'*******' was the most searched keyword on Google in the United States between January and March 2025, with an average monthly volume of ****** million searches over the researched period. "***" ranked second with a search volume of ***** million searches. The keyword for "nfl" came in third, making up to ***** million searches.

"*******" was the most frequently searched keyword on Google worldwide, with over ***** million monthly online searches during the analyzed period of January to March in 2025. Furthermore, the search resulted in more than ***** million website visits, or more than **** percent of all traffic. With *** million monthly searches, "***" was the second most popular keyword, and "***********" came in third place with about ****** million searches per month.

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.

Between January and March 2021, the most searched questions or "how-to" Google keywords on YouTube.com concerned products offered by the platform, or different ways to interact with the platform content. The question "how to download youtube videos" had an average number of monthly searches close to 127 thousand times. Users were also interested in receiving more information on YouTube's own television service, with 38.5 thousand searches of a specific question on the cost of YouTube TV.

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.

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.

A dataset of fashion keywords, including their definitions, synonyms, antonyms, search volume and costs.

This represents the top 10 searches that visitors have conducted on via Google Search. The data represents the most recent one-month period. *Note: On July 1, 2023, standard Universal Analytics properties will stop processing data.

Between January and March 2021, the most searched Google keyword on YouTube.com was "youtube," with close to *** million average monthly searches. The second leading keyword was "youtube to mp3," which is usually used by people to look for software to download music as mp3 files from videos hosted on the platform. Users also tried to reach YouTube TV, a live and on-demand video streaming service available in the United States, with the query "youtube tv" amassing almost *** million average monthly searches in the examined period.

In Qatar, the top google search query was Qatar in 2022. World cup was the second most googled term in Qatar in the same period.

Dataset

This dataset was created by Gamze Akkurt

Contents

The most searched keywords on Google Shopping by French Internet users throughout the year 2020 are represented in this statistic. That year, Nike was the top query searched on Google Shopping, followed by the keyword "Amazon" with an index of 84, meaning that this last query received 84 percent of the search volume of "Nike". "Samsung" came in third with and index of 57 and "Chaussure" (meaning shoe) occupied the fourth spot with an index of 43 out of 100.

As of February 2022, it appeared that mobile apps spotting specific target keywords in the titles ranked higher in the Google Play Store results page after a user prompt research. According to industry sources, while it is not clear what allows certain apps to appear among the first results on the Apple App Store results page, app store optimization practices can help developers increase their app visibility and users' interactions.

"Traduction" and "Google" were the most popular Google search queries in Tunisia in 2023. The following leading online search on Google was "Google Traduction", which obtained an index of ** points compared to 100 for the most popular term. Other popular search queries were "Facebook", "YouTube", and "Meteo".

These are the top trending "How to" searches on Google, ranked by their spike value. Trending searches are searches with the biggest increase in search interest since the previous time period. Data covers the past 5 years.

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} }

Google Search Trends: Computer & Electronics: Samsung Electronics data was reported at 59.000 Score in 15 May 2025. This records a decrease from the previous number of 67.000 Score for 14 May 2025. Google Search Trends: Computer & Electronics: Samsung Electronics data is updated daily, averaging 55.500 Score from Dec 2021 (Median) to 15 May 2025, with 1262 observations. The data reached an all-time high of 100.000 Score in 23 Dec 2023 and a record low of 0.000 Score in 02 Jul 2023. Google Search Trends: Computer & Electronics: Samsung Electronics data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Sri Lanka – Table LK.Google.GT: Google Search Trends: by Categories.

