This dataset includes observations of trackers present on the top 500 pages popular among Finnish web users as per Alexa. The data collection was conducted using TrackerTracker in five separate requests for five subsets of 100 sites each between 19.8.2017 and 20.8.2017. The tool used a tracker database from March 24, 2017. More methodology details are described in the associated journal article https://doi.org/10.23978/inf.87841

history.com is ranked #1765 in US with 7.03M Traffic. Categories: . Learn more about website traffic, market share, and more!

This anonymized data set consists of one month's (October 2018) web tracking data of 2,148 German users. For each user, the data contains the anonymized URL of the webpage the user visited, the domain of the webpage, category of the domain, which provides 41 distinct categories. In total, these 2,148 users made 9,151,243 URL visits, spanning 49,918 unique domains. For each user in our data set, we have self-reported information (collected via a survey) about their gender and age.

We acknowledge the support of Respondi AG, which provided the web tracking and survey data free of charge for research purposes, with special thanks to François Erner and Luc Kalaora at Respondi for their insights and help with data extraction.

The data set is analyzed in the following paper:

• Kulshrestha, J., Oliveira, M., Karacalik, O., Bonnay, D., Wagner, C. "Web Routineness and Limits of Predictability: Investigating Demographic and Behavioral Differences Using Web Tracking Data." Proceedings of the International AAAI Conference on Web and Social Media. 2021. https://arxiv.org/abs/2012.15112.

The code used to analyze the data is also available at https://github.com/gesiscss/web_tracking.

If you use data or code from this repository, please cite the paper above and the Zenodo link.

This dataset contains a list of 3654 Dutch websites that we considered the most popular websites in 2015. This list served as whitelist for the Newstracker Research project in which we monitored the online web behaviour of a group of respondents.The research project 'The Newstracker' was a subproject of the NWO-funded project 'The New News Consumer: A User-Based Innovation Project to Meet Paradigmatic Change in News Use and Media Habits'.For the Newstracker project we aimed to understand the web behaviour of a group of respondents. We created custom-built software to monitor their web browsing behaviour on their laptops and desktops (please find the code in open access at https://github.com/NITechLabs/NewsTracker). For reasons of scale and privacy we created a whitelist with websites that were the most popular websites in 2015. We manually compiled this list by using data of DDMM, Alexa and own research. The dataset consists of 5 columns:- the URL- the type of website: We created a list of types of websites and each website has been manually labeled with 1 category- Nieuws-regio: When the category was 'News', we subdivided these websites in the regional focus: International, National or Local- Nieuws-onderwerp: Furthermore, each website under the category News was further subdivided in type of news website. For this we created an own list of news categories and manually coded each website- Bron: For each website we noted which source we used to find this website.The full description of the research design of the Newstracker including the set-up of this whitelist is included in the following article: Kleppe, M., Otte, M. (in print), 'Analysing & understanding news consumption patterns by tracking online user behaviour with a multimodal research design', Digital Scholarship in the Humanities, doi 10.1093/llc/fqx030.

In March 2024, close to 4.4 billion unique global visitors had visited Wikipedia.org, slightly down from 4.4 billion visitors since August of the same year. Wikipedia is a free online encyclopedia with articles generated by volunteers worldwide. The platform is hosted by the Wikimedia Foundation.

amazon.com is ranked #3 in US with 2.82B Traffic. Categories: Online Services. Learn more about website traffic, market share, and more!

Mobile accounts for approximately half of web traffic worldwide. In the last quarter of 2024, mobile devices (excluding tablets) generated 62.54 percent of global website traffic. Mobiles and smartphones consistently hoovered around the 50 percent mark since the beginning of 2017, before surpassing it in 2020. Mobile traffic Due to low infrastructure and financial restraints, many emerging digital markets skipped the desktop internet phase entirely and moved straight onto mobile internet via smartphone and tablet devices. India is a prime example of a market with a significant mobile-first online population. Other countries with a significant share of mobile internet traffic include Nigeria, Ghana and Kenya. In most African markets, mobile accounts for more than half of the web traffic. By contrast, mobile only makes up around 45.49 percent of online traffic in the United States. Mobile usage The most popular mobile internet activities worldwide include watching movies or videos online, e-mail usage and accessing social media. Apps are a very popular way to watch video on the go and the most-downloaded entertainment apps in the Apple App Store are Netflix, Tencent Video and Amazon Prime Video.

tracker.co.za is ranked #1417 in ZA with 193.15K Traffic. Categories: Information Technology. Learn more about website traffic, market share, and more!

Scientists are increasingly engaging the web to provide formal and informal science education opportunities. Despite the prolific growth of web-based resources, systematic evaluation and assessment of their efficacy remains limited. We used clickstream analytics, a widely available method for tracking website visitors and their behavior, to evaluate >60,000 visits over three years to an educational website focused on ecology. Visits originating from search engine queries were a small proportion of the traffic, suggesting the need to actively promote websites to drive visitation. However, the number of visits referred to the website per social media post varied depending on the social media platform and the quality of those visits (e.g., time on site and number of pages viewed) was significantly lower than visits originating from other referring websites. In particular, visitors referred to the website through targeted promotion (e.g., inclusion in a website listing classroom teaching resources) had higher quality visits. Once engaged in the site's core content, visitor retention was high; however, visitors rarely used the tutorial resources that serve to explain the site's use. Our results demonstrate that simple changes in website design, content and promotion are likely to increase the number of visitors and their engagement. While there is a growing emphasis on using the web to broaden the impacts of biological research, time and resources remain limited. Clickstream analytics provides an easily accessible, relatively fast and quantitative means by which those engaging in educational outreach can improve upon their efforts.

