100+ datasets found
  1. d

    Website Analytics

    • catalog.data.gov
    • data.brla.gov
    • +2more
    Updated Jun 29, 2025
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    data.brla.gov (2025). Website Analytics [Dataset]. https://catalog.data.gov/dataset/website-analytics-89ba5
    Explore at:
    Dataset updated
    Jun 29, 2025
    Dataset provided by
    data.brla.gov
    Description

    Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

  2. d

    Web Traffic Data | 500M+ US Web Traffic Data Resolution | B2B and B2C...

    • datarade.ai
    .csv, .xls
    Updated Feb 24, 2025
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    Allforce (2025). Web Traffic Data | 500M+ US Web Traffic Data Resolution | B2B and B2C Website Visitor Identity Resolution [Dataset]. https://datarade.ai/data-products/traffic-continuum-from-solution-publishing-500m-us-web-traf-solution-publishing
    Explore at:
    .csv, .xlsAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Allforce
    Area covered
    United States
    Description

    Unlock the Potential of Your Web Traffic with Advanced Data Resolution

    In the digital age, understanding and leveraging web traffic data is crucial for businesses aiming to thrive online. Our pioneering solution transforms anonymous website visits into valuable B2B and B2C contact data, offering unprecedented insights into your digital audience. By integrating our unique tag into your website, you unlock the capability to convert 25-50% of your anonymous traffic into actionable contact rows, directly deposited into an S3 bucket for your convenience. This process, known as "Web Traffic Data Resolution," is at the forefront of digital marketing and sales strategies, providing a competitive edge in understanding and engaging with your online visitors.

    Comprehensive Web Traffic Data Resolution Our product stands out by offering a robust solution for "Web Traffic Data Resolution," a process that demystifies the identities behind your website traffic. By deploying a simple tag on your site, our technology goes to work, analyzing visitor behavior and leveraging proprietary data matching techniques to reveal the individuals and businesses behind the clicks. This innovative approach not only enhances your data collection but does so with respect for privacy and compliance standards, ensuring that your business gains insights ethically and responsibly.

    Deep Dive into Web Traffic Data At the core of our solution is the sophisticated analysis of "Web Traffic Data." Our system meticulously collects and processes every interaction on your site, from page views to time spent on each section. This data, once anonymous and perhaps seen as abstract numbers, is transformed into a detailed ledger of potential leads and customer insights. By understanding who visits your site, their interests, and their contact information, your business is equipped to tailor marketing efforts, personalize customer experiences, and streamline sales processes like never before.

    Benefits of Our Web Traffic Data Resolution Service Enhanced Lead Generation: By converting anonymous visitors into identifiable contact data, our service significantly expands your pool of potential leads. This direct enhancement of your lead generation efforts can dramatically increase conversion rates and ROI on marketing campaigns.

    Targeted Marketing Campaigns: Armed with detailed B2B and B2C contact data, your marketing team can create highly targeted and personalized campaigns. This precision in marketing not only improves engagement rates but also ensures that your messaging resonates with the intended audience.

    Improved Customer Insights: Gaining a deeper understanding of your web traffic enables your business to refine customer personas and tailor offerings to meet market demands. These insights are invaluable for product development, customer service improvement, and strategic planning.

    Competitive Advantage: In a digital landscape where understanding your audience can make or break your business, our Web Traffic Data Resolution service provides a significant competitive edge. By accessing detailed contact data that others in your industry may overlook, you position your business as a leader in customer engagement and data-driven strategies.

    Seamless Integration and Accessibility: Our solution is designed for ease of use, requiring only the placement of a tag on your website to start gathering data. The contact rows generated are easily accessible in an S3 bucket, ensuring that you can integrate this data with your existing CRM systems and marketing tools without hassle.

    How It Works: A Closer Look at the Process Our Web Traffic Data Resolution process is streamlined and user-friendly, designed to integrate seamlessly with your existing website infrastructure:

    Tag Deployment: Implement our unique tag on your website with simple instructions. This tag is lightweight and does not impact your site's loading speed or user experience.

    Data Collection and Analysis: As visitors navigate your site, our system collects web traffic data in real-time, analyzing behavior patterns, engagement metrics, and more.

    Resolution and Transformation: Using advanced data matching algorithms, we resolve the collected web traffic data into identifiable B2B and B2C contact information.

    Data Delivery: The resolved contact data is then securely transferred to an S3 bucket, where it is organized and ready for your access. This process occurs daily, ensuring you have the most up-to-date information at your fingertips.

    Integration and Action: With the resolved data now in your possession, your business can take immediate action. From refining marketing strategies to enhancing customer experiences, the possibilities are endless.

    Security and Privacy: Our Commitment Understanding the sensitivity of web traffic data and contact information, our solution is built with security and privacy at its core. We adhere to strict data protection regulat...

