The Impact of Topicality on Google Ranking: Understanding the System

In the latest episode of "Search Off the Record", Google presented many valuable lessons about how Google Search works. Particular attention was paid to the topicality system, which helps determine how the content of the web page corresponds to the topic of the user's search query. This approach is based on machine learning, specifically the BERT model, which helps Google understand words in the context of those that come before and after them.

"Yes, we think about many important aspects of search. We have many systems. Obviously, we want to show content that is topically relevant to your search. In the early stages of Google Search, that was sometimes a challenge. Our systems have gotten much better, but it's all a challenge, especially for very difficult searches that we can struggle with. People search in many ways, from typing in keywords to talking to Google to using normal, everyday language..." - Elizabeth Tucker, director of product management at Google.

🚀 It is interesting to note that Google does not use just one system, but many systems that work together to provide an answer to a search query. Thus, when trying to understand why a web page is ranking a certain way, it is important not to focus on one or two systems, but to consider that the reason may lie in another system that we may not be aware of.

• 📌 Topicality is an important factor for ranking in Google, but not the only one. There are many other systems and signals that Google takes into account when ranking web pages.
• 📌 Google uses machine learning models like BERT to better understand what users mean when they type in a search query.
• 📌 Focusing on topics rather than keywords can be a more effective approach to SEO.