This public use dataset has 11 data elements reflecting COVID-19 community levels for all available counties. This dataset contains the same values used to display information available at https://www.cdc.gov/coronavirus/2019-ncov/science/community-levels-county-map.html. CDC looks at the combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days — to determine the COVID-19 community level. The COVID-19 community level is determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge. Using these data, the COVID-19 community level is classified as low, medium , or high. COVID-19 Community Levels can help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals. See https://www.cdc.gov/coronavirus/2019-ncov/science/community-levels.html for more information. Visit CDC’s COVID Data Tracker County View* to learn more about the individual metrics used for CDC’s COVID-19 community level in your county. Please note that county-level data are not available for territories. Go to https://covid.cdc.gov/covid-data-tracker/#county-view. For the most accurate and up-to-date data for any county or state, visit the relevant health department website. *COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

xlsx form for Survey123 endangered species monitoring workflows. This file can be used to create a new form.Download the file and use to create a new survey.

The data set includes Time from First Fixation to Click and Click Count data from particpants who viewed a beta-version website that promotes ecotourism in Greece. A Tobii Nano eye tracker was used for the data collection.

Context

The Google Merchandise Store sells Google branded merchandise. The data is typical of what you would see for an ecommerce website.

Content

The sample dataset contains Google Analytics 360 data from the Google Merchandise Store, a real ecommerce store. The Google Merchandise Store sells Google branded merchandise. The data is typical of what you would see for an ecommerce website. It includes the following kinds of information:

Traffic source data: information about where website visitors originate. This includes data about organic traffic, paid search traffic, display traffic, etc. Content data: information about the behavior of users on the site. This includes the URLs of pages that visitors look at, how they interact with content, etc. Transactional data: information about the transactions that occur on the Google Merchandise Store website.

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Acknowledgements

Data from: https://bigquery.cloud.google.com/table/bigquery-public-data:google_analytics_sample.ga_sessions_20170801

Banner Photo by Edho Pratama from Unsplash.

Inspiration

What is the total number of transactions generated per device browser in July 2017?

The real bounce rate is defined as the percentage of visits with a single pageview. What was the real bounce rate per traffic source?

What was the average number of product pageviews for users who made a purchase in July 2017?

What was the average number of product pageviews for users who did not make a purchase in July 2017?

What was the average total transactions per user that made a purchase in July 2017?

What is the average amount of money spent per session in July 2017?

What is the sequence of pages viewed?

Most migratory birds return every year to the same breeding sites and some species show a similarly high fidelity to wintering grounds as well. Fidelity to stopover sites during migration has been much less studied and is usually found to be lower. Here, we investigate site fidelity and distance to previously visited sites throughout the annual cycle in the common cuckoo, a nocturnal trans-Saharan migrant, based on satellite-tracking data from repeated annual migrations of thirteen adult males. All birds (100%) returned to the same breeding grounds, with a median shortest distance of only 1 km from the locations in previous year. This was in strong contrast to a much lower and much less precise site fidelity at non-breeding sites during the annual cycle: In only 18% of the possible cases in all non-breeding regions combined, did the cuckoos return to within 50 km of a previously visited non-breeding site, with no significant differences among the main staging regions (Europe in autumn, Sahel in autumn, wintering in Central Africa, West Africa in spring, Europe in spring). The shortest distance to a previously visited non-breeding site differed among the staging regions with median shortest distances for the longest stopovers of 131 km 2;1223 in Europe, 207 km [1;2222] in Sahel in autumn and 110 km [0;628] in Central Africa. The distance to a previously visited staging site decreased with the time spent at the stopover in a previous year. Understanding the drivers of recurrence and site selection in migratory birds are important for guiding conservation efforts in this group but further studies are needed to establish whether the patterns observed in cuckoos are general among terrestrial migrants with continuous distribution of habitat.

Vegetation surveys were conducted at each Great Valley and Mojave Desert study site between March and June 2017. The surveys followed the California Department of Fish and Wildlife Vegetation Reconnissance Field Protocol and were representative of either the lifeform for which the survey site was selected, or the dominant vegetation type encountered on site, if the preassigned lieform was not found. These reconnaissance vegetation surveys are based on a representative stand with a subset of dominant or characteristic plant species and their cover values recorded rather than a plot based survey. Field crews determined the primary alliance for the stand and identified the dominant species present, along with percent cover and phenology information. If there was any uncertainty in keying to alliance, a secondary alliance was also described, along with any details to aid in later determination. The CDFW Vegetation Classification and Mapping Program reviewed and confirmed or corrected all field assessments herein.

youtube.com is ranked #1 in KR with 47.12B Traffic. Categories: Newspapers, Online Services. Learn more about website traffic, market share, and more!

