In the first half of 2022, page views of mainstream newspaper and magazine websites in Brazil peaked in June. That month, news sites audited by the source reported over *** million page views, of which more than two-thirds (*** million) were generated via smartphones. 2022 was the first year mobile phones accounted for most of the web traffic in Brazil.

For more information on CDC.gov metrics please see http://www.cdc.gov/metrics/

Cars.com is a U.S.- based automotive classifieds website which recorded nearly ** million average monthly unique visitors from the start of 2019 to June 30th, 2019. In the same period of 2023, average monthly unique visitors to the site raised to **** million.

In November 2024, Google.com was the most popular website worldwide with approximately 6.25 billion unique monthly visitors. YouTube.com was ranked second with an estimated 3.64 billion unique monthly visitors. Both websites are among the most visited websites worldwide.

Daily page views for City Archives' Digital Repository for a given month.

This statistic illustrates the number of monthly unique visitors of Corriere della Sera website in Italy in the period from March to October 2018. Compared to March, when the number of unique visitors nearly reached ** million, Corriere.it lost approximately *** million unique visitors in October 2018.

In November 2024, Google.com was the leading website in Argentina by unique visits, with around 60.7 million single accesses to the URL during that month. YouTube.com followed, with 33.6 million unique monthly visits. Facebook.com came in third, with 23.5 million unique monthly visits.

The statistic shows the number of monthly unique visitors on online dating services in China from January 2016 to November 2018. In the latest reported month, Chinese online dating websites had about **** million unique visitors.

This dataset provides monthly page views in Data.gov up to 2013.

Difference uses Google Analytics as the Baseline. Results based on Paired t-Test for Hypotheses Supported.

The dataset contains information, divided by month, on the accesses made to the online services offered by the citizen's file and provided by the municipality of Milan. The pageviews column represents the total number of web pages, which have been displayed within the time frame used. The visitors column represents the total number of unique visitors who have accessed the web pages. By unique visitor, we mean a visitor counted only once within the time frame used.

This data, exported from Google Analytics displays the most popular 50 pages on Austintexas.gov based on the following: Pageviews: The total number of times the page was viewed. Repeated views of a single page are counted. Unique Pageviews: The number of visits during which the specified page was viewed at least once. A unique pageview is counted for each page URL + page Title combination. Average Time on Page: The average amount of time users spent viewing a specified page or screen, or set of pages or screens. Entrances: The number of times visitors entered your site through a specified page or set of pages. Bounce Rate: The percentage of single-page visits (i.e. visits in which the person left your site from the entrance page without interacting with the page). Percent Exit: (number of exits) / (number of pageviews) for the page or set of pages. It indicates how often users exit from that page or set of pages when they view the page(s). This demonstrates the top 50 pages for a three-month period.

This dataset presents the number of unique visitors on issy.com, the site of the City of Issy-les-Moulineaux, at monthly intervals.

Comparison of definitions of total visits, unique visitors, bounce rate, and session duration conceptually and for the two analytics platforms: Google Analytics and SimilarWeb.

This dataset tracks the updates made on the dataset "Monthly Page Views to CDC.gov" as a repository for previous versions of the data and metadata.

General data recollected for the studio " Analysis of the Quantitative Impact of Social Networks on Web Traffic of Cybermedia in the 27 Countries of the European Union". Four research questions are posed: what percentage of the total web traffic generated by cybermedia in the European Union comes from social networks? Is said percentage higher or lower than that provided through direct traffic and through the use of search engines via SEO positioning? Which social networks have a greater impact? And is there any degree of relationship between the specific weight of social networks in the web traffic of a cybermedia and circumstances such as the average duration of the user's visit, the number of page views or the bounce rate understood in its formal aspect of not performing any kind of interaction on the visited page beyond reading its content? To answer these questions, we have first proceeded to a selection of the cybermedia with the highest web traffic of the 27 countries that are currently part of the European Union after the United Kingdom left on December 31, 2020. In each nation we have selected five media using a combination of the global web traffic metrics provided by the tools Alexa (https://www.alexa.com/), which ceased to be operational on May 1, 2022, and SimilarWeb (https:// www.similarweb.com/). We have not used local metrics by country since the results obtained with these first two tools were sufficiently significant and our objective is not to establish a ranking of cybermedia by nation but to examine the relevance of social networks in their web traffic. In all cases, cybermedia whose property corresponds to a journalistic company have been selected, ruling out those belonging to telecommunications portals or service providers; in some cases they correspond to classic information companies (both newspapers and televisions) while in others they refer to digital natives, without this circumstance affecting the nature of the research proposed.
Below we have proceeded to examine the web traffic data of said cybermedia. The period corresponding to the months of October, November and December 2021 and January, February and March 2022 has been selected. We believe that this six-month stretch allows possible one-time variations to be overcome for a month, reinforcing the precision of the data obtained. To secure this data, we have used the SimilarWeb tool, currently the most precise tool that exists when examining the web traffic of a portal, although it is limited to that coming from desktops and laptops, without taking into account those that come from mobile devices, currently impossible to determine with existing measurement tools on the market. It includes:

Web traffic general data: average visit duration, pages per visit and bounce rate Web traffic origin by country Percentage of traffic generated from social media over total web traffic Distribution of web traffic generated from social networks Comparison of web traffic generated from social netwoks with direct and search procedures

Host country of organization for 86 websites in study.

This statistic contains data on the aggregated monthly audience of newspaper websites in the United States. In January 2015, U.S. newspapers' websites attracted a total of *** million unique visitors.

The dataset contains information, divided by month, on accesses made to the online services offered by the institutional portal and provided by the municipality of Milan. The pageviews column represents the total number of web pages that have been viewed within the time frame used. The visits column represents the total visits made, within the time frame used. The visitors column represents the total number of unique visitors who have accessed the web pages. By unique visitor, we mean a visitor counted only once within the time frame used.

Below you’ll find a month by month breakdown of traffic on the australia.gov.au website along the following lines:

• Pageviews
• Visits
• Pages per visit
• Average time on page
• Devices

This data is generated using Google analytics.

Please Note: This is an initial version of the data only. We’re looking forward to hearing your feedback on what other metrics are of interest to you. Please let us know by sending an email to data@digital.gov.au.