  3. d

    Open Data Website Traffic

    • catalog.data.gov
    • data.lacity.org
    Updated Jun 21, 2025
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    data.lacity.org (2025). Open Data Website Traffic [Dataset]. https://catalog.data.gov/dataset/open-data-website-traffic
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    Dataset updated
    Jun 21, 2025
    Dataset provided by
    data.lacity.org
    Description

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

  4. W

    Website Visitor Tracking Software Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Apr 25, 2025
    + more versions
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    Archive Market Research (2025). Website Visitor Tracking Software Report [Dataset]. https://www.archivemarketresearch.com/reports/website-visitor-tracking-software-561091
    Explore at:
    ppt, doc, pdfAvailable download formats
    Dataset updated
    Apr 25, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Website Visitor Tracking Software market is experiencing robust growth, driven by the increasing need for businesses to understand online customer behavior and optimize their digital strategies. This market, currently valued at approximately $5 billion in 2025, is projected to grow at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting both SMEs and large enterprises. Furthermore, the increasing sophistication of analytics features within these platforms allows for deeper insights into website traffic, user engagement, and conversion rates. This empowers businesses to personalize user experiences, refine marketing campaigns, and ultimately drive revenue growth. The market segmentation reveals a significant share held by cloud-based solutions due to their accessibility and flexibility, while the large enterprise segment is a primary revenue driver due to its higher spending capacity. Competition is intense, with established players like Google Analytics and Adobe Analytics alongside a burgeoning number of specialized providers offering unique features and functionalities. The competitive landscape is dynamic, with established players facing challenges from nimble startups innovating in areas like AI-powered behavioral analytics and personalized recommendations. While data privacy concerns and the increasing complexity of tracking regulations represent potential restraints, the overall market outlook remains positive. The continued growth of e-commerce, digital marketing, and the broader digital economy will fuel further demand for sophisticated visitor tracking solutions. Geographic expansion, particularly in rapidly developing economies within Asia-Pacific and Latin America, will contribute significantly to market expansion over the forecast period. The integration of website visitor tracking with other marketing automation and CRM tools is another key trend, further solidifying its importance within a comprehensive digital strategy. The market's future hinges on the continuous innovation in data analytics capabilities, the development of user-friendly interfaces, and the ability to adapt to evolving privacy regulations.

  5. A

    ‘Popular Website Traffic Over Time ’ analyzed by Analyst-2

    • analyst-2.ai
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com), ‘Popular Website Traffic Over Time ’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-popular-website-traffic-over-time-62e4/62549059/?iid=003-357&v=presentation
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    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Popular Website Traffic Over Time ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/popular-website-traffice on 13 February 2022.

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

    About this dataset

    Background

    Have you every been in a conversation and the question comes up, who uses Bing? This question comes up occasionally because people wonder if these sites have any views. For this research study, we are going to be exploring popular website traffic for many popular websites.

    Methodology

    The data collected originates from SimilarWeb.com.

    Source

    For the analysis and study, go to The Concept Center

    This dataset was created by Chase Willden and contains around 0 samples along with 1/1/2017, Social Media, technical information and other features such as: - 12/1/2016 - 3/1/2017 - and more.

    How to use this dataset

    • Analyze 11/1/2016 in relation to 2/1/2017
    • Study the influence of 4/1/2017 on 1/1/2017
    • More datasets

    Acknowledgements

    If you use this dataset in your research, please credit Chase Willden

    Start A New Notebook!

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

  6. Z

    Network Traffic Analysis: Data and Code

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jun 12, 2024
    + more versions
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    Honig, Joshua (2024). Network Traffic Analysis: Data and Code [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_11479410
    Explore at:
    Dataset updated
    Jun 12, 2024
    Dataset provided by
    Chan-Tin, Eric
    Homan, Sophia
    Honig, Joshua
    Soni, Shreena
    Moran, Madeline
    Ferrell, Nathan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Code:

    Packet_Features_Generator.py & Features.py

    To run this code:

    pkt_features.py [-h] -i TXTFILE [-x X] [-y Y] [-z Z] [-ml] [-s S] -j

    -h, --help show this help message and exit -i TXTFILE input text file -x X Add first X number of total packets as features. -y Y Add first Y number of negative packets as features. -z Z Add first Z number of positive packets as features. -ml Output to text file all websites in the format of websiteNumber1,feature1,feature2,... -s S Generate samples using size s. -j

    Purpose:

    Turns a text file containing lists of incomeing and outgoing network packet sizes into separate website objects with associative features.

    Uses Features.py to calcualte the features.

    startMachineLearning.sh & machineLearning.py

    To run this code:

    bash startMachineLearning.sh

    This code then runs machineLearning.py in a tmux session with the nessisary file paths and flags

    Options (to be edited within this file):

    --evaluate-only to test 5 fold cross validation accuracy

    --test-scaling-normalization to test 6 different combinations of scalers and normalizers

    Note: once the best combination is determined, it should be added to the data_preprocessing function in machineLearning.py for future use

    --grid-search to test the best grid search hyperparameters - note: the possible hyperparameters must be added to train_model under 'if not evaluateOnly:' - once best hyperparameters are determined, add them to train_model under 'if evaluateOnly:'

    Purpose:

    Using the .ml file generated by Packet_Features_Generator.py & Features.py, this program trains a RandomForest Classifier on the provided data and provides results using cross validation. These results include the best scaling and normailzation options for each data set as well as the best grid search hyperparameters based on the provided ranges.

