Google’s exact ranking algorithms remain unclear as they are so complex due to machine learning. Nevertheless, it is important to understand the search engine structure in order to better categorise ranking anomalies. ๐
๐New material is discovered by Googlebots through crawling. Sitemaps and links help to index content. The โAlexandriaโ indexing system assigns DocIDs and decides which URL is favoured in the rankings. Relevant content ends up in the โHiveMindโ, while less important content is stored on hard drives. ๐พ
During a search, QBST analyses the terms and filters relevant results. Systems such as Twiddler and NavBoost optimise rankings based on additional signals such as user behaviour and clicks ๐. Twiddler can customise content and increase relevance. ๐ง
๐Google uses click-through rate data and other user behaviour signals to dynamically adjust rankings. This data has a major influence, even if Google does not officially confirm this. ๐ง
The Google Web Server (GWS) compiles the search results, with systems such as CookBook and FreshnessNode adjusting rankings in real time. Changes in rankings often depend on external factors and are not always a sign of mistakes โ๏ธ. Successful SEO includes not only on-page optimisation, but also the consideration of user behaviour and dynamic ranking factors. ๐
๐๐บ๐ฝ๐ผ๐ฟ๐๐ฎ๐ป๐ ๐ฆ๐๐ข ๐ถ๐ป๐๐ถ๐ด๐ต๐๐:
- Diversify traffic sources and increase brand awareness ๐๐.
2. Customise content to the search intent.
3. Optimise titles, descriptions and avoid content that is difficult to access ๐.
4. Remove weak pages and improve the page structure.
5. Encourage engagement and maintain high-quality backlinks ๐.
