The Intersection of AI and Search: Why You Need Artificial Intelligence to Win in SEO

There’s always a bounty of opportunity and advancements in the search industry, but there’s also a paradox: the more room for growth, the harder it is to accomplish your goals.

After all, any one person can only accomplish so much in a day.

In an effort to create the best SEO strategy and user experience humanly possible, it’s vital to work with some non-humans…that is, AI-enabled technology.

The goal of user experience is to create a strategy that drives clickiness and stickiness—generating a high click-through-rate and keeping users on your site for lengthy periods of time.

With countless factors to optimize for, artificial intelligence and up-and-coming technology help you to stay ahead of organic search trends–and the competition.

In this blog, we’ll explore the relationship between artificial intelligence and SEO, and show you how it can play into your digital marketing strategy.

We’ll cover:

• Why AI is Important in Search

• How AI Influences SEO Principles

• How to Include AI in Content Strategy and Creation

• Implementing Machine Learning through SEO Automation

• Conclusion

 

Why AI is Important in Search

Why is AI important in search and digital marketing specifically? Well, for one: Google is using it, and Google waits for no one. 

In recent years, they’ve developed and released a number of algorithm updates that utilize AI, all of which completely changed the playing field for sites in organic search that better serves the end user. 

The following is a brief look at Google’s algorithm updates and how they’ve incorporated AI over time.

Hummingbird 

Google’s Hummingbird update, released in fall 2013, gave the search engine the ability to understand user intent. By reading queries based on context rather than a direct processing of each individual keyword, the search engine was able to provide better search results—and enhance the user experience. 

RankBrain

Two years after Hummingbird, Google launched RankBrain. It allowed Google to even better understand the user intent behind a query. It did this through machine learning. 

Because of RankBrain, Google can analyze new search queries and provide more relevant results to users. It was another push away from a query’s individual keywords, toward a more holistic understanding of topics and overall context of a page and site.   

BERT

BERT was a huge step forward in natural language processing (NLP). It gave the search engine the ability to understand the complete context of a word by understanding the words that come before and after it. 

When this smart thinking is applied to search queries, you can see how Google pushed themselves to fully understand a searcher’s overall intent, rather than just understand the individual keywords isolated in silos. 

Google’s AI Updates

An October 2020 announcement from Google proved that the advancements toward a smarter search are never-ending. Two examples of Google’s AI updates included an enhanced ability to understand misspelled words and the option to index individual passages from web pages. 

 

These AI updates have a huge impact on organic search and bring along new opportunities in SEO as well. 

 

How AI Influences SEO Principles

Understanding Google’s AI-driven algorithms can influence your own approach to SEO, especially when it comes to user intent and semantic search. 

When you understand user intent and the semantic meaning behind a searcher’s query, you can transfer this knowledge into your content.

By demonstrating these AI concepts within your content, you not only prove that the content is semantically relevant and authoritative, you also prove to search engines that you have the right content to address the searcher’s query. 

Identifying the underlying intent behind a query and delivering authoritative content works to generate stickiness—that is, keeping the users on your page. You don’t achieve this through deception, you achieve this by providing value.    

User Intent and Content

As the various algorithm updates prove, search is no longer about individual keywords. Google is continuously adapting to properly serve users with the correct content by understanding the context behind their query, applying user intent to the results they’re shown. 

In this new age of AI, you need to tailor your content to match these different intents in an effort to deliver content that satisfies the users’ needs. Essentially, you need to match your content to the right user intent to provide relevant information for the correct stage of the user’s buying journey. 

Uncovering user intent in SEO isn’t just an option—it’s a necessity. If you don’t address the right user intent, you can’t get the search visibility needed to compete on the SERPs. 

Because Google uses AI to understand search queries to offer the best user experience possible, you too have to use AI in your SEO strategy to uncover and address user intent at scale.

This is why we apply user intent throughout the seoClarity platform–from keyword research to content creation and optimization. When you have an understanding of what need a user has, you can create the right content type to address that need.

Semantic Search and Analysis

Since Google no longer reads and analyzes queries through a tunnel vision, it can understand the context of a query and understand if your content is delivered with authority. 

Take a look at the example query “what are the white earbuds everyone is wearing”. There’s no specific mention of a brand, a product name, or any other indicator that directly leads Google to understand what it is we’re searching for. 

And yet, Google is able to decipher the query and present us with the following SERP:

(Google is able to identify what the query means, despite it lacking specific keywords.)

So, Google is able to form connections between queries and relevant search results even if there is no main keyword given. 

Not only does the SERP demonstrate a semantic understanding of the query, it also presents results that can address a variety of intents, including transactional.

This all comes together as evidence as to why SEOs should no longer chase keyword to keyword, or page to page optimizations—the SERP is simply too intelligent to keep up with. 

How else does this apply on the SERPs?

