Are you an SEO practitioner looking to improve your website ranking on Google? In this article, we will explore Google’s ranking algorithms to give you insights into how Google conducts its ranking process. Continue reading to discover more about the secrets behind website rankings on Google.

Key Takeaways

• Factors such as site authority, loading performance, and adherence to search engine rules affect website rankings.
• BERT is a key technology in understanding human language in search queries.
• Google’s system uses various algorithms, including Deduplication, Exact Match Domain, Freshness, Helpful Content, Link Analysis, MUM, Neural Matching, Original Content, Passage Ranking, RankBrain, Reliable Information, Review, and Spam Detection.

BERT (Bidirectional Encoder Representations from Transformers) – The Translator

The main goal of BERT is to enhance the understanding of human language in search queries and how it relates to Google’s dataset or documents for search results. Launched in 2019, BERT marked a major breakthrough in natural language understanding, helping us comprehend how word combinations express various meanings and intentions. BERT doesn’t simply look for content that matches individual words; it understands how word combinations express complex ideas. It interprets words in order and how they relate to each other, ensuring important words aren’t missed in user queries. For example, if you search “Can you pick up medicine for someone at the pharmacy?” BERT understands that the user is asking whether the person you’re speaking to can pick up medicine for someone else.

Today, BERT plays a crucial role in processing every query across multiple languages. Based on its understanding of complex language, BERT quickly ranks relevant documents to provide accurate results. Though BERT plays a primary role in Google Search, it doesn’t work alone; it’s part of a group of systems working together to deliver high-quality results.

Fun Fact: BERT is based on Transformer technology, the same technology used in ChatGPT (Generative PreTransformer).

For more details on BERT, click here (https://blog.google/products/search/search-language-understanding-bert/).

Deduplication System – Fighting Plagiarism with AI

Google Search can return thousands or even millions of web pages that match. Some of these may be very similar to one another. In such cases, Google’s system only displays the most relevant results to avoid displaying duplicates that are not helpful.

Deduplication also applies to feature snippets. If a webpage is featured in a snippet, Google will not list it again on the first page of search results.

Exact Match Domain System – Preventing System Exploitation

Google’s system considers the words in a domain name as one factor in determining content relevance in search results. However, Google ensures that content hosted under a domain intentionally designed to exactly match a particular query does not receive excessive ranking. For example, someone might create a domain name containing the words “seo-services-professional” hoping that all the words in the domain will boost their ranking. Google’s system adjusts this.

Freshness System – Monitoring the Timeliness of Sites

Google has various systems designed to display the most up-to-date content. For example, a search about “earthquakes” might typically return information about their causes and required disaster response. However, if an earthquake has occurred recently, news articles and fresher content might appear.

Helpful Content System – Focusing on Helping Readers, Not Search Engines

The Helpful Content Update is Google’s effort to enhance the quality of websites’ rankings in search engines. Google looks for helpful, original content written by humans for humans. Content that is unhelpful, repetitive, or overly promotional will perform poorly. To rank at the top in search results, it’s essential to create informative, comprehensive content that meets user expectations. With this update, Google emphasizes user experience and encourages content creators to avoid unhelpful practices.

Link Analysis Systems and PageRank – The Importance of Links in SEO Optimization

Google uses various systems to understand the relationships between pages to determine the topic of a page and which pages are most helpful in answering a query. One such system is PageRank, Google’s core ranking algorithm when it was first launched. PageRank looks at the links between pages to determine their ranking and SEO performance in search results.

Read Also: Is your site ready for Google’s algorithm change this April 21?

MUM – AI for Text, Images, and Video

Google has developed the Multitask Unified Model (MUM) as a far more powerful system than BERT. MUM can understand and generate language with a thousand times more power. It is trained in 75 languages and can handle multiple tasks simultaneously, allowing it to develop a more comprehensive understanding of the world’s information and knowledge. Additionally, MUM is multimodal, meaning it can understand information across various modalities like text, images, and potentially more in the future.

Although we are still in the early stages of MUM’s potential, Google has used it to improve searches for COVID-19 vaccine information. In the coming months, Google will offer more intuitive search features that combine text and images through Google Lens. However, MUM’s current application is specific and does not yet help determine rankings or improve search result quality as systems like RankBrain, neural matching, and BERT do.

