In August 2025, Google.com was the most visited website worldwide, attracting approximately 5.66 billion unique monthly visitors. YouTube.com ranked second, with an estimated 2.98 billion unique visitors. Both platforms also held the top positions globally in terms of total website visits.

In March 2024, search platform Google.com generated approximately 85.5 billion visits, down from 87 billion platform visits in October 2023. Google is a global search platform and one of the biggest online companies worldwide.

Comprehensive dataset analyzing Amazon's daily website visits, traffic patterns, seasonal trends, and comparative analysis with other ecommerce platforms based on May 2025 data.

Context

This file contains 5 years of daily time series data for several measures of traffic on a statistical forecasting teaching notes website whose alias is statforecasting.com. The variables have complex seasonality that is keyed to the day of the week and to the academic calendar. The patterns you you see here are similar in principle to what you would see in other daily data with day-of-week and time-of-year effects. Some good exercises are to develop a 1-day-ahead forecasting model, a 7-day ahead forecasting model, and an entire-next-week forecasting model (i.e., next 7 days) for unique visitors.

Content

The variables are daily counts of page loads, unique visitors, first-time visitors, and returning visitors to an academic teaching notes website. There are 2167 rows of data spanning the date range from September 14, 2014, to August 19, 2020. A visit is defined as a stream of hits on one or more pages on the site on a given day by the same user, as identified by IP address. Multiple individuals with a shared IP address (e.g., in a computer lab) are considered as a single user, so real users may be undercounted to some extent. A visit is classified as "unique" if a hit from the same IP address has not come within the last 6 hours. Returning visitors are identified by cookies if those are accepted. All others are classified as first-time visitors, so the count of unique visitors is the sum of the counts of returning and first-time visitors by definition. The data was collected through a traffic monitoring service known as StatCounter.

Inspiration

This file and a number of other sample datasets can also be found on the website of RegressIt, a free Excel add-in for linear and logistic regression which I originally developed for use in the course whose website generated the traffic data given here. If you use Excel to some extent as well as Python or R, you might want to try it out on this dataset.

Comprehensive dataset analyzing Walmart.com's daily website traffic, including 16.7 million daily visits, device distribution, geographic patterns, and competitive benchmarking data.

In August 2025, Google.com was the most visited website worldwide, with an average of 98.2 billion monthly visits. The platform has maintained its leading position since June 2010, when it surpassed Yahoo to take first place. YouTube ranked second during the same period, recording over 48 billion monthly visits. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

Google Search Statistics 2023

• Google is the most searched website in the World.
• Google receives more visitors than any other site. Google is accessed 89.3 trillion times per month.
• Google is used by billions of people every day to conduct their searches. Google is much more than a simple search engine.
• Google provides many other services. Google Shopping and Google News also feature. Google Mail, Google's popular email service, is included.
• Google organic search traffic is 16.3% of the total US searches.

In 2021, July was the busiest month for National Park Service sites in the United States. That month, national sites attracted about *** million visitors per day, denoting a ** percent increase in the average daily number of people going to sites over the same month in the previous year.

Website visit data with URLs, categories, timestamps, and anonymized unique device identifiers.

Over 50 million unique devices per day. 1 billion+ raw signals per month with historical raw data available.

This data can be combined with demographic and lifestyle data to provide a richer view of the anonymous users/devices.

Intended for training ML and AI models.

This dataset was obtained from website visit data. These are real data. It contains monthly visit information of the tr-metaverse.com website hosted on Linux. Day Hit Hit% Files Files% Pages Pages% Visit Visit% Sites Sites% Kbytes Kbytes% It consists of fields. Values with a % sign next to them are numbers in percent. 30-day visit data from the beginning of the month to the end of the month. Day: Day index number, which day of the month Hit: How much reach there is in general Hit%: How much access there is overall in percentage Files: How many visits have been made as files Files%: Percentage in files Pages Pages% Visit: Number of unique visitors Visit%: Unique visitor rate sites sites% Kbytes: how much data has been downloaded Kbytes%: percentage in data

This dataset displays the number of page views each day in 2017 for mississauga.ca. This data is compiled by Google Analytics and is updated annually.

