![]() ![]() Now you see that popularity used in Google Trends does not always correlate with query’s search volume. Search term popularity will also change if the total number of searches changes, even if the query’s search volume is constant (see June 2017 - July 2017 in my example above).Search term popularity changes when the query’s search volume changes (see May 2017 - June 2017).This example gives us two important takeaways: Scale these values proportionally so that the maximum value is 100.Calculate relative popularity as a ratio of the query’s search volume to the total number of searches.To build a graph the way Google Trends does, you need to take the following steps: Here’s the table I made for this simulation: They are just an assumption to demonstrate how things work.Īssumption 1: the total monthly number of all Google searches in the US is around 10 Billion ( Source)Īssumption 2: the search volume for the query “Facebook” in the US is 83 Million (according to Ahrefs Keywords Explorer) The numbers I will use below are by no means accurate. To demonstrate you how Google Trends builds its “Interest over time” graph, let’s pretend I have the same data Google has. Here’s the Google Trends graph for the query “Facebook” over the past 12 months (in the US): ![]() And it is important to note that Trends only shows data for popular terms (low volume appears as 0). ![]() Trends eliminates repeated searches from the same person over a short period to give you a better picture. The resulting numbers then get scaled on a range of 0 to 100 based on a topics proportion to all searches. ![]()
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