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California Business Journal
5 Tech trends in SEO to apply in 2023

Photo Credits: TechABU

5 Tech trends in SEO to apply in 2023

by Bia Pendelton, California Business Journal
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SEO is a dynamic field. What worked a few weeks ago may not work today. Thus, SEO campaign management professionals need to be up-to-date on the latest trends and technologies in order to stay ahead of changing industry demands. This will allow them to stay ahead of the curve and improve your business’ efficiency.

This post will discuss five technologies in the SEO field and their impact on your work as an SEO expert. These technologies will help you scale your SEO efforts in 2023 and beyond. Therefore, you should start using them immediately in your business.

Mobile-First Indexing to Improve SEO Ranking

The proliferation of smartphones has increased exponentially. As a result, mobile search is becoming more popular than desktops, laptops, and other devices. If you design and market your site for desktops and ignore what Google Analytics has to say about mobiles, your SEO and content marketing efforts will be hampered.

Google will use mobile-friendly search algorithms to rank pages on a site’s mobile site. They will also use structured data to understand and show snippets of those pages in their results. As a result, your mobile site is now more important to Google than your desktop site.

While indexing and ranking are two different things, they are closely related. The ranking is the way that indexing determines how your page is viewed by Google bots or other web crawlers. Indexing refers to how your page is viewed by Google bots and other search engines. Your rankings will drop if your page isn’t properly indexed.

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Optimize dynamic web content and optimize images for enhanced mobile experiences. A mobile-optimized version can improve your page ranking and increase organic traffic.

SSL Certificate Labeling to Strengthen Customer Trust

Although often forgotten, SSL certificate (HTTPS) labeling is an important SEO trend that businesses should consider. HTTPS is an important ranking factor for Google because it builds trust with your target audience. This requirement has been reinforced by ongoing innovations in search engine optimization.

Google labels websites that have an SSL certificate as “HTTPS.” This means that the site is highly secure and reliable. For example, Digital Print business that provides printing services must ensure the security of user data. This can increase their search engine rankings and help drive more traffic, thus more sales.

Google and other search engines will label a site as “Not Secure” if it does not have SSL certification or is non-HTTPS. This could have a significant impact on search engine rankings. As a result, end-users may be reluctant to visit sites that are not secure.

These are the implications for innovation in this area. Websites must have a basic SSL certificate in order to improve search engine rankings and provide secure browsing. It is now an integral part of any SEO strategy.

Natural Language Generation (NLG) for short-form content

SEOs can now create meaningful sentences and phrases using NLG.

NLG automates the writing process, so you don’t have to struggle with writer’s block or spend hours trying to figure out what words to use. Instead, NLG makes it easy to focus on creating and polishing content.

There are many uses for NLG. However, it is best to use it to create short-form content like headlines, product descriptions, memos, and so forth.

TF*IDF

TF-IDF stands for “Term Frequency times inverse document frequency.” It is a statistical measure that reflects the importance of a term in a document or a collection of documents. The basic idea behind TF-IDF is that if a term frequently appears in a document but is rare in the rest of the collection, it is likely to be an important term for that document.

Yes, Google uses TF-IDF as one of the many ranking factors to determine the relevance of web pages to a given search query. So, make sure to include it in your on-page SEO strategy.

In the context of search engines, TF-IDF is used to calculate a score that reflects the relevance of a web page to a given search query. This involves calculating the TF-IDF score for each term in the query and for each document in the collection. The documents with the highest TF-IDF scores for the query terms are considered the most relevant and are ranked higher in the search results.

However, it’s important to note that TF-IDF is just one of many ranking factors that Google uses. Google’s ranking algorithm is complex and involves many other factors, such as PageRank, content quality, user experience, and many others. In addition, Google’s algorithm is constantly evolving, and the weight given to each ranking factor can vary depending on the specific search query and other contextual factors.

NLP (Natural Langue Processing).

Natural language processing, also known as NLP, is an AI field that allows machines to understand written and spoken human language. It combines computer science and linguistics to analyze and “understand” language and extract meaning from speech and text. Here are some ways NLP is used in search engines:

  • Query Understanding: NLP algorithms help search engines understand the intent behind a search query. For example, if a user types “how to bake a cake,” NLP algorithms can understand that the user is looking for instructions on how to bake a cake.
  • Keyword Extraction: NLP algorithms are used to extract important keywords from the search query. These keywords are then used to match the query with relevant web pages.
  • Document Understanding: NLP algorithms are used to understand the content of web pages. This includes identifying important keywords, extracting entities such as names and locations, and understanding the context of the content.
  • Query Expansion: NLP algorithms are used to expand the query to include related terms and synonyms. This helps to ensure that relevant results are returned even if the exact keywords are not present in the content.
  • Rank and Relevance: NLP algorithms are used to determine the relevance of web pages to a given search query. This involves analyzing the web page’s content, the website’s authority, and other factors in determining the web page’s ranking in the search results.

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Tags: AIbestbusinessesdatafocusimproveinnovationlanguagemarketingmobileorganicscienceSEOsmartphonestargetTech trendstrust
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Bia Pendelton, California Business Journal

Bia Pendelton, California Business Journal

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