    Data

    Encrypted network traffic was collected on an isolated computer visiting different Wikipedia and New York Times articles, different Google search queres (collected in the form of their autocomplete results and their results page), and different actions taken on a Virtual Reality head set.

    Data for this experiment was stored and analyzed in the form of a txt file for each experiment which contains:

    First number is a classification number to denote what website, query, or vr action is taking place.

    The remaining numbers in each line denote:

    The size of a packet,

    and the direction it is traveling.

    negative numbers denote incoming packets

    positive numbers denote outgoing packets

    Figure 4 Data

    This data uses specific lines from the Virtual Reality.txt file.

    The action 'LongText Search' refers to a user searching for "Saint Basils Cathedral" with text in the Wander app.

    The action 'ShortText Search' refers to a user searching for "Mexico" with text in the Wander app.

    The .xlsx and .csv file are identical

    Each file includes (from right to left):

    The origional packet data,

    each line of data organized from smallest to largest packet size in order to calculate the mean and standard deviation of each packet capture,

    and the final Cumulative Distrubution Function (CDF) caluclation that generated the Figure 4 Graph.

  7. Share of global mobile website traffic 2015-2024

    • statista.com
    • ai-chatbox.pro
    Updated Jan 28, 2025
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    Statista (2025). Share of global mobile website traffic 2015-2024 [Dataset]. https://www.statista.com/statistics/277125/share-of-website-traffic-coming-from-mobile-devices/
    Explore at:
    Dataset updated
    Jan 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    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.

  8. W

    Website Traffic Analysis Tool Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Apr 25, 2025
    + more versions
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    Data Insights Market (2025). Website Traffic Analysis Tool Report [Dataset]. https://www.datainsightsmarket.com/reports/website-traffic-analysis-tool-1455386
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Apr 25, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global website traffic analysis tool market is experiencing robust growth, driven by the increasing reliance on digital marketing and the need for businesses of all sizes to understand their online audience. The market, estimated at $15 billion in 2025, is projected to grow at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. The rising adoption of cloud-based solutions provides scalability and cost-effectiveness for businesses, particularly SMEs seeking affordable analytics. Moreover, the evolution of sophisticated analytics features, including advanced user behavior tracking and predictive analytics, enhances the value proposition for both SMEs and large enterprises. The market is segmented by application (SMEs and large enterprises) and by type (cloud-based and web-based), with cloud-based solutions dominating due to their accessibility and flexibility. Competitive pressures among numerous vendors, including established players like Google Analytics, Semrush, and Ahrefs, as well as emerging niche players, drive innovation and affordability, benefiting users. Geographic distribution shows strong growth across North America and Europe, with Asia-Pacific emerging as a high-growth region. However, factors such as data privacy concerns and the increasing complexity of website analytics can act as potential restraints. Despite these challenges, the continued expansion of e-commerce and digital marketing strategies across various industries will solidify the demand for robust website traffic analysis tools. The market is expected to witness further consolidation through mergers and acquisitions, with leading players investing heavily in research and development to enhance their offerings. The increasing need for real-time data analysis and integration with other marketing automation platforms will further shape market evolution. The emergence of AI-powered analytics, providing predictive insights and automated reporting, is transforming the industry and will continue to drive market expansion in the coming years. This makes this market an attractive landscape for investors and technology providers looking for strong future growth.

  9. Number of worldwide internet users 2009-2022, by region

    • statista.com
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    Ani Petrosyan, Number of worldwide internet users 2009-2022, by region [Dataset]. https://www.statista.com/study/33852/reach-and-website-traffic-in-the-united-kingdom-statista-dossier/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Ani Petrosyan
    Description

    As of June 2022, Asia was leading by the number of internet users worldwide with nearly 2.9 billion internet users. Europe ranked second, with more than 750 million internet users. Meanwhile, the number of internet users worldwide was 5.47 billion.

  10. Share of U.S. mobile website traffic 2015-2023

    • statista.com
    Updated Mar 25, 2024
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    Statista (2024). Share of U.S. mobile website traffic 2015-2023 [Dataset]. https://www.statista.com/statistics/683082/share-of-website-traffic-coming-from-mobile-devices-usa/
    Explore at:
    Dataset updated
    Mar 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of the last quarter of 2023, 31.57 percent of web traffic in the United States originated from mobile devices, down from 49.51 percent in the fourth quarter of 2022. In comparison, over half of web traffic worldwide was generated via mobile in the last examined period.

  11. d

    Click Global Data | Web Traffic Data + Transaction Data | Consumer and B2B...

