Google’s original breakthrough in search was placing weight on links & using them to approximate the behavior of web users.
The abstract of
The PageRank Citation Ranking: Bringing Order to the Web reads
The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.
Back when I got started in the search game if you wanted to rank better you simply threw more links at whatever you wanted to rank & used the anchor text you wanted to rank for. A friend (who will remain nameless here!) used to rank websites for one-word search queries in major industries without even looking at them. 😀
Suffice it to say, as more people read about PageRank & learned the influence of anchor text, Google had to advance their algorithms in order to counteract efforts to manipulate them.
Over the years as Google has grown more dominant they have been able to create many other signals. Some signals might be easy to understand & explain, while signals that approximate abstract concepts (like brand) might be a bit more convoluted to understand or attempt to explain.
Google owns the most widely used web browser (Chrome) & the most popular mobile operating system (Android). Owning those gives Google unique insights to where they do not need to place as much weight on a links-driven approximation of a random web user. They can see what users actually do & model their algorithms based on that.
Google considers the user experience an important part of their ranking algorithms. That…