Google’s Model of Learning: Understanding the Structure, Consumption, Learning, and Retirement Approach
Google has a unique approach to interacting with the web, which can be seen as a pattern of “give and take.” The search engine provides structured data formats and tools that allow users to supply information to Google. This includes meta tags, schema markup, and the disavow tool, among others. Google then consumes and learns from this structured data deployed across the web. Once it has extracted sufficient learnings, Google retires or de-emphasizes these structured data formats, making them less impactful or obsolete. This cyclical process seems to be a core part of Google’s strategy.
The first stage of this pattern is structure. Google provides ways for webmasters to interact with search snippets or its ranking algorithms. In the past, meta keywords played a crucial role in Google’s ranking algorithms. However, they were quickly abused by webmasters who injected thousands of keywords per page to increase search traffic. As a result, Google announced in 2009 that it no longer uses the keywords meta tag in its web search ranking. Another example is the meta description, which Google supported since its early days. However, Google started ignoring meta descriptions in certain situations to better match user search intent.
The second stage is consumption. Google collects data from the web by crawling websites. This step is crucial as it allows Google to learn from the structured data provided by webmasters.
The third stage is learning. After consuming the structured data, Google leverages fresh crawl data to make changes to its ranking algorithms. It examines the reactions to its proposed tools or snippets of code and determines if they were useful changes or abused.
The final stage is retirement. Once Google has learned what it can from the structured data, it retires or diminishes those capabilities. Leaving them intact would lead to abuse over time. For example, Google introduced support for schema (a form of structured data) in 2009. Initially, schema had the power to control the visuals of a page’s search listings. However, people began abusing this power, and Google started penalizing rich snippet spam. Today, while still useful, schema is not as powerful as it once was.
This give and take approach allows Google to temporarily empower SEOs and brands to extract data and improve its algorithms. It also helps Google continually improve its understanding of the web. However, it’s important to note that Google usually discards these structural items before illegitimate manipulations become widespread. It’s a race for webmasters to learn from Google’s suggested structure before Google discards it.
Some may argue that these temporary deployments from Google are not worth the effort, while others see it as an opportunity to gain temporary control. It ultimately depends on your ability to adapt to web changes efficiently. If you’re comfortable with quick changes, it can be beneficial to implement what you can and react fast. However, if you lack the expertise or resources for quick changes, blindly following trends may not be worth it.
In the end, this give and take relationship between webmasters and Google doesn’t necessarily make Google evil or bad. It’s a business leveraging its unique assets to drive further learning and commercial activity. Whether you choose to cooperate with Google’s temporary power, long-term learning trade deals is up to you. But be aware that not cooperating may leave you at a competitive disadvantage.
Overall, Google’s model of learning through structured data and then retiring or diminishing those capabilities is a fascinating approach that has shaped the way we interact with the search engine. It highlights the constant evolution of Google’s algorithms and its commitment to improving user experience and search results.
