"Squid Game" was the keyword that had the highest maximum monthly search volume in 2021, with 101 million online searches worldwide in its peak month. The second most trending keyword based on its peak search volume was "Christian Eriksen." Eriksen is a Danish football player who experienced cardiac arrest during the Euro 2020 Denmark against Finland match, on June 12, 2021. Another popular keyword search on Google was Queen Elisabeth's late husband "Prince Phillip," with a peak of 37.2 million searches. Another popular topic related to the British royal family was Prince Harry and Meghan Markle's interview with Oprah Winfrey in March 2021. This was the first big interview after the couple decided to step back as senior royals, and queries on the topic went up to 1.2 million searches on Google in 2021.

In 2023, "weather" was the most searched keyword on Google in the United States, with almost 82.62 million online searches monthly. "youtube" ranked second with an average of 71.3 million searches per month. The video platform generated nearly 582.7 million searches annually, of which over 99 percent were organic. The keyword for "amazon" came in third with over 56 million monthly searches, while "facebook" was the fourth-most popular keyword searched on Google, with over 54 million monthly searches.

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.

"VG" was the most entered query into the Google search engine by internet users in Norway in 2023, which had an index value of 100. Next in the ranking was "Google" which had an index score of 72, and it was followed by "Translate", with an index value of 58 in the examined year.

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.

In 2024, "YouTube" was the most searched keyword on Google, with over 346 million monthly online searches. In addition, over 99 percent of its traffic was organic. The second most popular keyword was "facebook", with 228 million monthly searches. "Amazon" ranked third with approximately 163.94 million searches monthly. Additionally, the keyword "translate" ranked fourth, with around 141.5 million searches monthly.

As of June 2024, global Google searches for the word "ChatGPT" increased again after a slight decline by the end of 2024. Interest in the chatbot, developed by the U.S.-based OpenAI and launched in November 2022, started rising in the week ending December 3, 2022. Recently, growing demand for information on ChatGPT made the keyword hit a peak of 100 index points during the week ending on June 2, 2024. ChatGPT, which stands for Chat Generative Pre-trained Transformer, is a chatbot and AI-powered auto-generative text system able to give human-sounding replies and reproduce human-like interactions when prompted.

Analysis of ‘TPS - Jan22 | Google Trends Kaggle search DataSet’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ankitkalauni/tps-jan22-google-trends-kaggle-search-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

"Kaggle" keyword web search (WorldWide) dataset from the google trends. I am not sure if this is going to help. I searched for Finland, Sweden, and Norway but the data is not enough.

--- Original source retains full ownership of the source dataset ---

In 2023, the most common terms that Hong Kong internet users entered into Google search were "Hong Kong (in Chinese)", Google", "translate", and "YouTube". The word "weather" in Chinese received 25 percent of the search volume of the top query during 2023.

In 2020, many brand new trends were searched online for the first time. The most popular new search term worldwide typed to the Google search bar for the first time ever in 2020 was "my2020census gov". During the measured period, the search query generated a maximum monthly search volume of 13.6 million searches.

Data collection of search data retrieved from Google Trends for brands of car manufacturers and their car brands as well as data for the brands of listed companies active in Europe. Data were retrieved using R code for a list of keywords of interest.

The aim of this project was to investigate whether data from Google Trends could be used to value brands. Currently brand valuation methods are highly complex and results are generally not available for many brands and are not comparable across brands. We downloaded Google Trends data for brands in the automotive sector and for the brands of listed companies. The data were then joined to other data about the firms and brands we collected from public sources. Analysis of this data showed that Google Trends data provides a good measure of changes to brand value for well established brands with national or global reach in the automotive sector. The data capture changes in brand value that are the result of exogeous shocks, e.g. as a result of product recalls. Google Trends data also contain information about variation in stock market value of listed companies that is not contained in data released through firms' quarterly and annual reports or in other publicly available data on intellectual property rights and citations of these rights.

The Google Trends data was complemented by data on car registrations and characteristics from various sources and data on various shocks affecting the car industry. These are not included in this dataset.

Brands are names, phrases, symbols or designs that identify particular products, which are often protected by trade marks. Trade marks help owners protect their reputation by forbidding use of their brand name by others.

Trade marks are usually registered, but not all registered marks are used. Much litigation arises over the extent of use and reputation of marks, which often results in costly surveys being run with data from trade mark registers and data from Google's search products. Data from Google's search products can be used to measure value and use of marks. In using these data, two important challenges must be overcome: heterogeneity of the data and attempts to manipulate the measures obtained. Both challenges will be addressed in the project.

The aim of this project was to improve the measurement of brand value and the measurement of trade mark use by combining data obtained from trade mark registers and data from Google's search products (Google Search, Google Trends and Google Insights for Search).