    • datarade.ai
    .csv
    Updated Mar 13, 2025
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    Consumer Edge (2025). Click Global Data | Web Traffic Data + Transaction Data | Consumer and B2B Shopper Insights | 59 Countries, 3-Day Lag, Daily Delivery [Dataset]. https://datarade.ai/data-products/click-global-data-web-traffic-data-transaction-data-con-consumer-edge
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Mar 13, 2025
    Dataset authored and provided by
    Consumer Edge
    Area covered
    Bermuda, Marshall Islands, Congo, Bosnia and Herzegovina, South Africa, Sri Lanka, Nauru, El Salvador, Finland, Montserrat
    Description

    Click Web Traffic Combined with Transaction Data: A New Dimension of Shopper Insights

    Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. Click enhances the unparalleled accuracy of CE Transact by allowing investors to delve deeper and browse further into global online web traffic for CE Transact companies and more. Leverage the unique fusion of web traffic and transaction datasets to understand the addressable market and understand spending behavior on consumer and B2B websites. See the impact of changes in marketing spend, search engine algorithms, and social media awareness on visits to a merchant’s website, and discover the extent to which product mix and pricing drive or hinder visits and dwell time. Plus, Click uncovers a more global view of traffic trends in geographies not covered by Transact. Doubleclick into better forecasting, with Click.

    Consumer Edge’s Click is available in machine-readable file delivery and enables: • Comprehensive Global Coverage: Insights across 620+ brands and 59 countries, including key markets in the US, Europe, Asia, and Latin America. • Integrated Data Ecosystem: Click seamlessly maps web traffic data to CE entities and stock tickers, enabling a unified view across various business intelligence tools. • Near Real-Time Insights: Daily data delivery with a 5-day lag ensures timely, actionable insights for agile decision-making. • Enhanced Forecasting Capabilities: Combining web traffic indicators with transaction data helps identify patterns and predict revenue performance.

    Use Case: Analyze Year Over Year Growth Rate by Region

    Problem A public investor wants to understand how a company’s year-over-year growth differs by region.

    Solution The firm leveraged Consumer Edge Click data to: • Gain visibility into key metrics like views, bounce rate, visits, and addressable spend • Analyze year-over-year growth rates for a time period • Breakout data by geographic region to see growth trends

    Metrics Include: • Spend • Items • Volume • Transactions • Price Per Volume

    Inquire about a Click subscription to perform more complex, near real-time analyses on public tickers and private brands as well as for industries beyond CPG like: • Monitor web traffic as a leading indicator of stock performance and consumer demand • Analyze customer interest and sentiment at the brand and sub-brand levels

    Consumer Edge offers a variety of datasets covering the US, Europe (UK, Austria, France, Germany, Italy, Spain), and across the globe, with subscription options serving a wide range of business needs.

    Consumer Edge is the Leader in Data-Driven Insights Focused on the Global Consumer

  12. C

    Competitive Analysis of Industry Rivals Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated May 20, 2025
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    Data Insights Market (2025). Competitive Analysis of Industry Rivals Report [Dataset]. https://www.datainsightsmarket.com/reports/competitive-analysis-of-industry-rivals-1427015
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    May 20, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The website analytics market, encompassing solutions like product, traffic, and sales analytics, is a dynamic and rapidly growing sector. While precise market sizing data wasn't provided, considering the presence of major players like Google, SEMrush, and SimilarWeb, along with numerous smaller competitors catering to SMEs and large enterprises, we can reasonably estimate a 2025 market value of $15 billion, projecting a Compound Annual Growth Rate (CAGR) of 15% from 2025-2033. This growth is fueled by the increasing reliance of businesses on data-driven decision-making, the expanding adoption of digital marketing strategies, and the rising need for precise performance measurement across all digital channels. Key trends driving this expansion include the integration of AI and machine learning for enhanced predictive analytics, the rise of serverless architectures for cost-effective scalability, and the growing demand for comprehensive dashboards providing unified insights across different marketing channels. However, challenges remain, including data privacy concerns, the complexity of integrating various analytics tools, and the need for businesses to cultivate internal expertise to effectively utilize the data generated. The competitive landscape is highly fragmented, with established giants like Google Analytics competing alongside specialized providers like SEMrush (focused on SEO and PPC analytics), SimilarWeb (website traffic analysis), and BuiltWith (technology identification). Smaller companies, such as Owletter and SpyFu, carve out niches by focusing on specific areas or offering specialized features. This dynamic competition necessitates continuous innovation and adaptation. Companies must differentiate themselves through specialized features, ease of use, and strong customer support. The market's geographic distribution is likely skewed towards North America and Europe initially, mirroring the higher digital maturity in these regions; however, rapid growth is anticipated in Asia-Pacific regions driven by increasing internet penetration and adoption of digital technologies within emerging economies like India and China. Successful players will need to develop strategies to effectively capture this expanding global market, adapting offerings to suit diverse regional needs and regulatory environments.

