Understanding the Algorithm Behind DataForSEO Trends API

DataForSEO Trends API employs our proprietary algorithm to supply you with the keyword popularity rate over time and for the specified location(s). The DataForSEO Trends Tool, built on top of the DataForSEO Trends API, naturally has the same algorithm at its core.

So, let’s dive into the algorithm behind our tool and API to find out how it works.

Data Collection

We collect data from web pages, search engine results, news articles, shopping listings, and other relevant sources to provide a comprehensive keyword popularity overview. We also combine this information with anonymous user web behavior data from various sources, such as browsing patterns and the search terms used. This data is fed to our machine learning algorithm and allows it to predict searchers’ gender, age, and approximate regional location. It’s essential to note that we use only aggregated anonymized data which makes it impossible to identify individual users.

To ensure accurate results and avoid misinterpretation, certain data is excluded from the DataForSEO Trends, such as searches made by very few people, duplicate searches, and searches containing special characters.

How Our Algorithm Works

Our algorithm provides insights into the popularity of specific keywords based on their association with relevant web pages, news articles, or shopping listings, as well as the popularity of each relevant piece of content based on factors such as search ranking, page views, and engagement metrics.

Here’s a more detailed overview of how it works.

First, our algorithm uses keyword matching and semantic analysis to identify web pages, news articles, or shopping listings that are directly relevant to the specified target keywords and for the selected types of Trends (web, news, or shopping).

Next, the algorithm evaluates the popularity of each relevant piece of content based on its search ranking, page views, engagement metrics, and other data. The scores of content popularity are normalized and scaled to a standardized range, from 0 to 100.

To calculate the popularity of a keyword across the Internet, the algorithm aggregates the popularity scores of all relevant content associated with that keyword.

To estimate keyword popularity at specific timestamps and track changes over time, the algorithm considers the timestamp of each data point and the temporal dimension of anonymous interactions with relevant web content.

To assess keyword popularity in different regions or countries, the algorithm blends content popularity data with anonymous approximate location data of users that interact with that content. Following the same logic, the algorithm estimates the demographic breakdown of keyword popularity.

It’s important to note that our algorithm uses normalized keyword popularity data, which means it is put on a relative scale from 0 to 100. The normalization process helps to standardize the data, making it easier to interpret and visualize keyword popularity trends.

Overall, by analyzing a vast variety of factors, our algorithm offers a nuanced understanding of a keyword’s popularity on the web. This allows us to provide valuable insights neatly visualized in the DataForSEO Trends Tool and accessible via our robust and reliable API.

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