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Friday, August 24, 2018

Why Your SEO Strategy Must Recognize The Impact Of Machine Learning On Google


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With Google pouring in billions of dollars in machine learning and artificial intelligence, it is pretty evident that the SEO landscape is set to undergo a radical transformation very soon. Some areas that will undergo major upheavals:

Content
Even though content has already assumed great importance in SEO, AI is expected to become its driving force soon. It is expected that other on-page activities like keywords, technical issues, backlinks, etc. will take a backseat. Things like keywords, content structure, design, graphics, linking, etc. that partially affect SEO now will assume greater importance with AI being able to assess the quality of a webpage instantaneously. SEO will need to verify that the content is relevant and of high quality and that it satisfies the intent of the user while providing an experience that is positive. Ultimately, the content should drive users towards conversion. With data being machine processed, failure will invariably tank the page rankings immediately.



On-page Optimization and Backlinks
Title tags, URLs, Meta descriptions, alt texts, etc. while continuing to be important will no longer drive SEO as it does today. 

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AI algorithms will easily be able to identify strategies that fail to add value to user experience, design, and content; forcing SEO practitioners to monitor and enhance their efforts. AI will put an end to black hat SEO techniques and also diminish the importance of organic links that drive contemporary SEO. With Google’s AI expertise being able to understand the page contents, assess its value, and also analyze the relevance and value of links, search rankings will no longer be manipulated, according to experts .

Technical SEO
Technical knowledge and skills will become far less important in SEO with Google being able to diagnose and auto-correct technical errors on your website. Today Google is encouraging the adoption of technologies like Alexa, Google Home, and Amazon Echo simply because it wants to access sites for analyzing and ranking them; not having the initial data, the AI prowess is left useless.



User Experience
Unlike many technical aspects of SEO, UX quality will continue to grow in importance and be a key ranking factor. Today, if you want to know whether users have been enamored by a specific webpage, the best indicators are user engagement and the click-through rate. However, with time Google is expected to refine its AI capabilities to such an extent that it would be able to understand the level of user satisfaction just like a human and be able to rank the site accordingly. All those involved with the website, not only the SEO team but also digital marketers, designers, developers, etc. will need to get their act together to ensure that there are no flat spots in the UX.

Conclusion
The AI implementation will make Google even smarter and lend it the power to assess the true value and utility of websites very much like a human being but without the mistakes and biases. The technology will permit instantaneous assessment of whether the user’s intent has been met and a page rank allocated.

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3 comments:

  1. SEO work goes beyond simple content and focusing on keywords. Most people know that keyword targeting and the inclusion of keyword-focused content on your website is part of SEO, but the truth is that modern search engine optimization goes far beyond that, find here best SEO marketing companies

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  2. I found this article on the importance of recognizing intent in SEO strategy very insightful. It's interesting to see how understanding the user's intent can greatly improve search engine rankings and increase website traffic. However, in order to effectively recognize intent, a large amount of labeled data is required. That's where this article https://voiceofaction.org/cost-effective-ways-to-label-machine-learning-datasets/ on cost-effective ways to label machine learning datasets comes in. By utilizing these methods, companies can gather the necessary data to train machine learning models that can accurately recognize and optimize for user intent.

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