Encoding SERPs: The Impact of AI on Ranking
A lot has happened to the Search Engine Results Pages (SERPs), especially over the last few years, and this has been driven by the advances in artificial intelligence and machine learning. As the algorithms become more complex and advanced, such as the one used by Google, there is always improvement in presenting the best search results to end users. Therefore, website owners and content creators have had to factor this into their decision-making by considering SEO.
AI and Voice Searches
Some search algorithms have incorporated AI into the system since before it became a new trend. Google has been the first to embrace this by providing its users with a feature to block specific websites. The purpose of Google has also changed over the years, and its ranking factor has also introduced other features that help it consider the user’s intention and the page’s relevance.
Some of the key AI technologies Google uses include:
RankBrain: Initially introduced in 2015, this AI system assists Google in translating search queries and comprehending their meaning even if their words have never been entered. This enables Google to connect the searches carried out with the content that best matches them.
BERT: The Bidirectional Encoder Representations from Transformers, commonly known as BERT, was introduced in 2019. It works with words and the relationship to any other words in a given sentence, which helps Google understand the context of the content.
MUM: The proposal for the Multitask Unified Model was made in 2021. It can help Google deal with complicated inquiries and necessities, delivering the most relevant and accurate answers and findings.
Impacts on Rankings
This resulted in a change of focus in Search Engine Optimization as it gradually incorporated the uses of Artificial Intelligence.
Some of the critical impacts include the following:
- It has been realized that quality content is more important than ever before, especially with the rise of the internet and technology. It is necessary to be very careful of the kind of content being produced, developed, and shared as AI algorithms are very effective in analyzing content. First of all, content should satisfy the need of a searcher and it should be clear what kind of relevance it has, not to be disguised by such things as topic analysis, headings, and tags.
- Increased focus on E-A-T (expertise, authority, trustworthiness) signals– To assess the level of emphasis that has been placed on enhancing E-A-T signals, consider that Google gives priority to content from the sources considered more reliable, which is evident in the case of website ranking. Thus, such factors as website expertise, author credentials, and trust indicators originating from the E-A-T signals are more relevant.
- Analyzing the case from this perspective, it can be noted that keyword targeting is gradually taking a backseat. In the past, the two main ranking strategies used in the SEO process were keyword targeting and optimization. However, with the rise of semantic parsing and intent understanding by the bots and machines, keywords are of little significance now. Compared to previous studies, there is an increased emphasis on topics and natural language.
- Link popularity is still an essential indicator of Google ranking as the references to the web site. Since links help AI in determining the relevance of the site based on the authority and trust metrics, they are useful when it comes to the examination of websites.
- Additionally, since most searches are done on a mobile device, it is crucial to have a mobile-friendly website. This is because it loads fast, has good font size, is easy to navigate and does not require to pinch or zoom most of the time. It is also possible to increase the visibility of mobile SERPs by using structured data and accelerated mobile pages (AMP).
- AI is particularly adept at comprehending multimedia such as pictures, motion pictures, and structured information. When properly applied, all these aspects assist in capturing the attention and explaining how the content is relevant.
- As the local search evolves, however, it is crucial to invest more time in the organization and verification of the listings within Google My Business, Apple Maps, Bing Local, etc., in terms of receiving local traffic. The citations and reviews produced on the regional level also contribute to the trust and authority.
Key Takeaways
The improvement and optimization of the search process through AI and ML are the main focus of Google. In this evolution process, the SEO technique also experiences changes. While there is still a basis of good practices that are carried over for use in the current SEO, more importance is placed on quality content generation, authority creation, semantic optimization, and user experience across interfaces.
Conclusion
These changes are attributed to breakthroughs in AI that have significantly impacted the SERP and rankings of search engines. It can be safely assumed that in the future, Google will continue the development of AI technologies, which will create new SEO strategies and make specific old techniques irrelevant. But it is not gone; the human touch still counts. When SEO is aligned with AI, brands can focus on creating quality content, establishing authority, and enhancing user experience to remain relevant to the constantly changing SERP features.