  13. C

    Competitive Analysis of Industry Rivals Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Feb 21, 2025
    + more versions
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    Archive Market Research (2025). Competitive Analysis of Industry Rivals Report [Dataset]. https://www.archivemarketresearch.com/reports/competitive-analysis-of-industry-rivals-38541
    Explore at:
    ppt, doc, pdfAvailable download formats
    Dataset updated
    Feb 21, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Competitive Analysis of Industry Rivals The market for competitive analysis is expected to grow significantly over the forecast period, driven by increasing need for businesses to understand their competitive landscape. Key players in the market include BuiltWith, WooRank, SEMrush, Google, SpyFu, Owletter, SimilarWeb, Moz, SunTec Data, and TrendSource. These companies offer a range of services to help businesses track their competitors' online performance, including website traffic, social media engagement, and search engine rankings. Some of the key trends driving the growth of the market include the increasing adoption of digital marketing by businesses, the growing importance of social media, and the increasing availability of data and analytics tools. The market is segmented by type, application, and region. In terms of type, the market is divided into product analysis, traffic analytics, sales analytics, and others. In terms of application, the market is divided into SMEs and large enterprises. In terms of region, the market is divided into North America, South America, Europe, Middle East & Africa, and Asia Pacific. The North American region is expected to dominate the market during the forecast period, due to the presence of a large number of established players in the market. The Asia Pacific region is expected to grow at the highest CAGR during the forecast period, due to the increasing adoption of digital marketing by businesses in the region. This report provides a comprehensive analysis of the industry rivals, encompassing their concentration, product insights, regional trends, and key industry developments.

  14. Zalando: website traffic on desktop and mobile across all domains 2023

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Zalando: website traffic on desktop and mobile across all domains 2023 [Dataset]. https://www.statista.com/statistics/1175856/zalando-website-traffic-all-domains/
    Explore at:
    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2023 - Dec 2023
    Area covered
    Europe
    Description

    Desktop and mobile website traffic data showed that Germany domain of Zalando had by far the highest number of visitors compared to all other European countries. Between July 2023 and December 2023, zalando.de recorded more nearly *** million visits. The Polish web domain followed in the ranking, as the total visits amounted to **** million.

  15. Leading internet brands ranked by Buzz score in the United Kingdom 2019

    • statista.com
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    Statista Research Department, Leading internet brands ranked by Buzz score in the United Kingdom 2019 [Dataset]. https://www.statista.com/study/33852/reach-and-website-traffic-in-the-united-kingdom-statista-dossier/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United Kingdom
    Description

    This statistic ranks leading internet brands by average Buzz score in the United Kingdom from January to December 2019. WhatsApp ranked highest with a score of 7.1, followed by eBay and YouTube.

  16. Web Analytics Market Analysis, Size, and Forecast 2025-2029: North America...

    • technavio.com
    Updated Apr 15, 2025
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    Technavio (2025). Web Analytics Market Analysis, Size, and Forecast 2025-2029: North America (US and Canada), Europe (France, Germany, Italy, and UK), APAC (China, India, Japan, and South Korea), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/web-analytics-market-industry-analysis
    Explore at:
    Dataset updated
    Apr 15, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Global, United States
    Description

    Snapshot img

    Web Analytics Market Size 2025-2029

    The web analytics market size is forecast to increase by USD 3.63 billion, at a CAGR of 15.4% between 2024 and 2029.

    The market is experiencing significant growth, driven by the rising preference for online shopping and the increasing adoption of cloud-based solutions. The shift towards e-commerce is fueling the demand for advanced web analytics tools that enable businesses to gain insights into customer behavior and optimize their digital strategies. Furthermore, cloud deployment models offer flexibility, scalability, and cost savings, making them an attractive option for businesses of all sizes. However, the market also faces challenges associated with compliance to data privacy and regulations. With the increasing amount of data being generated and collected, ensuring data security and privacy is becoming a major concern for businesses.
    Regulatory compliance, such as GDPR and CCPA, adds complexity to the implementation and management of web analytics solutions. Companies must navigate these challenges effectively to maintain customer trust and avoid potential legal issues. To capitalize on market opportunities and address these challenges, businesses should invest in robust web analytics solutions that prioritize data security and privacy while providing actionable insights to inform strategic decision-making and enhance customer experiences.
    

    What will be the Size of the Web Analytics Market during the forecast period?

    Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
    Request Free Sample

    The market continues to evolve, with dynamic market activities unfolding across various sectors. Entities such as reporting dashboards, schema markup, conversion optimization, session duration, organic traffic, attribution modeling, conversion rate optimization, call to action, content calendar, SEO audits, website performance optimization, link building, page load speed, user behavior tracking, and more, play integral roles in this ever-changing landscape. Data visualization tools like Google Analytics and Adobe Analytics provide valuable insights into user engagement metrics, helping businesses optimize their content strategy, website design, and technical SEO. Goal tracking and keyword research enable marketers to measure the return on investment of their efforts and refine their content marketing and social media marketing strategies.

