Google data search exercises can be used to practice finding data or statistics on a topic of interest, including using Google's own internal tools and by using advanced operators.

United States Google Search Trends: Government Measures: Government Subsidy data was reported at 0.000 Score in 14 May 2025. This stayed constant from the previous number of 0.000 Score for 13 May 2025. United States Google Search Trends: Government Measures: Government Subsidy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 0.000 Score in 14 May 2025 and a record low of 0.000 Score in 14 May 2025. United States Google Search Trends: Government Measures: Government Subsidy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s United States – Table US.Google.GT: Google Search Trends: by Categories.

OpenWeb Ninja's Google Images Data (Google SERP Data) API provides real-time image search capabilities for images sourced from all public sources on the web.

The API enables you to search and access more than 100 billion images from across the web including advanced filtering capabilities as supported by Google Advanced Image Search. The API provides Google Images Data (Google SERP Data) including details such as image URL, title, size information, thumbnail, source information, and more data points. The API supports advanced filtering and options such as file type, image color, usage rights, creation time, and more. In addition, any Advanced Google Search operators can be used with the API.

OpenWeb Ninja's Google Images Data & Google SERP Data API common use cases:

• Creative Media Production: Enhance digital content with a vast array of real-time images, ensuring engaging and brand-aligned visuals for blogs, social media, and advertising.

• AI Model Enhancement: Train and refine AI models with diverse, annotated images, improving object recognition and image classification accuracy.

• Trend Analysis: Identify emerging market trends and consumer preferences through real-time visual data, enabling proactive business decisions.

• Innovative Product Design: Inspire product innovation by exploring current design trends and competitor products, ensuring market-relevant offerings.

• Advanced Search Optimization: Improve search engines and applications with enriched image datasets, providing users with accurate, relevant, and visually appealing search results.

OpenWeb Ninja's Annotated Imagery Data & Google SERP Data Stats & Capabilities:

• 100B+ Images: Access an extensive database of over 100 billion images.

• Images Data from all Public Sources (Google SERP Data): Benefit from a comprehensive aggregation of image data from various public websites, ensuring a wide range of sources and perspectives.

• Extensive Search and Filtering Capabilities: Utilize advanced search operators and filters to refine image searches by file type, color, usage rights, creation time, and more, making it easy to find exactly what you need.

• Rich Data Points: Each image comes with more than 10 data points, including URL, title (annotation), size information, thumbnail, and source information, providing a detailed context for each image.

The International Google Trends dataset will provide critical signals that individual users and businesses alike can leverage to make better data-driven decisions. This dataset simplifies the manual interaction with the existing Google Trends UI by automating and exposing anonymized, aggregated, and indexed search data in BigQuery. This dataset includes the Top 25 stories and Top 25 Rising queries from Google Trends. It will be made available as two separate BigQuery tables, with a set of new top terms appended daily. Each set of Top 25 and Top 25 rising expires after 30 days, and will be accompanied by a rolling five-year window of historical data for each country and region across the globe, where data is available. This Google dataset is hosted in Google BigQuery as part of Google Cloud's Datasets solution and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery

The COVID-19 Search Trends symptoms dataset shows aggregated, anonymized trends in Google searches for a broad set of health symptoms, signs, and conditions. The dataset provides a daily or weekly time series for each region showing the relative volume of searches for each symptom. This dataset is intended to help researchers to better understand the impact of COVID-19. It shouldn't be used for medical diagnostic, prognostic, or treatment purposes. It also isn't intended to be used for guidance on personal travel plans. To learn more about the dataset, how we generate it and preserve privacy, read the data documentation . To visualize the data, try exploring these interactive charts and map of symptom search trends . As of Dec. 15, 2020, the dataset was expanded to include trends for Australia, Ireland, New Zealand, Singapore, and the United Kingdom. This expanded data is available in new tables that provide data at country and two subregional levels. We will not be updating existing state/county tables going forward. All bytes processed in queries against this dataset will be zeroed out, making this part of the query free. Data joined with the dataset will be billed at the normal rate to prevent abuse. After September 15, queries over these datasets will revert to the normal billing rate. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Google Search Trends: Online Games: Call of Duty data was reported at 0.000 Score in 15 May 2025. This stayed constant from the previous number of 0.000 Score for 14 May 2025. Google Search Trends: Online Games: Call of Duty data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 15 May 2025, with 1262 observations. The data reached an all-time high of 83.000 Score in 28 Jun 2022 and a record low of 0.000 Score in 15 May 2025. Google Search Trends: Online Games: Call of Duty data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Costa Rica – Table CR.Google.GT: Google Search Trends: by Categories.

