What You Need to Know to Properly Analyze Google Trends Data
Posted: Sun Feb 02, 2025 7:17 am
Not everyone understands what Google Trends data is. It may seem like the trend curve is simply the dependence of sales volume on time. Various Google Trends analogues provide approximately such results.
But in our case the operating principle is different.
Let's compare the data obtained for the query "flowers" on two different services: Google Trends and GKP:
What You Need to Know to Properly medical practice email list Analyze Google Trends Data
Note : You can only get curves like these in Google Keyword Planner if you pay for AdWords.
The figure shows that the resulting graphs are almost indistinguishable, but this is not so. The upper graph contains data on the relative popularity of the query, and the lower graph contains absolute data on the search volume.
Let's see how the Google Trends Help Center comments on this:
"Trends adjusts search values to make it easier to compare search terms. The resulting data points are divided by the total number of queries — across geographic and time parameters — it returns to compare relative relevance."
That is, relative popularity is the ratio of the number of queries you are interested in to the sum of all possible searches.
"The resulting data is scaled from 0 to 100 based on a specific characteristic that is relevant to all queries."
Google Trends, when creating a trend chart, excludes searches that came from the same user over a short period of time. This helps to see a more realistic situation. Please note that the service can only be used for relevant keywords. Otherwise, you will get zero results.
Below is Google Trends data for the query "Facebook"* last year in the US:
The resulting data is scaled from 0 to 100 based on a specific characteristic that is relevant to all queries.
To understand the system by which the “Popularity Dynamics” graphs are constructed, let’s imagine that we, like Google, have all the necessary information.
The table below contains the values. They should not be taken seriously, as they are provided only as an example and have nothing to do with reality.
Assumption 1 : In the US, the approximate number of all search queries per month is 10 billion.
Assumption 2 : There are 83 million searches for the keyword “Facebook”*.
Facebook
To convert the data to Google Trends format, we will perform the following steps:
First, let's calculate the ratio of the number of queries for a term to their total number. The resulting number is called relative popularity.
Let's take the maximum value as 100 and perform scaling.
All that remains is to place the obtained values on the graph.
Download a useful document on the topic:
Checklist: How to Achieve Your Goals in Negotiations with Clients
This is what we ended up with:
Google Trends
Two conclusions follow from this.
The popularity of a term is directly related to how often it is used, as can be seen from the values for May and June 2017. But you probably already knew that.
But the popularity of a query is also affected by their total number. That is, if a specific key is used just as often, but the variety of queries has increased, then the relevance will decrease. This is observed in June-July 2017.
Now you understand that the "popularity" criterion obtained from the analysis in Google Trends usually does not depend on the number of specific queries. But sometimes this connection is still present.
For example, the keyword “Star Wars” has a clearly visible peak in December 2015, which is tracked in both Google Trends and Ahrefs Keywords Explorer, despite the difference in the data processing systems.
But in our case the operating principle is different.
Let's compare the data obtained for the query "flowers" on two different services: Google Trends and GKP:
What You Need to Know to Properly medical practice email list Analyze Google Trends Data
Note : You can only get curves like these in Google Keyword Planner if you pay for AdWords.
The figure shows that the resulting graphs are almost indistinguishable, but this is not so. The upper graph contains data on the relative popularity of the query, and the lower graph contains absolute data on the search volume.
Let's see how the Google Trends Help Center comments on this:
"Trends adjusts search values to make it easier to compare search terms. The resulting data points are divided by the total number of queries — across geographic and time parameters — it returns to compare relative relevance."
That is, relative popularity is the ratio of the number of queries you are interested in to the sum of all possible searches.
"The resulting data is scaled from 0 to 100 based on a specific characteristic that is relevant to all queries."
Google Trends, when creating a trend chart, excludes searches that came from the same user over a short period of time. This helps to see a more realistic situation. Please note that the service can only be used for relevant keywords. Otherwise, you will get zero results.
Below is Google Trends data for the query "Facebook"* last year in the US:
The resulting data is scaled from 0 to 100 based on a specific characteristic that is relevant to all queries.
To understand the system by which the “Popularity Dynamics” graphs are constructed, let’s imagine that we, like Google, have all the necessary information.
The table below contains the values. They should not be taken seriously, as they are provided only as an example and have nothing to do with reality.
Assumption 1 : In the US, the approximate number of all search queries per month is 10 billion.
Assumption 2 : There are 83 million searches for the keyword “Facebook”*.
To convert the data to Google Trends format, we will perform the following steps:
First, let's calculate the ratio of the number of queries for a term to their total number. The resulting number is called relative popularity.
Let's take the maximum value as 100 and perform scaling.
All that remains is to place the obtained values on the graph.
Download a useful document on the topic:
Checklist: How to Achieve Your Goals in Negotiations with Clients
This is what we ended up with:
Google Trends
Two conclusions follow from this.
The popularity of a term is directly related to how often it is used, as can be seen from the values for May and June 2017. But you probably already knew that.
But the popularity of a query is also affected by their total number. That is, if a specific key is used just as often, but the variety of queries has increased, then the relevance will decrease. This is observed in June-July 2017.
Now you understand that the "popularity" criterion obtained from the analysis in Google Trends usually does not depend on the number of specific queries. But sometimes this connection is still present.
For example, the keyword “Star Wars” has a clearly visible peak in December 2015, which is tracked in both Google Trends and Ahrefs Keywords Explorer, despite the difference in the data processing systems.