7/25/2023 0 Comments Google trends.![]() ![]() It would make sense to start prioritizing the optimization of such pages a couple of months before the peak occurs (i.e., 2-3 months before December, if you’re in Australia). Start optimizing existing relevant pages before the peak(s): Let’s say you already have a “wet season preparation guide” or perhaps even an ecommerce page selling umbrellas. ![]() After all, this is when your potential customers are most likely to be searching for such information. Create relevant content to coincide with the peak: For example, if you live in Australia and sell umbrellas, it may make sense to put together a “wet season preparation guide” and publish it in December.You can then put this data to use in two ways: So if your business is season-dependent, you can quickly estimate its peaks and bottoms by analyzing the relevant search queries in Google Trends. These are the months when the rainy season begins in these countries, and people realize they don’t want to get wet. You can see that the query “umbrella” is the most popular in the US in June while in Australia the peak falls in December. You probably realize that search volumes for some keywords are affected by seasonality.įor example, take a look at the Google Trends data for the keyword “umbrella” in the US. Identify seasonal trends, then create (and promote) content at the RIGHT time! Now let me show you how you can (and should) use Google Trends in your online marketing activities and during keyword research in particular. This is despite the fact that Keywords Explorer shows the search volume trend, whereas Google Trends shows the “popularity” trend (as outlined above). But in most cases, it does.įor example, if you take the keyword “Star Wars,” you’ll notice that the same spike (December 2015) appears in Google Trends and Ahrefs Keywords Explorer. 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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