What’s the relationship between data science and SEO? How can data science analytics help improve your SEO initiatives and boost your rankings? Keep reading for an in-depth look at how data science impacts SEO and how you can use it to your advantage.
What Is Data Science?
Data science is a multidisciplinary field of study that incorporates the use of different data-driven scientific methods, algorithms, and processes to analyze information and identify distinctive patterns from structured and structured datasets. Important and telling insights can be gleaned from these dataset analyses to facilitate improved artificially intelligent machine learning processes that also lead to better data mining.
Machine learning is the process of using identifiable dataset patterns to help machines take on more humanistic personality traits which can help streamline customer service and backend processes for businesses. It can also help you save some overhead money. Rather than having to hire live bodies to perform simple tasks like live chat customer service, you can install artificially intelligent software that’s equipped to handle, resolve, and answer basic customer service inquiries. More complex inquiries that require a human touch can be reserved for and transferred to live agents.
Analytics Tools and SEO
Google has in-depth analytics capabilities that are designed to identify and understand the needs and sentimentalities of users based on their past or current activity. This includes past searches, purchases, and online inquiries. Through comprehensive analytics, you can gain a better, more in-depth and valuable understanding of what your existing and prospective customers are looking for. Use intuitive intent-based search algorithms to answer and address customer inquiries and actively expand your target audience base.
Over the years, data science trends have seen tremendous growth on search engines like Google. Google launched one of its most revolutionary inventions, Google Brain, back in 2011. According to the tech mogul company, the main objective of Google Brain is to use artificial intelligence to make Google products “faster, smarter, and more useful.”
Google Analytics allows SEO experts to quickly and easily access and analyze search data, identify common patterns, and then use that information to create skillfully targeted ads that are designed to entice specific users. Online marketers can use this valuable data to capitalize on the interests of their target audience members and even expand their outreach to new demographics on a national and international level.
What Is the Correlation between Google and Artificial Intelligence?
In 2015, Google launched another important brainchild that revolutionized the way SEO was done. They called it Rank Brain. The goal of this platform is to help improve the quality of search results that users are presented with to make them more relevant, intuitive, intent-driven, and search related.
Rank Brain helps the search engine better comprehend the intent behind each search in the same way that humans would process certain human implications. For instance, if you’ve ever misspelled a word during a search and had Google correct it with the “Did you mean” feature, then this is a direct result of Rank Brain implementing its advanced artificial intelligence and machine learning capabilities to better understand your search and present relevant results.
After Rank Brain came another Google mastermind project, BERT. BERT stands for Bidirectional Encoder Representations for Transformers. Much like its predecessor, Rank Brain, BERT’s main objective is to ultimately improve the user’s search experience. Unlike Rank Brain, however, BERT isn’t designed to identify and locate specific relevant search results. Instead, BERT is designed to comprehend natural human language and its unique nuances based on the speaking patterns of individuals in specific regions of the world.
Natural language recognition is what ultimately paved the way for the growth and popularity of voice search technology. BERT’s intrinsic natural language processing pre-training capabilities allows it to understand more than just the characters involved in the search query—contextual meanings are at the forefront of this search processing platform.
With all of these amazing innovations constantly taking place, it’s no wonder that Google has managed to monopolize the majority of the search market with a whopping 95% of users using the search engine as their default search platform.
SEO and Artificial Intelligence
So, how does data for SEO comply with artificial intelligence? The answer to this question lies in the correlation between search inquiries and search results. Machine learning technology uses tried and true frames of references to learn to accurately identify certain search terms and images based on specific frames of references. By implementing effective repetitive training techniques, machine learning algorithms are able to improve the accuracy of their search results until they achieve human-like response mechanisms.
The majority of the time when users are interacting with a customer service agent via live chat, they’re really speaking to an artificially intelligent program that’s capable of accurately and effectively mimicking human conversational techniques based on learned natural language traits.
The same mechanisms can and should be used in SEO, particularly when it comes to virtual assistant and voice search platforms. After all, these are platforms that rely either heavily or entirely on presenting users with relevant search results based on their voice-activated search queries.
Initially, the results may not always be what the users are looking for, but with enough self-training and experience gained, eventually the platforms will be able to get better at recognizing certain nuances of natural language and the specific contexts in which they could be used.
As always, the technology is in a constant state of improvement and as advancements continue to be made, it’s important for SEO professionals to sit upright and pay full attention to new announcements and updates from Google.
What Is the Value of Machine Learning for SEO?
Machine learning has a lot of value for SEO. While it’s impossible to optimize your website completely based on voice search and machine learning analytics as the data is constantly changing, you can certainly use the data to make predictions of what topics will be trending in your industry.
Based on these analytical and data-driven predictions, you can then compile a list of relevant keywords that will help boost your rankings and produce content that’s related to top search queries that are currently trending online. Moreover, machine learning can help streamline certain simple backend operations and resolve simple customer service inquiries or issues.
Search Engine Optimization in Toronto
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