Google Cleans Noise In The Trends Data
Daniel Waisberg said that Google cleans the data to remove noise and data that relates to user privacy.
An example of private data that is removed is the full names of individuals. An instance of “noise” in the data includes repeated search queries by the same person, such as a trivial daily search for how to boil eggs.
The part about people repeating a search query is intriguing because, in the early days of SEO, before Google Trends was around, SEOs relied on a public keyword volume tool from Overture (owned by Yahoo). Some SEOs manipulated the data by conducting thousands of searches for rarely-used keyword phrases, artificially boosting their query volume. This tactic misled competitors into optimizing for those ineffective keywords.
Google Normalizes Google Trends Data?
Google doesn’t provide the actual search query volumes, such as one query receiving a million searches per day and another getting 200,000. Instead, Google identifies the peak search volume for a keyword phrase and sets that as the 100% benchmark. The Google Trends graph then displays percentages relative to this peak. For instance, if a query’s highest daily search volume is 1 million, a day with 500,000 searches will be shown as 50% on the graph. This process of adjusting the data to relative percentages is known as normalization in Google Trends.
Explore Search Queries And Topics
For over 25 years, SEOs have concentrated on optimizing for keywords. However, Google has since advanced, now categorizing documents based on topics and even the specific queries they relate to, which is more about topics than individual keywords.
In my opinion, one of the most valuable features is the ability to explore topics related to the search query entity. This exploration reveals the search volume for all related keywords.
The “explore by topic” tool provides a potentially more precise understanding of a topic’s popularity, which is crucial because Google’s algorithms, machine learning systems, and AI models create representations of content at the sentence, paragraph, and document levels that align with specific topics. I believe this is one of the aspects referred to when Googlers discuss Core Topicality Systems.