Google Search Trends: Online Shopping: Wayfair data was reported at 0.000 Score in 14 May 2025. This stayed constant from the previous number of 0.000 Score for 13 May 2025. Google Search Trends: Online Shopping: Wayfair data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 4.000 Score in 18 Jan 2022 and a record low of 0.000 Score in 14 May 2025. Google Search Trends: Online Shopping: Wayfair data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Costa Rica – Table CR.Google.GT: Google Search Trends: by Categories.

China Google Search Trends: Online Shopping: Tmall data was reported at 8.000 Score in 14 May 2025. This stayed constant from the previous number of 8.000 Score for 13 May 2025. China Google Search Trends: Online Shopping: Tmall data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 70.000 Score in 22 Jan 2023 and a record low of 0.000 Score in 02 May 2025. China Google Search Trends: Online Shopping: Tmall data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s China – Table CN.Google.GT: Google Search Trends: by Categories.

You can check the fields description in the documentation: current Keyword database: https://docs.dataforseo.com/v3/databases/google/keywords/?bash; Historical Keyword database: https://docs.dataforseo.com/v3/databases/google/history/keywords/?bash. You don’t have to download fresh data dumps in JSON or CSV – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

You can check the fields description in the documentation: current Full database: https://docs.dataforseo.com/v3/databases/google/full/?bash; Historical Full database: https://docs.dataforseo.com/v3/databases/google/history/full/?bash.

Full Google Database is a combination of the Advanced Google SERP Database and Google Keyword Database.

Google SERP Database offers millions of SERPs collected in 67 regions with most of Google’s advanced SERP features, including featured snippets, knowledge graphs, people also ask sections, top stories, and more.

Google Keyword Database encompasses billions of search terms enriched with related Google Ads data: search volume trends, CPC, competition, and more.

This database is available in JSON format only.

You don’t have to download fresh data dumps in JSON – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

As of March 2025, Google represented 79.1 percent of the global online search engine market on desktop devices. Despite being much ahead of its competitors, this represents the lowest share ever recorded by the search engine in these devices for over two decades. Meanwhile, its long-time competitor Bing accounted for 12.21 percent, as tools like Yahoo and Yandex held shares of over 2.9 percent each. Google and the global search market Ever since the introduction of Google Search in 1997, the company has dominated the search engine market, while the shares of all other tools has been rather lopsided. The majority of Google revenues are generated through advertising. Its parent corporation, Alphabet, was one of the biggest internet companies worldwide as of 2024, with a market capitalization of 2.02 trillion U.S. dollars. The company has also expanded its services to mail, productivity tools, enterprise products, mobile devices, and other ventures. As a result, Google earned one of the highest tech company revenues in 2024 with roughly 348.16 billion U.S. dollars. Search engine usage in different countries Google is the most frequently used search engine worldwide. But in some countries, its alternatives are leading or competing with it to some extent. As of the last quarter of 2023, more than 63 percent of internet users in Russia used Yandex, whereas Google users represented little over 33 percent. Meanwhile, Baidu was the most used search engine in China, despite a strong decrease in the percentage of internet users in the country accessing it. In other countries, like Japan and Mexico, people tend to use Yahoo along with Google. By the end of 2024, nearly half of the respondents in Japan said that they had used Yahoo in the past four weeks. In the same year, over 21 percent of users in Mexico said they used Yahoo.

Eritrea Google Search Trends: Computer & Electronics: Apple data was reported at 0.000 Score in 15 May 2025. This stayed constant from the previous number of 0.000 Score for 14 May 2025. Eritrea Google Search Trends: Computer & Electronics: Apple data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 15 May 2025, with 1262 observations. The data reached an all-time high of 100.000 Score in 19 Apr 2025 and a record low of 0.000 Score in 15 May 2025. Eritrea Google Search Trends: Computer & Electronics: Apple data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Eritrea – Table ER.Google.GT: Google Search Trends: by Categories.

