October 31, 2023
Digital Marketing, Search Engine Optimisation
From Backrub to Google – The Rise of Google Search
The early days: From Backrub to Google
In the mid-90s, two Stanford University students, Larry Page and Sergey Brin, embarked on a project called ‘Backrub’, a precursor to what would become the world’s leading search engine, Google. The project’s name was derived from its ability to analyze “back links” to determine a website’s importance. As the digital landscape expanded, the duo recognized the need for a scalable search engine that could effectively rank websites. This vision culminated in the birth of Google in 1997, with a mission “to deliver the most relevant and reliable information available.” This foundational mission influenced every iteration of Google’s search algorithm, emphasizing the importance of relevance and user experience.
The inception of Google was revolutionary. Unlike other search engines of its time that often ranked search results based on the number of times a search term appeared on a webpage, Google Search prioritized relevance. The early algorithm took into account factors such as the quality and relevance of webpages linked to a site, ensuring that users received the most pertinent results. As businesses began to recognize the potential of being highly ranked on Google, the art and science of Search Engine Optimization (SEO) started to take shape.
Table of Contents
Pagerank: The Foundation of Google's Success”
PageRank, named after co-founder Larry Page, is the algorithm that was at the heart of Google’s early success. It was an innovative system that used the structure of the web itself to determine the importance of a webpage.
“Since our launch in 1997, Google Search has continued to evolve to help you find the information you’re looking for.” – Google
By analyzing the number and quality of links to a page, PageRank could effectively gauge a website’s credibility and relevance. This approach was groundbreaking because it looked beyond mere keyword matches and delved into the interconnectedness of the web.
The significance of backlinks in early SEO
Backlinks, or incoming links to a webpage, were a cornerstone of early SEO practices. These links acted as votes of confidence, signalling to Google that a webpage held value to present it in the Google Search Results Pages. However, it wasn’t just about quantity; the quality of these backlinks mattered immensely.
Sites with reputable and relevant backlinks were deemed more trustworthy, leading them to rank higher in search results. This emphasis on backlinks ushered in an era where websites sought to build strong link profiles, both organically and sometimes through less scrupulous methods.
If you’re interested in finding out how Hy can help you grow your website’s rankings, relevancy and trustworthiness then contact our SEO experts today!
“Semantic search was set to revolutionize search engine optimization. It was no longer just about keywords; it’s about creating content that genuinely answers users’ questions.”
From Strings to Things: The Introduction of Semantic Google Search
Google’s Knowledge Graph and its impact
The launch of Google’s Knowledge Graph in 2012 marked a significant shift in the company’s approach to search. Rather than merely matching keywords, the Knowledge Graph aimed to understand the relationships between entities.
This semantic understanding allowed Google to provide users with richer, more contextual search results. For instance, searching for the “Eiffel Tower” wouldn’t just yield websites about the monument; it would also provide information about its height, location, history, and related landmarks.
Shifting from keyword-based to intent-based search
The introduction of semantic search signified Google’s move from focusing on keywords to understanding user intent. This transition emphasized the importance of context, meaning, and relevance. Websites now had to ensure that their content was not only keyword-rich but also meaningful and contextually relevant to rank higher in search results.
Mobile-First Indexing: Adapting to the Mobile Era
The rise of mobile search and its implications
With the increase in the usage of smartphones and tablets, the way people access the internet changed radically. Mobile searches surpassed desktop searches, prompting Google Search to adjust its ranking algorithms.
Recognizing the shift in user behavior, Google introduced mobile-first indexing, emphasizing the importance of mobile-friendly websites. This meant that Google would prioritize the mobile version of a site for indexing and ranking.
Is your business’ website built for mobile first and conversion rate optimised?
Adjusting SEO strategies for mobile users
The mobile-first approach necessitated a change in SEO strategies. Businesses had to ensure that their websites were mobile-responsive, with fast loading times and optimized images and conversion optimised for the best results. The user experience on mobile devices became paramount, influencing factors like site design, navigation, and content structure.
