolution of the realization of semantic search, which is understanding the meaning behind words and the relationship between these words in a given topic.
This means that Google is now using semantic search to understand what an article is all about even without the article containing the specific keyword. And the results are already visible. There are several websites that now rank on top of a search query even without having the keyword in their title tag or other usual optimization targets.
It is all about human readability now
What does all this mean for SEO? This means that traditional SEO based solely on keyword search is dead. The way to optimize for search engines needs to evolve and should now be based on human readability, relevance and semantic search. While the link building process continues and does help in improving rankings, only high-quality links that are relevant to your content, have good user engagement and add value help you rank higher. This requires real human interaction. Hence, it is always a good idea to consider a human-first approach to earn links and think how these links will help you gain more visitors to your site.
Besides SEO, there is also a new content strategy that is required to help your website rank higher during search engine queries, especially when the focus is to drive organic search. A great way to optimize content for semantic search is the use of topic clusters, which creates visibility across the topic than just focusing on a specific keyword.
Topic clusters are based on a premise of enabling a wider and deeper coverage across a range of core topic areas, while organizing a website’s content pages using a cleaner content architecture. A topic cluster basically involves a pillar page which is built around the main focus area. Linked to the pillar content is a vast amount of content covering a range of subtopics, also known as cluster content. Both the pillar content and cluster content are linked to each other.
A major advantage of this model, apart from providing a better user experience, is that one high performing cluster content can improve the search rankings for all the other cluster pages linked to the same pillar.
Search engine algorithms have evolved and the prime deciding factor of content rankings is user readability. Hence, SEO needs to evolve and focus on optimizing content not for search engines or keywords, but semantic search and user readability. Optimizing content for readability and semantics, not only provides better user experience but also provides better visibility and helps your overall SEO as well.