Imagine you search for the query “how warm is it in chicago”. You’ll see something like this:

 

 

This result may seem insignificant; afterall, it’s what searchers are used to seeing nowadays. 

But looking past the familiarity of the SERP, we can see the search engine’s intelligence in action: semantic search allows the search engine to provide the precise information we’re looking for (directly on the SERP) instead of analyzing the literal meaning of each keyword searched for in the query. 

To summarize: This SERP answers the intent of the query, identified semantic relationships as  Google was able to discern that the word “warm” in relation to the other words mentioned in the query relate to the larger topic of “weather”.

Google has successfully processed the semantic meaning of the query, and offered informational content to deliver on the informational intent. 

How Does This Apply to Your SEO Execution?

Herein lies the challenge: Google is powered by machine learning, and can constantly learn and adapt to search behavior. Your efforts to optimize your own content creation process, on the other hand, are dependent on a human agent—a human agent that is naturally limited in their ability to thoroughly research a topic in its entirety. 

To overcome inherent human limitations, you need to introduce AI into your content strategy and execution. 

 

How to Include AI in Content Strategy and Creation

You’ve probably noted by now that Google’s main objective is to deliver the best results to their users, and their approach to doing so is more sophisticated than ever. 

If Google presents the most quality, authoritative content on the SERPs to answer queries, you know that you have to create high-quality content to compete.

This becomes challenging with the mass amount of content being created every day—quantities so high that it’s increasingly difficult for a content marketer to break through the content chaos.

Plus, the adoption of voice search has created a new playing field (and a new competitive landscape) for landing content in front of users. In 2017, 35.6 million Americans would use a voice-activated device at least once a month, according to eMarketer.

Voice search answers come from the Answer Box/Featured Snippet results for a search given. If you can secure this SERP feature, you give your content a new avenue to reach users. 

You can benefit from other SERP features as well, such as the Knowledge Graph, People Also Ask, and Images. Any SERP feature that you can secure gives your content more ways to be seen. 

People Also Ask Box for “Why is the sky blue?”

 

Yet another way to have your content seen is to target these SERP features that include larger pixel space which increases your visibility. 

Structured data from schema.org helps search engines digest parts of your web pages and the respective content to better understand them — and these structured data types are leveraged in the rich results on the SERP

Take a look at the following example of a search listing. It resembles the standard organic search result, with the addition of a few internal site links.

Over time, various schema were added to the page to give it a rich result, which subsequently increased its pixel space, as you can see here:

 

 

This enhanced appearance on the SERPs works to attract users’ attention and improve your CTR. In short, implementing Schema can give your site more clickability. 

This leads us to a question: If you need to create quality content to compete on the SERPs, but can’t effectively or efficiently accomplish this process in a manual way, how do you create well-targeted content? 

We realized that the answer was found at the intersection of AI and content marketing: a deep-learning system that intelligently scrapes the web for relevant information that allows content writers and SEOs to create authoritative content at scale.

This, precisely, is Content Fusion, an AI-enabled content writer tool from seoClarity that allows SEOs, content strategists, and writers to create the most authoritative content faster than ever before. 

 

Implementing Machine Learning Through SEO Automation

Google is constantly working to become smarter than it was yesterday, and the only way to compete is to implement AI into your own SEO efforts.

With the power of AI, the analysis of big SEO data becomes more manageable, and more importantly, leads to a shift from data collection and strategy formation to strategy execution.

If you were to go about this in an entirely manual way, there would simply be no way to manage and scale the work. With so many moving parts, and no way to definitely know what the search engine will reveal for queries, Google will always be one step ahead of you. 

By the time you analyze the data manually, things have already changed. Not to mention inherent human error.  

This is exactly why the seoClarity team built Actionable Insights, an AI-driven SEO analyst that provides 24/7 insights based on real-time analysis of your site data. 

Taking the burden of data analysis off your shoulders and placing it onto the back of a rigorous AI-powered machine allows you to execute a strategy that you know is backed by data. 

This, in turn, enhances your SEO efforts tenfold to drive clickiness and maintain the stickiness of your content. 

 

Conclusion

With so many changes to Google, it’s nearly impossible for human agents to keep up on their own. AI, however, helps us overcome the challenge of analysis in every realm of SEO.

 

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About the Author 

Mitul Gandhi is the Co-Founder and Chief Architect of seoClarity, an AI-driven SEO and content optimization platform. As a longtime data-driven serial entrepreneur, information architect and SEO veteran, Mitul expertly combines vast technical expertise with intense marketing insight. His variety of experience in in-house SEO, search marketing, and software development allows him to efficiently assess how to use software tools to meet challenges and drive ROI. Mitul holds an MBA in direct marketing from Rochester Institute of Technology. Additionally, he has spoken at conferences in the United States and the U.K., including SES, SMX and Pubcon. He has also been quoted in MSN Money, USA Today, Time Online, Search Engine Watch, Search Engine Land and Web Pro News.

 

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