    Mobile optimization, form optimization, and landing page optimization are crucial aspects of website performance optimization, ensuring a seamless user experience across devices and improving customer acquisition cost. Search console and page speed insights offer valuable insights into website traffic analysis and help businesses address technical issues that may impact user behavior. Continuous optimization efforts, such as multivariate testing, data segmentation, and data filtering, allow businesses to fine-tune their customer journey mapping and cohort analysis. Search engine optimization, both on-page and off-page, remains a critical component of digital marketing, with backlink analysis and page authority playing key roles in improving domain authority and organic traffic.

    The ongoing integration of user behavior tracking, click-through rate, and bounce rate into marketing strategies enables businesses to gain a deeper understanding of their audience and optimize their customer experience accordingly. As market dynamics continue to evolve, the integration of these tools and techniques into comprehensive digital marketing strategies will remain essential for businesses looking to stay competitive in the digital landscape.

    How is this Web Analytics Industry segmented?

    The web analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Deployment
    
      Cloud-based
      On-premises
    
    
    Application
    
      Social media management
      Targeting and behavioral analysis
      Display advertising optimization
      Multichannel campaign analysis
      Online marketing
    
    
    Component
    
      Solutions
      Services
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        Italy
        UK
    
    
      APAC
    
        China
        India
        Japan
        South Korea
    
    
      Rest of World (ROW)
    

    .

    By Deployment Insights

    The cloud-based segment is estimated to witness significant growth during the forecast period.

    In today's digital landscape, web analytics plays a pivotal role in driving business growth and optimizing online performance. Cloud-based deployment of web analytics is a game-changer, enabling on-demand access to computing resources for data analysis. This model streamlines business intelligence processes by collecting,

  17. Network Traffic Analysis NTA Software Market Report | Global Forecast From...

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 4, 2024
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    Dataintelo (2024). Network Traffic Analysis NTA Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-network-traffic-analysis-nta-software-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Dec 4, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Network Traffic Analysis (NTA) Software Market Outlook



    The global Network Traffic Analysis (NTA) Software market size is poised to witness a robust growth trajectory, with a projected market valuation rising from approximately USD 3.5 billion in 2023 to an impressive USD 12.4 billion by 2032, growing at a compound annual growth rate (CAGR) of 15.2% during the forecast period. The surge in this market is predominantly fueled by the increasing need for sophisticated cybersecurity measures due to the escalating frequency and complexity of cyber threats. Organizations are progressively recognizing the critical importance of NTA software in detecting, monitoring, and responding to potential network anomalies and threats, driving the market's expansion.



    A major growth factor contributing to the burgeoning NTA Software market is the exponential growth in data traffic, attributed to the widespread adoption of cloud computing, IoT devices, and the ongoing digital transformation across industries. As enterprises expand their digital footprint, the volume of data traversing networks has seen an unprecedented rise, necessitating advanced network traffic analysis solutions to ensure efficient management and security of data. Moreover, the increasing sophistication of cyber threats, including advanced persistent threats (APTs) and ransomware, has made continuous network monitoring and analysis indispensable for organizations striving to protect sensitive information and maintain business continuity.



    Another significant driver for the NTA Software market is the growing regulatory pressures and compliance requirements across various sectors, including BFSI, healthcare, and government. These regulations mandate organizations to implement robust cybersecurity frameworks and ensure data protection, thereby propelling the demand for comprehensive NTA solutions. Companies are increasingly investing in NTA software to comply with standards such as GDPR, HIPAA, and PCI-DSS, which emphasize the importance of network security and data privacy. As regulatory landscapes continue to evolve, the necessity for effective network traffic analysis tools becomes even more pronounced, further accelerating market growth.



    The increasing adoption of artificial intelligence (AI) and machine learning (ML) technologies in network traffic analysis is also a key factor driving the market's growth. These technologies enhance the capabilities of NTA software by enabling automated threat detection, predictive analytics, and anomaly detection, thereby improving the overall efficiency and accuracy of network monitoring. The integration of AI and ML has allowed NTA solutions to evolve from traditional reactive systems to proactive security platforms, capable of identifying and mitigating threats in real-time. This technological advancement is particularly attractive to large enterprises and government agencies that require robust security measures to safeguard critical infrastructure and data.



    From a regional perspective, North America is anticipated to lead the NTA Software market during the forecast period, owing to the region's well-established IT infrastructure and the presence of major industry players. The Asia Pacific region, however, is expected to witness the fastest growth, driven by rapid technological advancements, increasing internet penetration, and a rising focus on cybersecurity across emerging economies such as India and China. Europe also presents significant growth opportunities, supported by stringent data protection regulations and growing investments in cybersecurity solutions. These regional dynamics highlight the diverse growth trajectories and opportunities present across the global NTA Software market.



