Let’s go back to the “python” example. If I search for this, I do indeed get all results related to the programming language.
No matter how much we dislike all the ways our personal data is used, it’s at least useful for search engines. Google uses limited data together with your search history to deliver more accurate and personalized search results.
We’re all aware of this. Just type any type of service into your search bar and you’ll get localized results:
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But what’s more fascinating is Google’s ability to temporarily adjust search results based on dynamically changing search intent.
For example, coronavirus is not a new term. It has always been the name of a group of viruses. But as we all know, the search intent changed rapidly at the beginning of 2020. People started looking for information about a particular strain of coronavirus (SARS-CoV-2), and the SERP had to be adjusted accordingly.
The workload like this whatsapp number list allows both the vendor and the affiliate to focus on. Clicks are the number of clicks coming to your website’s URL from organic search results.
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As you can see in the SERP position history for “coronavirus” above, none of the current top five search results ranked before 2020.
You see the same thing in the ecommerce industry during big sales events like Christmas or Black Friday. The search intent during that time is highly transactional, whereas people might ordinarily prefer to see comparisons or reviews.
Which Google technologies play a role in how semantic search works?
Google continuously pushes out algorithm updates and technologies that further improve its capabilities of understanding natural language and search intent.
There are four important milestones that make the semantic search what it is in 2020.
Google’s Knowledge Graph, released in 2012, is a knowledgebase of entities and the relationships between them.
You can imagine it looking something like this—but with five billion entities instead:
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In short, it’s a technology that kickstarted and enabled the shift from keyword matching to semantic matching.