In Google Search, MUM is used to analyze rankings and offer a broader understanding of global information.

Neural Matching – Matching Queries and Documents Based on Human Brain Function

Neural Matching (NM) or Neural Networks form the basis for many modern AI systems. However, it was only in 2018 that Google introduced Neural Matching into Search, enabling them to better understand how queries relate to pages. Neural Matching helps Google understand more abstract representations of queries and pages, and matches them. Neural Matching looks at an entire query or page rather than just keywords, thereby developing a better understanding of the underlying concepts. For example, a search query like “how to manage green things” might confuse you in casual conversation. But with Neural Matching, Google can understand it.

Original Content Systems – Ensuring the Visibility of Original Sites

Google has systems in place to ensure that original content is given priority in search results. This includes support for canonical markup tags to identify the main page in case of duplication. This helps Google display relevant search results and supports original content.

Passage Ranking System – Understanding Information at the Paragraph Level

Finding specific information can be challenging, as sometimes the answer might be buried deep within a webpage. Google has made a breakthrough in ranking and now better understands the relevance of paragraph-level snippets. By understanding these snippets and their relevance to the entire page, Google can find the information users are searching for, almost like finding a needle in a haystack. This technology will improve search results by 7% in all languages as it is rolled out globally.

RankBrain – AI for Discovering New Information

RankBrain is an AI system that helps Google understand how words relate to concepts. This means Google can return relevant content even if it doesn’t contain all the exact words in a query, by understanding that the content is related to other words and concepts. This check aims to improve Google’s AI’s understanding of the relationships between words and concepts. Its main goal is to develop the ability to return relevant content even if it doesn’t contain all the exact words in the query.

Reliable Information System – Detecting Trustworthiness and Author Experience

This system helps Google rank higher quality pages and demote lower-quality content, improving journalism. In cases where reliable information may be scarce, Google automatically displays content warnings about rapidly changing topics or when reliable information is not found in search results.

Review System – Cross-Checking Customer Reviews

The Review System rewards high-quality reviews—those that provide informative analysis, original research, and are written by experts or enthusiasts with a deep understanding of the topic. This is done through an AI-based verification process by Google.

Spam Detection System – Fighting Spam and Exploitation

The internet contains vast amounts of spam content that can prevent Google from displaying the most helpful and relevant results. Various Google algorithms are used to handle content and behavior that violate spam policies. These systems are continually updated to stay ahead of new spam threats.

Conclusion

Google’s ranking algorithms are crucial for improving website rankings on the world’s largest search engine. Factors like site authority, loading performance, and adherence to search engine rules affect search results. You don’t need to study every algorithm in-depth; some of Google’s algorithms are dynamic, with the help of AI making them complex. Refer to the Search Essentials guide to ensure your site is meaningful to readers and enhances your Google ranking. Always remember to help readers first before optimizing for search engines.

Doxadigital Creative Digital Agency is an official Google Premier Partner, Facebook Preferred Agency, and TikTok Agency that offers a full range of digital marketing services. If your business needs an SEO strategy to improve its Google ranking, contact us via WhatsApp at +6281288883692 for a free SEO consultation and discover the right digital marketing solutions for your business.

Reference: A Guide to Google Search Ranking System

Viktor Iwan( CEO and Founder of Doxadigital Creative Digital Marketing Agency )

Viktor Iwan adalah CEO dan pendiri Doxadigital Creative Digital Agency. Dia juga merupakan pembicara dan pelatih publik dalam berbagai acara pemasaran digital seperti “Social Media Week”, “Tech in Asia”, “WordCamp”, “SEOCon”, “QuBisa Bootcamp”, dan “Google Agency Bootcamp”. Viktor Iwan memiliki sertifikasi Google Ads, Facebook Lead Trainer, Facebook Media Buying and Planning, dan Google Analytics. Dia juga menjadi salah satu dari 5 Product Expert Google Ads asal Indonesia oleh Google Inc. Viktor Iwan juga memiliki website pribadi di viktoriwan.com.