Google has earned a special place in the search engine industry. It’s the world’s leading search engine in terms of search volume, currently serving 3.5 billion search queries per day. Google has consistently invested in machine learning to improve its SEO metrics and serve 40k+ search queries per second. Natural language processing (NLP) is one of the pivotal machine learning products for Google. It has enabled Google to decode the search intent and relation between the words to perform the semantic search.

NLP is the future; learning about NLP is critical for understanding Google’s evolving SEO metrics. This blog will walk you through the NLP fundamental concepts and how Google NLP is impacting SEO marketing.

What is Natural Language Processing?

NLP – Natural language processing uses machine learning modules to analyze the words’ structure, intent, meaning, relation, and sentiments to interpret the text.

NLP is a subset of AI (artificial intelligence) that uses ML models to extract information from unstructured text. NLR (Natural language recognition) and NLG (Natural language generation) are the two fundamental types of Natural language processing.

NLP Frameworks

There are two frameworks of NLP,

• BERT – Bidirectional Encoder Representations from Transformers (BERT) was introduced in 2019 by Google. It enables NLP algorithms to look at the surrounding words to precisely interpret a word’s meaning instead of looking at a single word like its predecessor.
• SMITH – Google revolutionized SEO and AI by introducing the new NLP framework SMITH (Siamese Multi-depth Transformer-based Hierarchical), in early 2021. Unlike its predecessor, SMITH allows NLP models to analyze the surrounding paragraphs to better interpret a word or passage by analyzing the document.

BERT and SMITH frameworks enable Google to isolate the most relevant passages against the search queries for SERPs. However, SMITH can do it better because of its capability to analyze the surrounding passages for interpreting a paragraph’s meaning.

Google NLP Impact on SEO Marketing

Digital marketers should closely follow Google’s every update as it can dramatically impact the site’s ranking. A few Google updates may have less impact on SEO marketing than others; however, you need to comprehend every update to optimize your business sites.

The addition of NLP algorithms to Google has impacted its ranking metrics. You need to focus on these impacts to learn how to optimize the business sites to regain top ranking.

Writing keyword-rich content with a particular keyword density is not enough to grab Google’s attention after the NLP introduction. Google loves the natural writing style, and NLP enables it to rank natural content on top SERPs.

You can follow the enlisted tips to get noticed by the Google SEO metrics after the NLP frameworks addition,

Optimize for Long-Tail Keywords

Before the NLP frameworks introductions, marketers avoided targeting long-tail keywords as Google ranking metrics could not comprehend the context. Now, NLP has enabled Google to look at the surrounding passages to decode the context of a particular paragraph. And it has opened the gates for long-tail keywords. In fact, after the NLP addition, ranking the long-tail keywords is easier and more worthful than single-word keywords.

The following are the reasons behind the increasing weightage of long-tail keywords,

• They allow marketers to target a micro topic. For instance, targeting a long-tail keyword like “SEO product description writer” lets you reach your target audience compared to a single-word keyword like “writer.
• Long-Tail keywords give a clear context to search queries and website content, making it easier for NLP-powered SEO metrics to display relevant results on SERPs.
• Long-tail keywords will indirectly assist you in getting rank for single-word keywords. NLP updates allow Google to look at the context of search queries to trigger relevant results on SERPs. It makes it easier for marketers to target a long-tail keyword, write thoroughly on a topic and enjoy ranking on a long-tail keyword along with single-word keywords because of rich context.
• It’s easier to rank for voice searches with long-tail keywords, as voice searches generally have up to four words.
• Long-tail keywords assist marketers in building a robust SEO funnel. Marketers can easily find options for building internal links and external do-follow links with long-tail keywords compared to single-word ones.
• Last but not least is the incredible portion of long-tail keywords searched in total Google search volume. A study reveals that 95.88% of Google searches have long-tail keywords (comprised of four or more words).

Focus on User Search Intent

NLP framework incorporation into Google is a few of its initial practical steps in making user search intent a primary SEO metric. Search intent is way more important than keyword optimization after the NLP frameworks BERT and SMITH incorporation into Google. Your content must address the users’ needs and answer their queries directly if you want to get visibility for your business site.

Refine the Website Formatting

Website formatting is another key feature Google looks at while analyzing a site to rank it higher on SERPs. Focus on refining your website formatting to display images, content pieces, and meta tags correctly. A well-formatted website provides a positive user experience and assists search engine crawlers in crawling a site. Besides, a well-formatted site gets NLP frameworks’ attention and gets featured on higher SERPs against the related semantic searches.

Quality Backlinks

Focus on backlinks quality, not quantity, as Google’s new SEO metrics update prioritize the sites with quality backlinks. Pay attention to getting backlinks from high-authority sites. Do your site audit to find and remove the backlinks from low authority and unrelated sites. The NLP incorporation into Google is just an initial step toward the semantic search; you may get your site ready with a customer-centric approach to meet the Google SEO metrics and avoid losing top ranking on SERPs.

Final Words | Everything you should know about Google NLP

NLP – Natural language process is a subset of AI that has revolutionized the way today’s search engines work. It relies on machine learning models to assist Google in providing the semantic search experience. After the NLP incorporation into Google, its SEO metrics don’t rely solely on keywords to find relevant content for SERPs.

You may follow the above-discussed tips to optimize your business sites after the NLP incorporation into Google. It will surely enable your business sites to avoid losing the top position on the SERPs.