How Machine Learning Impacts The Need For Quality Content

quality-content

Google continually invests in the advancement of machine learning technology to improve their system, particularly when understanding and parsing user queries. Because of this, the need for quality content and the demand for user satisfaction are dramatically on the upsurge.

Google’s first publicly announced algorithm that’s designed to improve its understanding of language was Hummingbird followed by RankBrain. These algorithms and more have been established to better understand user intent and to assess content quality.

The Significance of Machine Learning Today

Google can’t afford to solely rely on human resources to do the bulk of what it does. Machine learning is maximized to mimic the human brain using algorithms and historical data. Humans learn by receiving information while tapping our past experiences and stocked knowledge.

Machine learning uses a relatively the same approach. After years of progression and study, Google has made use of machine learning to create accurate processes that automate their system in a systematic and clever way.

Impact of machine learning on content quality

The reason Google is the top search engine is because of the quality of the content it feeds on the search results pages. Their machine learning algorithms, such as RankBrain, have improved a lot that their ability to understand human language has gone so advanced. For example, if you key in a query about “getting 100% score on Super Mario without walkthrough”, the old version of the algorithm might not be able to show the most accurate results. Before RankBrain was born, Google can’t pick up the word “without”, leading to inaccurate search results. RankBrain has been designed to focus on long-tail search queries. This has been a great progression that has led to a better understanding of user intent.

Although around 80% of searchers use Google for their navigational, informational, ad transactional queries because of its high level of accuracy, it doesn’t mean Google is perfect. There are still certain slips that Google’s algorithm misses. The human language might sound natural and easy for us, but the scale of machine learning that is required to fix these slips can be massive. Google is constantly watching out for more slips on their end, so they can enhance their machine learning-derived algorithms and ensure seamless searches.

Google’s Pygmalion team, the one in charge for understanding natural language, is working day in and day out to ensure that users’ intent as implied by their query can show the most relevant search results. They will also strive to design their machine learning algorithms in such a way that they can detect the most comprehensives pages that can address the users’ needs.

With all these efforts, we can expect that the quality of information we get on dedicated platforms like Google can boost our user experience further in the years to come.

Impact of machine learning on user engagement

Search engines make use of different methods of assessing user engagement. A website’s CTR or click through rate is said to be a huge quality control factor and is also believed to be a direct ranking factor. We can expect that more ways of picking up user engagement signals will be used to set the general search ranking algorithm.

The kind of machine learning that is associated with user engagement is called “reinforcement learning”. User satisfaction and engagement is directly correlated to content quality. If a user does a long click and lingers on a site in more than 3 minutes, that could already mean that the user engagement is present. That could also imply the following:

  • The information/product/ service they are looking for is present on the web page.
  • They can find what they are looking for easily on the web page.
  • The website/web page looks and feels like a credible source.
  • The general web design is user-friendly.

Google’s machine learning abilities are expected to become better in assessing the page quality of web pages with respect to user engagement. Any digital marketing strategy must cover the criteria mentioned above in order to gain an edge over the competition. On top of the actual content, the navigational experience of the user must also be taken into account.

Final Thoughts

In a nutshell, as Google and other search engines get better and better at identifying genuine quality across all pages on the web, webmasters must also do their best to go with flow of increasing demand in terms of content quality and user engagement. These should be the core of any marketing campaign. Without these two, all other SEO efforts will go in vain.

CATEGORIES: SEO