Records of species and habitat ad hoc sightings collected in the freshwater environment. This includes, but it not limited to aquatic plants, amphibians and certain easily identified invertebrates. Data collection will be on-going during the monitoring and other survey work.

Unlock the Power of Behavioural Data with GDPR-Compliant Clickstream Insights.

Swash clickstream data offers a comprehensive and GDPR-compliant dataset sourced from users worldwide, encompassing both desktop and mobile browsing behaviour. Here's an in-depth look at what sets us apart and how our data can benefit your organisation.

User-Centric Approach: Unlike traditional data collection methods, we take a user-centric approach by rewarding users for the data they willingly provide. This unique methodology ensures transparent data collection practices, encourages user participation, and establishes trust between data providers and consumers.

Wide Coverage and Varied Categories: Our clickstream data covers diverse categories, including search, shopping, and URL visits. Whether you are interested in understanding user preferences in e-commerce, analysing search behaviour across different industries, or tracking website visits, our data provides a rich and multi-dimensional view of user activities.

GDPR Compliance and Privacy: We prioritise data privacy and strictly adhere to GDPR guidelines. Our data collection methods are fully compliant, ensuring the protection of user identities and personal information. You can confidently leverage our clickstream data without compromising privacy or facing regulatory challenges.

Market Intelligence and Consumer Behaviuor: Gain deep insights into market intelligence and consumer behaviour using our clickstream data. Understand trends, preferences, and user behaviour patterns by analysing the comprehensive user-level, time-stamped raw or processed data feed. Uncover valuable information about user journeys, search funnels, and paths to purchase to enhance your marketing strategies and drive business growth.

High-Frequency Updates and Consistency: We provide high-frequency updates and consistent user participation, offering both historical data and ongoing daily delivery. This ensures you have access to up-to-date insights and a continuous data feed for comprehensive analysis. Our reliable and consistent data empowers you to make accurate and timely decisions.

Custom Reporting and Analysis: We understand that every organisation has unique requirements. That's why we offer customisable reporting options, allowing you to tailor the analysis and reporting of clickstream data to your specific needs. Whether you need detailed metrics, visualisations, or in-depth analytics, we provide the flexibility to meet your reporting requirements.

Data Quality and Credibility: We take data quality seriously. Our data sourcing practices are designed to ensure responsible and reliable data collection. We implement rigorous data cleaning, validation, and verification processes, guaranteeing the accuracy and reliability of our clickstream data. You can confidently rely on our data to drive your decision-making processes.

The global website monitoring services market, valued at $26.85 billion in 2025, is projected to experience robust growth, driven by the increasing reliance on websites for business operations and the escalating need for seamless online experiences. A compound annual growth rate (CAGR) of 9.6% from 2025 to 2033 indicates a significant expansion, with the market exceeding $50 billion by the end of the forecast period. This growth is fueled by several key factors. The proliferation of e-commerce and online businesses necessitates robust monitoring to ensure website uptime and performance, directly impacting revenue and customer satisfaction. Furthermore, the rising adoption of cloud-based solutions offers scalable and cost-effective monitoring options, attracting both small and medium-sized enterprises (SMEs) and large enterprises. Advanced features such as real-time alerts, performance analysis, and synthetic monitoring are becoming increasingly popular, driving demand for sophisticated solutions. The market segmentation, with applications spanning SMEs, large enterprises, and others, and types encompassing on-premise and cloud-based services, reflects the diverse needs of various customer segments. Geographical expansion, particularly in rapidly developing economies within Asia Pacific, also contributes significantly to market growth. However, challenges such as the complexity of implementing comprehensive monitoring systems and the associated costs could potentially act as restraints. The competitive landscape is characterized by a mix of established players and emerging companies offering diverse solutions, creating a dynamic and innovative market. The competitive landscape is highly dynamic, with established players like Google, Dynatrace, and SolarWinds competing alongside specialized providers such as Uptime Robot and ManageWP. This competition fosters innovation and drives the development of increasingly sophisticated and user-friendly monitoring tools. The continuous evolution of website technologies and security threats necessitates the development of adaptive monitoring solutions that can address emerging challenges. Future growth will likely be shaped by the increasing integration of Artificial Intelligence (AI) and machine learning (ML) into monitoring platforms, enabling proactive issue detection and improved performance optimization. The adoption of serverless architectures and edge computing will also impact the future of website monitoring, necessitating the development of monitoring solutions adapted to these evolving technological landscapes. The continued growth of the global digital economy ensures the long-term viability and expansion of the website monitoring services market.

In this cross-sectional study, we extracted the uniform resource locator (URL) of each National Abortion Federation member facility on May 6, 2022. We visited each unique URL using webXray (Timothy Libert), which detects third-party tracking. For each web page, we recorded data transfers to third-party domains. Transfers typically include a user’s IP (internet protocol) address and the web page being visited. We also recorded the presence of third-party cookies, data stored on a user’s computer that can facilitate tracking across multiple websites.