    Component Analysis



    The Network Traffic Analysis Software market is segmented into two primary components: software and services. The software segment accounts for the largest share of the market and is expected to continue its dominance throughout the forecast period. This is primarily due to the increasing demand for advanced network traffic analysis solutions that can efficiently monitor, detect, and respond to potential security threats. With the escalating frequency of cyberattacks, organizations are increasingly leveraging sophisticated software to enhance their network security posture and mitigate risks. The software component includes various solutions such as real-time traffic monitoring, anomaly detection, and threat intelligence, which are integral to comprehensive network security strategies.



    The services segment, on the other hand, is projected to witness signi

  18. C

    Competitor Analysis Evaluation Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 16, 2025
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    Archive Market Research (2025). Competitor Analysis Evaluation Report [Dataset]. https://www.archivemarketresearch.com/reports/competitor-analysis-evaluation-59567
    Explore at:
    pdf, ppt, docAvailable download formats
    Dataset updated
    Mar 16, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global website analytics market, encompassing solutions for large enterprises and SMEs, is poised for significant growth. While the provided data lacks specific market size and CAGR figures, a reasonable estimation based on industry trends suggests a 2025 market size of approximately $15 billion, experiencing a compound annual growth rate (CAGR) of 12% from 2025 to 2033. This robust growth is fueled by several key drivers: the increasing reliance on data-driven decision-making across businesses, the escalating need for enhanced website performance optimization, and the growing adoption of sophisticated analytics tools offering deeper insights into user behavior and conversion rates. Market segmentation reveals strong demand across diverse analytics types, including product, traffic, and sales analytics. The competitive landscape is intensely dynamic, with established players like Google, SEMrush, and SimilarWeb vying for market share alongside emerging innovative companies like Owletter and TrendSource. These companies are constantly innovating to provide more comprehensive and user-friendly analytics platforms, leading to increased competition. This competitive pressure fosters innovation, but also necessitates strategic differentiation, focusing on specific niche markets or offering unique features to attract and retain customers. The market’s geographic distribution shows significant traction in North America and Europe, but emerging markets in Asia Pacific are also exhibiting substantial growth potential, driven by increasing internet penetration and digital transformation initiatives. While data security concerns and the complexity of implementing analytics tools present some restraints, the overall market outlook remains highly positive, promising considerable opportunities for market participants in the coming years.

  19. i

    Website Fingerprinting Dataset of Browsing Network Traffic for Desktop and...

    • ieee-dataport.org
    Updated Oct 21, 2024
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    Mohamad Amar Irsyad Mohd Aminuddin (2024). Website Fingerprinting Dataset of Browsing Network Traffic for Desktop and Mobile Webpages [Dataset]. https://ieee-dataport.org/documents/website-fingerprinting-dataset-browsing-network-traffic-desktop-and-mobile-webpages
    Explore at:
    Dataset updated
    Oct 21, 2024
    Authors
    Mohamad Amar Irsyad Mohd Aminuddin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is a dataset of Tor cell file extracted from browsing simulation using Tor Browser. The simulations cover both desktop and mobile webpages. The data collection process was using WFP-Collector tool (https://github.com/irsyadpage/WFP-Collector). All the neccessary configuration to perform the simulation as detailed in the tool repository.The webpage URL is selected by using the first 100 website based on: https://dataforseo.com/free-seo-stats/top-1000-websites.Each webpage URL is visited 90 times for each deskop and mobile browsing mode.

  20. Network traffic datasets created by Single Flow Time Series Analysis

    • zenodo.org
    • data.niaid.nih.gov
    csv, pdf
    Updated Jul 11, 2024
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    Josef Koumar; Josef Koumar; Karel Hynek; Karel Hynek; Tomáš Čejka; Tomáš Čejka (2024). Network traffic datasets created by Single Flow Time Series Analysis [Dataset]. http://doi.org/10.5281/zenodo.8035724
    Explore at:
    csv, pdfAvailable download formats
    Dataset updated
    Jul 11, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Josef Koumar; Josef Koumar; Karel Hynek; Karel Hynek; Tomáš Čejka; Tomáš Čejka
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Network traffic datasets created by Single Flow Time Series Analysis

    Datasets were created for the paper: Network Traffic Classification based on Single Flow Time Series Analysis -- Josef Koumar, Karel Hynek, Tomáš Čejka -- which was published at The 19th International Conference on Network and Service Management (CNSM) 2023. Please cite usage of our datasets as:

    J. Koumar, K. Hynek and T. Čejka, "Network Traffic Classification Based on Single Flow Time Series Analysis," 2023 19th International Conference on Network and Service Management (CNSM), Niagara Falls, ON, Canada, 2023, pp. 1-7, doi: 10.23919/CNSM59352.2023.10327876.

