Information about discrepancies in Google Trends

You might have noticed that sometimes, when you get data from Google Trends in really detailed ways, like by looking at results for each day, the numbers you get can sometimes be quite different than the numbers of the Google Trends console.

This discrepancies are due to the way Google Trends API operates. Google Trends API works extracting random segments from the total of Google's search volume. This approach speeds up data processing on Google's servers, but it also could introduce potential discrepancies between successive queries. Each query may come from a different random sample, resulting in the observed differences.

After processing this sampled data, the Google trends API sends it directly to Dataslayer. That is the reason why, as the Google Trends API and the Google trends console are different products with a different way of handling the data, they can present differences depending on the query and its characteristics.

Is there a way to reduce these discrepancies?

It is difficult to completely eliminate these inconsistencies due to the randomness involved in the Google Trends data extraction. However, there is a way to minimize the impact of these variations.

An effective solution is to optimize the date ranges used in queries. Rather than focusing on very short intervals, consider extending the time frame to cover periods from 1 week on. This approach has the potential to provide a more stable and aligned set of results, possibly reducing the discrepancies that can be caused by Google Trends API random sampling.

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Updated on: 01/09/2023