DataForSEO Labs API offers three powerful keyword research algorithms and historical keyword data:

• Related Keywords from the “searches related to” element of Google SERP. • Keyword Suggestions that match the specified seed keyword with additional words before, after, or within the seed key phrase. • Keyword Ideas that fall into the same category as specified seed keywords. • Historical Search Volume with current cost-per-click, and competition values.

Based on in-market categories of Google Ads, you can get keyword ideas from the relevant Categories For Domain and discover relevant Keywords For Categories. You can also obtain Top Google Searches with AdWords and Bing Ads metrics, product categories, and Google SERP data.

You will find well-rounded ways to scout the competitors:

• Domain Whois Overview with ranking and traffic info from organic and paid search. • Ranked Keywords that any domain or URL has positions for in SERP. • SERP Competitors and the rankings they hold for the keywords you specify. • Competitors Domain with a full overview of its rankings and traffic from organic and paid search. • Domain Intersection keywords for which both specified domains rank within the same SERPs. • Subdomains for the target domain you specify along with the ranking distribution across organic and paid search. • Relevant Pages of the specified domain with rankings and traffic data. • Domain Rank Overview with ranking and traffic data from organic and paid search. • Historical Rank Overview with historical data on rankings and traffic of the specified domain from organic and paid search. • Page Intersection keywords for which the specified pages rank within the same SERP.

All DataForSEO Labs API endpoints function in the Live mode. This means you will be provided with the results in response right after sending the necessary parameters with a POST request.

The limit is 2000 API calls per minute, however, you can contact our support team if your project requires higher rates.

We offer well-rounded API documentation, GUI for API usage control, comprehensive client libraries for different programming languages, free sandbox API testing, ad hoc integration, and deployment support.

We have a pay-as-you-go pricing model. You simply add funds to your account and use them to get data. The account balance doesn't expire.

Google Search Trends: Computer & Electronics: Apple data was reported at 30.000 Score in 14 May 2025. This records a decrease from the previous number of 33.000 Score for 13 May 2025. Google Search Trends: Computer & Electronics: Apple data is updated daily, averaging 33.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 100.000 Score in 09 Sep 2024 and a record low of 0.000 Score in 22 Jun 2023. Google Search Trends: Computer & Electronics: Apple data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Bulgaria – Table BG.Google.GT: Google Search Trends: by Categories.

This dataset contains a collection of around 2,000 HTML pages: these web pages contain the search results obtained in return to queries for different products, searched by a set of synthetic users surfing Google Shopping (US version) from different locations, in July, 2016.

Each file in the collection has a name where there is indicated the location from where the search has been done, the userID, and the searched product: no_email_LOCATION_USERID.PRODUCT.shopping_testing.#.html

The locations are Philippines (PHI), United States (US), India (IN). The userIDs: 26 to 30 for users searching from Philippines, 1 to 5 from US, 11 to 15 from India.

Products have been choice following 130 keywords (e.g., MP3 player, MP4 Watch, Personal organizer, Television, etc.).

In the following, we describe how the search results have been collected.

Each user has a fresh profile. The creation of a new profile corresponds to launch a new, isolated, web browser client instance and open the Google Shopping US web page.

To mimic real users, the synthetic users can browse, scroll pages, stay on a page, and click on links.

A fully-fledged web browser is used to get the correct desktop version of the website under investigation. This is because websites could be designed to behave according to user agents, as witnessed by the differences between the mobile and desktop versions of the same website.

The prices are the retail ones displayed by Google Shopping in US dollars (thus, excluding shipping fees).

Several frameworks have been proposed for interacting with web browsers and analysing results from search engines. This research adopts OpenWPM. OpenWPM is automatised with Selenium to efficiently create and manage different users with isolated Firefox and Chrome client instances, each of them with their own associated cookies.