RankBrain: Embracing Machine Learning in Search
Google’s first steps into machine learning with RankBrain was another testament to its commitment to improving search. RankBrain is a machine learning-based component of Google’s core algorithm that helps decipher complex search queries, especially those that the system hasn’t encountered before.
It interprets the intent behind queries and provides relevant results, even if the exact phrasing isn’t present in the indexed web pages. This shift towards understanding user intent further emphasized the importance of optimizing your website and creating quality content over keyword stuffing for better website rankings in Google Search Results.
BERT & Core Updates: Towards Natural Language Understanding
The significance of BERT in understanding Google Search queries
In 2019, Google rolled out BERT (Bidirectional Encoder Representations from Transformers), a neural network-based technique for natural language processing. BERT’s primary goal is to understand the context of words in search queries better.
For instance, the word “bank” could mean a financial institution or the side of a river, and BERT helps Google’s algorithm determine the correct context based on the entire query.
Navigating the continuous core algorithm updates
Google’s continuous core algorithm updates aim to provide users with the most relevant and high-quality search results. These updates often involve tweaks to the algorithm to counteract spammy practices and reward genuine, valuable content.
For businesses and SEO professionals, it’s crucial to stay updated with these changes and adjust strategies accordingly to maintain or improve search rankings.
“In the world of SEO, change is the only constant. Adapting to algorithm updates and understanding the nuances of natural language processing and relevancy will be key to success in the coming years.”
Google's Algorithm Patents: A Peek Behind the Curtain
Deciphering Google’s patented technologies
Google’s numerous patents offer invaluable insights into its search algorithm’s inner workings. While not all patented technologies are used in their core algorithm, they reflect the company’s research direction and potential future implementations.
By analyzing these patents, the SEO experts at Hy Digital gain a deeper understanding of the principles that guide Google’s search functionalities and the possible techniques Google may employ in the future. This helps us craft up-to-date SEO ranking strategies for the best results.
How patents shape the future of search
Patents not only protect intellectual property but also provide a roadmap of where technology might be headed. Google’s patents, ranging from machine learning techniques to voice search optimizations, suggest a continuous commitment to improving user experience and adapting to emerging technologies.
The team at Hy Digital always stays up to date on the latest developments, patents and trends in SEO. Contact our SEO expert to discuss any questions you might have.
Preparing for the Future of SEO
Adapting to the ever-evolving search landscape with AI
Artificial Intelligence (AI) is reshaping many industries, and SEO is no exception. As Google incorporates more AI and machine learning into its search algorithms, businesses must understand these technologies to optimize their web presence effectively.
Embracing change and staying ahead in the SEO game
The only constant in the realm of SEO is change. To succeed, businesses must be agile, adaptable, and proactive. At Hy Digital this entails continuous learning, testing, and iterating SEO strategies and being open to novel technologies and methodologies.
From its inception as a university project to its current status as the world’s leading search engine, Google’s algorithms have continually evolved, always with the user’s experience at the forefront.
This deep dive into the evolution of Google’s search algorithms underscores the importance of adaptability in SEO. As technology advances, businesses must stay informed, be flexible, and anticipate changes to remain competitive in the digital landscape.
FAQ About "The Evolution of Google's Search Algorithms"
Here are some commonly asked questions regarding the evolution of Google’s search algorithms.
Is your question not answered here? Contact our experts as we would love to chat with you!
It was known as "Backrub," which was the precursor to what would eventually become Google.
With the increasing number of users accessing the internet via mobile devices, Google introduced mobile-first indexing to prioritize mobile-friendly sites and enhance the mobile user experience.
BERT is a neural network-based technique for natural language processing that helps Google better understand the context of words in search queries.
Google makes thousands of changes to its search algorithms every year, but major core updates are less frequent, typically several times a year.
They offer insights into the potential future directions of Google's search functionalities and allow professionals to anticipate and prepare for possible changes.
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Digital Marketing, Search Engine Optimization
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