This workflow automates scraping Google Trends data and saving it to Google Sheets, ideal for marketing and SEO analytics.
Scrape Google Trends
Scraping Google Trends involves extracting data from Google's platform, which showcases the popularity of search queries over time. This can be valuable for various professionals, including marketers and SEO specialists, to understand search trends, compare keyword popularity, and derive insights for content strategy. While Google Trends does not offer an official API for public use, there are ways to programmatically access this data.
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How to Scrape Google Trends Data
To manually scrape Google Trends data, one could use Python scripting with libraries like 'httpx' for sending requests and 'pandas' for handling data. This method involves identifying API requests made by the Google Trends website to fetch JSON data related to search terms, geographical locations, and time ranges. However, this approach requires a good understanding of programming and might be subject to Google's data use policies.
Google Trends in Google Sheets
For those looking to integrate Google Trends data directly into Google Sheets without extensive coding, tools like Two Minute Reports offer a more accessible solution. This tool allows users to connect Google Trends to Google Sheets, enabling the extraction of daily search trends, interests by time or region, and related queries or topics. Users can schedule automatic data refreshes, making it easier to keep track of trends over time.
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Another innovative approach involves using a Google Sheets template combined with a Python script that runs in Google Colab. This method allows users to specify their search criteria directly in a Google Sheet, and the script fetches the data from Google Trends, populating the sheet with results. This method is particularly useful for handling large numbers of queries and offers a balance between manual and fully automated solutions.