The experiments run, on average, 24 hours. In each of them, the software runs on our local server, but the browser's traffic is redirected to the designated remote servers (i.e., to India), via tunneling in SOCKS proxies. This way, all commands are simultaneously distributed over all proxies. The experiments adopt the Mozilla Firefox browser (version 45.0) for the web browsing tasks and run under Ubuntu 14.04. Also, for each query, we consider the first page of results, counting 40 products. Among them, the focus of the experiments is mostly on the top 10 and top 3 results.

Due to connection errors, one of the Philippine profiles have no associated results. Also, for Philippines, a few keywords did not lead to any results: videocassette recorders, totes, umbrellas. Similarly, for US, no results were for totes and umbrellas.

The search results have been analyzed in order to check if there were evidence of price steering, based on users' location.

One term of usage applies:

In any research product whose findings are based on this dataset, please cite

@inproceedings{DBLP:conf/ircdl/CozzaHPN19, author = {Vittoria Cozza and Van Tien Hoang and Marinella Petrocchi and Rocco {De Nicola}}, title = {Transparency in Keyword Faceted Search: An Investigation on Google Shopping}, booktitle = {Digital Libraries: Supporting Open Science - 15th Italian Research Conference on Digital Libraries, {IRCDL} 2019, Pisa, Italy, January 31 - February 1, 2019, Proceedings}, pages = {29--43}, year = {2019}, crossref = {DBLP:conf/ircdl/2019}, url = {https://doi.org/10.1007/978-3-030-11226-4_3}, doi = {10.1007/978-3-030-11226-4_3}, timestamp = {Fri, 18 Jan 2019 23:22:50 +0100}, biburl = {https://dblp.org/rec/bib/conf/ircdl/CozzaHPN19}, bibsource = {dblp computer science bibliography, https://dblp.org} }

Moldova Google Search Trends: Online Training: Udemy data was reported at 4.000 Score in 15 May 2025. This records a decrease from the previous number of 7.000 Score for 14 May 2025. Moldova Google Search Trends: Online Training: Udemy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 15 May 2025, with 1262 observations. The data reached an all-time high of 100.000 Score in 15 Oct 2022 and a record low of 0.000 Score in 06 May 2025. Moldova Google Search Trends: Online Training: Udemy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Moldova – Table MD.Google.GT: Google Search Trends: by Categories.

Google Search Trends: Travel & Accommodations: American Airlines data was reported at 1.000 Score in 14 May 2025. This stayed constant from the previous number of 1.000 Score for 13 May 2025. Google Search Trends: Travel & Accommodations: American Airlines data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 19.000 Score in 02 Nov 2022 and a record low of 0.000 Score in 03 May 2025. Google Search Trends: Travel & Accommodations: American Airlines data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s China – Table CN.Google.GT: Google Search Trends: by Categories.

Google Search Trends: Online Shopping: Walmart data was reported at 0.000 Score in 14 May 2025. This stayed constant from the previous number of 0.000 Score for 13 May 2025. Google Search Trends: Online Shopping: Walmart data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 3.000 Score in 21 Apr 2023 and a record low of 0.000 Score in 14 May 2025. Google Search Trends: Online Shopping: Walmart data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Spain – Table ES.Google.GT: Google Search Trends: by Categories.

Google Search Trends: Economic Measures: Mortgage Loan data was reported at 10.000 Score in 14 May 2025. This records a decrease from the previous number of 12.000 Score for 13 May 2025. Google Search Trends: Economic Measures: Mortgage Loan data is updated daily, averaging 10.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 47.000 Score in 21 Apr 2023 and a record low of 0.000 Score in 14 Feb 2023. Google Search Trends: Economic Measures: Mortgage Loan data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Spain – Table ES.Google.GT: Google Search Trends: by Categories.

Google Search Trends: Computer & Electronics: Apple data was reported at 25.000 Score in 15 May 2025. This stayed constant from the previous number of 25.000 Score for 14 May 2025. Google Search Trends: Computer & Electronics: Apple data is updated daily, averaging 27.000 Score from Dec 2021 (Median) to 15 May 2025, with 1262 observations. The data reached an all-time high of 100.000 Score in 10 Sep 2024 and a record low of 0.000 Score in 08 Apr 2023. Google Search Trends: Computer & Electronics: Apple data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Taiwan – Table TW.Google.GT: Google Search Trends: by Categories.