This dataset represents a collection of records for users' visits to a website, where certain variables related to these users are studied to determine whether they clicked on a particular ad or not. Here’s a detailed description of the data:

Daily Time Spent on Site: The number of minutes the user spends on the website daily.

Age: The age of the user in years.

Area Income: The average annual income of the area where the user resides, measured in U.S. dollars.

Daily Internet Usage: The number of minutes the user spends on the internet daily.

Ad Topic Line: The headline or main topic of the ad that was shown to the user.

City: The city where the user resides.

Male: An indicator of the user's gender, where 1 represents male and 0 represents female.

Country: The country where the user resides.

Timestamp: The date and time when this record was logged.

Clicked on Ad: An indicator of whether the user clicked on the ad, where 1 means the user clicked on the ad, and 0 means they did not.

In summary, this data is used to analyze users' behavior on the website based on a set of demographic and usage factors, with a focus on whether they clicked on a particular ad or not.

This statistic shows the ten most popular coupon websites in China in June 2012, by unique visitors per day. In June 2012, the Chinese coupon website didatuan.com had approximately **** million unique visitors a day on average.

This dataset displays the number of page views each day in starting in June 2023 for data.mississauga.ca. This data is compiled by Google Analytics and is updated annually.

This dataset displays the number of page views each day in 2016 for mississauga.ca. This data is compiled by Google Analytics and is updated annually.

Daily utilization metrics for data.lacity.org and geohub.lacity.org. Updated monthly

This dataset displays the number of page views each day in 2018 for mississauga.ca. This data is compiled by Google Analytics and is updated annually.

Response variable: Revenue

Scenario

Online shopper's purchase intention is a difficult problem to predict, given the very large number of factors that can potentially affect an individual's decision to buy or not buy an item. It gets worse because most online stores can only obtain analytics information to facilitate such predictions, but not full-fledged individual-level information. Nevertheless, determining primary factors related to the site visits which lead to an efficacious transaction occurring enables retailers to maximize site layout and marketing campaigns, in an attempt to generate increased levels of sales.

This data set contains entries of a high volume of website visits, and the corresponding analytics information. The task is to forecast the value for the Revenue variable, with the models that can be applied to classification problems. Determine which features have the highest indication of a user's buying intention.

Attributes' Description Administrative: Number of administrative pages visited by the user

Administrative_Duration: Length of time spent on administrative pages, measured in seconds

Informational: Number of informational pages visited by the user

Informational_Duration: Length of time spent on informational pages, measured in seconds

ProductRelated: Number of product related pages visited by the user

ProductRelated_Duration: Length of time spent on product related pages, measured in seconds

BounceRates: Proportion of users who leave the site after only interacting with a single page

ExitRates: Proportion of views to a particular page that were the last in a user’s session

PageValues: Average number of pages visited by a user prior to a transaction taking place

SpecialDay: Closeness of the visit to a notable day of the year (e.g., Christmas Day, Mother’s Day, Valentine’s Day)

Month: Month in which the site visit took place

OperatingSystems: Operating system of the user Browser: Browser of the user

Region: Geographical region of the user

TrafficType: Traffic type of the user

VistorType: Whether the user is new or returning

Weekend: Whether the site visit took place on a weekend

Revenue: Whether the site visit resulted in a transaction taking place

Monthly analytics reports for the Brisbane City Council website

Information regarding the sessions for Brisbane City Council website during the month including the number of active users and views.

This dataset is a direct export from DC government's Google Analytics report of daily page views on the https://www.dc.gov web portal. This shows daily page views, per year, on DC.gov from 2008 to March 2020. It is identified by the part of the URL after the dc.gov domain path where users have visited.