Research datasets about top signals for covid 19 (coronavirus) for study into Google Trends (GT) and with SEO metrics

Website

The study is currently published on https://covidgilance.org website (in french)

Datasets description

covid signals -> |selection| -> 4 dataset -> |serp.py| -> 4 serp datasets -> |aggregate_serp.pl| -> 4 aggregated dataset of serp -> |prepare datasets| -> 4 ranked top seo dataset

Original lists of signals (mainly covid symptoms) - dataset

Description: contain the original relevant list of signals for covid19 (here list of queries where you can see, in GT, a relevant signal during the covid 19 period of time)
Name: covid_signal_list.tsv

List of content:

- id: unique id for the topic
- topic-fr: name of the topic in French
- topic-en: name of the topic in English
- topic-id: GT topic id
- keyword fr: one or several keywords in French for GT
- keyword en: one or several keywords in English for GT
- fr-topic-url-12M: link to 12-months French query topic in GT in France
- en-topic-url-12M: link to 12-months English query topic in GT in US
- fr-url-12M: link to 12-months French queries in GT in France
- en-url-12M: link to 12-months English queries topic in GT in US
- fr-topic-url-5M: link to 5-months French query topic in GT in France
- en-topic-url-5M: link to 5-months English query topic in GT in US
- fr-url-5M: link to 5-months French queries in GT in France
- en-url-5M: link to 5-months English queries topic in GT in US

Tool to get SERP of covid signals - tool

Description: query google with a list of covid signals and obtain a list of serps in csv (tsv in fact) file format
Name: serper.py

python serper.py

SERP files - datasets

Description Serp results for 4 datesets of queries Names: simple version of covid signals from google.ch in French: serp_signals_20_ch_fr.csv
simple version of covid signals from google.com in English: serp_signals_20_en.csv
amplified version of covid signals from google.ch in French: serp_signals_covid_20_ch_fr.csv
amplified version of covid signals from google.com in English: serp_signals_covid_20_en.csv

amplified version means that for each query we create two queries one with the keywords "covid" and one with "coronavirus"

Tool to aggregate SERP results - tool

Description: load csv serp data and aggregate the data to create a new csv file where each line is a website and each column is a query. Name: aggregate_serp.pl

`perl aggregate_serp.pl> aggregated_signals_20_en.csv

datasets of top website from the SERP results - dataset

Description a aggregated version of the SERP where each line is a website and each column a query
Names:
aggregated_signals_20_ch_fr.csv
aggregated_signals_20_en.csv
aggregated_signals_covid_20_ch_fr.csv
aggregated_signals_covid_20_en.csv

List of content:

- domain: domain name of the website
- signal 1: Position of the query 1 (signal 1) in the SERP where 30 indicates arbitrary that this website is not present in the SERP
- signal ...: Position of the query (signal) in the SERP where 30 indicates arbitrary that this website is not present in the SERP
- signal n: Position of the query n (signal n) in the SERP where 30 indicates arbitrary that this website is not present in the SERP
- total: average position (total of all position /divided by the number of queries)
- missing: Total number of missing results in the SERP for this website

datasets ranked top seo - dataset

Description a ranked (by weighted average position) version of the aggregated version of the SERP where each line is a website and each column a query. TOP 20 have more information about the type and HONcode validity (from the date of collect: September 2020)

Names:
ranked_signals_20_ch_fr.csv
ranked_signals_20_en.csv
ranked_signals_covid_20_ch_fr.csv
ranked_signals_covid_20_en.csv

List of content:

- domain: domain name of the website
- signal 1: Position of the query 1 (signal 1) in the SERP where 30 indicates arbitrary that this website is not present in the SERP
- signal ...: Position of the query (signal) in the SERP where 30 indicates arbitrary that this website is not present in the SERP
- signal n: Position of the query n (signal n) in the SERP where 30 indicates arbitrary that this website is not present in the SERP
- avg position: average position (total of all position /divided by the number of queries)
- nb missing: Total number of missing results in the SERP for this website
- % presence: % of presence
- weighted avg postion: combination of avg position and % of presence for final ranking
- honcode: status of the Honcode certificate for this website (none/valid/expired)
- type: type of the website (health, gov, edu or media)

"Meteo", "Google", and "Traduction" were the most entered queries in the Google search engine in France in 2024, with index ratings of ***, **, and **, respectively. These were followed by "Météo" and "YouTube", scoring ** and ** index points relative to the most searched query.

A dataset of web design keywords, including their definitions, synonyms, antonyms, search volume and costs.