Data on search are heterogeneous because the reasons for searches are heterogeneous, they may reflect positive or negative brand interest. Additionally, attempts to manipulate Google's rankings of websites though the PageRank link analysis algorithm are legion. To overcome both problems we will consider ways of limiting search terms to obtain consistent measures of value from Google's search products.

Google Search Trends: Travel & Accommodations: Lufthansa data was reported at 1.000 Score in 21 Mar 2025. This stayed constant from the previous number of 1.000 Score for 20 Mar 2025. Google Search Trends: Travel & Accommodations: Lufthansa data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 21 Mar 2025, with 1207 observations. The data reached an all-time high of 22.000 Score in 16 Oct 2022 and a record low of 0.000 Score in 09 Mar 2025. Google Search Trends: Travel & Accommodations: Lufthansa 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.

"Iceland" and "Google" were the most googled terms in Iceland in 2023. The terms had a search engine index of 100 and 72 respectively. The third most common term was "translate," with an index of 68. Among other popular search terms were "Reykjavik", "MBL" and "Visir".

Significant cross-correlation coefficients of individual and averaged time-series data.

Statistics results of Baidu index and Google trends on keywords related to the epidemic from January 10 to February 28

The dataset contains:

1) The list of tweets corresponding to the keywords "heat wave india" and "heatwave india" between 2010 and 2017.

2) The daily count of the same tweets

3) The monthly Google Trends data corresponding to the keywords "heat wave", "heatwave", "heat wave india", and "heatwave india" limited to the searches from India in the period 2010-2017

The Twitter data has been obtained wth the Python package Get-Old-Tweets (https://github.com/Jefferson-Henrique/GetOldTweets-python); the Google Trends data are obtained from the Google Trends webpage (https://trends.google.com/trends/?geo=US).

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

As of February 2025, several search terms were googled especially actively by German internet users. Among these, the leading three were ‘handball wm’ (handball championship), ‘australian open 2025’ and ‘handball wm 2025’. The terms reflect events, certain dates and ensuing media coverage taking place at the time, in this case about the handball championship and the Australian Open tennis tournament. Always searching Daily life seems unthinkable without using an online search engine, whether for longer research or quickly checking something, or even just to avoid setting bookmarks, typing in URLs. Google has by far the highest share among online search engines used on desktop and mobile devices at almost 90 percent of searches done on Google, followed by Bing and Ecosia. While DuckDuckGo was further down on the list, its market share has been rising in Germany. Google may still have a substantial head start compared to its competitors, but users are increasingly apprehensive about data privacy and protection in connection with how the online search giant uses and stores personal information, as well as tracks search queries. Searching for Trees Ecosia is an environmentally friendly search engine with a unique business model that sets it apart from other search engines. It uses the revenue from search ads to plant trees worldwide and support reforestation projects. Every time a user performs a search on Ecosia, they indirectly contribute to reforestation, as one tree is planted for every 45 searches.The search engine market share held by Ecosia has been growing in recent years, especially in Germany where the company is based, and in other countries in Europe. Ecosia, similarly to other alternative search engines (e.g. DuckDuckGo), uses Bing to power its results.

Abstract

Background. The search digital footprint, such as in Google Trend (GT), forms a large dataset that is suitable to be used as surveillance data and supports early warning systems. These advantages become great opportunities for disease surveillance agencies in Indonesia to get rapid early disease monitoring. Objective. Due to limited research in this area and the increasing level of internet penetration in Indonesia, a further study is needed in disease monitoring by utilizing Google Trends. In this research, we explore, analyze and create a set of the best search terms to be used in utilizing GT for disease surveillance in Indonesia, especially Tuberculosis. Method. We use correlation as the technique to define the relatedness between the real case data and GT results. We collect data from the Ministry of Health of Indonesia. From the data, we design a set of new search terms to take GT trend data. The collected data is analyzed using the Pearson correlation. Result. The analysis shows that the studied search terms give strong positive relationships between GT trend data and Tuberculosis cases number in Indonesia. From the correlation analysis, we get a set of proposed effective search terms with the highest score equals to 0.907. Conclusion. Finally, it is possible to monitor and make quick surveillance in tuberculosis in Indonesia through Google Trend and we have created a novel set of search terms that can be used as the basis in monitoring other diseases in Indonesia.

Jurnal : Fudholi, D., & Fikri, K. (2020). Towards an Effective Tuberculosis Surveillance in Indonesia through Google Trends. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 5(4). doi: https://doi.org/10.22219/kinetik.v5i4.1114

Number of nowcasting and forecasting models selected in the MCS at the 90% confidence level, using the statistic and the MSE loss function, as well as number of selected Google based models.