    This Zenodo repository contains 23 datasets created from 15 well-known published datasets which are cited in the table below. Each dataset contains 69 features created by Time Series Analysis of Single Flow Time Series. The detailed description of features from datasets is in the file: feature_description.pdf

    In the following table is a description of each dataset file:

    File nameDetection problemCitation of original raw dataset
    botnet_binary.csv Binary detection of botnet S. García et al. An Empirical Comparison of Botnet Detection Methods. Computers & Security, 45:100–123, 2014.
    botnet_multiclass.csv Multi-class classification of botnet S. García et al. An Empirical Comparison of Botnet Detection Methods. Computers & Security, 45:100–123, 2014.
    cryptomining_design.csvBinary detection of cryptomining; the design part Richard Plný et al. Datasets of Cryptomining Communication. Zenodo, October 2022
    cryptomining_evaluation.csv Binary detection of cryptomining; the evaluation part Richard Plný et al. Datasets of Cryptomining Communication. Zenodo, October 2022
    dns_malware.csv Binary detection of malware DNS Samaneh Mahdavifar et al. Classifying Malicious Domains using DNS Traffic Analysis. In DASC/PiCom/CBDCom/CyberSciTech 2021, pages 60–67. IEEE, 2021.
    doh_cic.csv Binary detection of DoH

    Mohammadreza MontazeriShatoori et al. Detection of doh tunnels using time-series classification of encrypted traffic. In DASC/PiCom/CBDCom/CyberSciTech 2020, pages 63–70. IEEE, 2020

    doh_real_world.csv Binary detection of DoH Kamil Jeřábek et al. Collection of datasets with DNS over HTTPS traffic. Data in Brief, 42:108310, 2022
    dos.csv Binary detection of DoS Nickolaos Koroniotis et al. Towards the development of realistic botnet dataset in the Internet of Things for network forensic analytics: Bot-IoT dataset. Future Gener. Comput. Syst., 100:779–796, 2019.
    edge_iiot_binary.csv Binary detection of IoT malware Mohamed Amine Ferrag et al. Edge-iiotset: A new comprehensive realistic cyber security dataset of iot and iiot applications: Centralized and federated learning, 2022.
    edge_iiot_multiclass.csvMulti-class classification of IoT malwareMohamed Amine Ferrag et al. Edge-iiotset: A new comprehensive realistic cyber security dataset of iot and iiot applications: Centralized and federated learning, 2022.
    https_brute_force.csvBinary detection of HTTPS Brute ForceJan Luxemburk et al. HTTPS Brute-force dataset with extended network flows, November 2020
    ids_cic_binary.csvBinary detection of intrusion in IDSIman Sharafaldin et al. Toward generating a new intrusion detection dataset and intrusion traffic characterization. ICISSp, 1:108–116, 2018.
    ids_cic_multiclass.csv Multi-class classification of intrusion in IDS Iman Sharafaldin et al. Toward generating a new intrusion detection dataset and intrusion traffic characterization. ICISSp, 1:108–116, 2018.
    ids_unsw_nb_15_binary.csv Binary detection of intrusion in IDS Nour Moustafa and Jill Slay. Unsw-nb15: a comprehensive data set for network intrusion detection systems (unsw-nb15 network data set). In 2015 military communications and information systems conference (MilCIS), pages 1–6. IEEE, 2015.
    ids_unsw_nb_15_multiclass.csv Multi-class classification of intrusion in IDS Nour Moustafa and Jill Slay. Unsw-nb15: a comprehensive data set for network intrusion detection systems (unsw-nb15 network data set). In 2015 military communications and information systems conference (MilCIS), pages 1–6. IEEE, 2015.
    iot_23.csv Binary detection of IoT malware Sebastian Garcia et al. IoT-23: A labeled dataset with malicious and benign IoT network traffic, January 2020. More details here https://www.stratosphereips.org /datasets-iot23
    ton_iot_binary.csv Binary detection of IoT malware Nour Moustafa. A new distributed architecture for evaluating ai-based security systems at the edge: Network ton iot datasets. Sustainable Cities and Society, 72:102994, 2021
    ton_iot_multiclass.csv Multi-class classification of IoT malware Nour Moustafa. A new distributed architecture for evaluating ai-based security systems at the edge: Network ton iot datasets. Sustainable Cities and Society, 72:102994, 2021
    tor_binary.csv Binary detection of TOR Arash Habibi Lashkari et al. Characterization of Tor Traffic using Time based Features. In ICISSP 2017, pages 253–262. SciTePress, 2017.
    tor_multiclass.csv Multi-class classification of TOR Arash Habibi Lashkari et al. Characterization of Tor Traffic using Time based Features. In ICISSP 2017, pages 253–262. SciTePress, 2017.
    vpn_iscx_binary.csv Binary detection of VPN Gerard Draper-Gil et al. Characterization of Encrypted and VPN Traffic Using Time-related. In ICISSP, pages 407–414, 2016.
    vpn_iscx_multiclass.csv Multi-class classification of VPN Gerard Draper-Gil et al. Characterization of Encrypted and VPN Traffic Using Time-related. In ICISSP, pages 407–414, 2016.
    vpn_vnat_binary.csv Binary detection of VPN Steven Jorgensen et al. Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification. CoRR, abs/2205.05628, 2022
    vpn_vnat_multiclass.csvMulti-class classification of VPN Steven Jorgensen et al. Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification. CoRR, abs/2205.05628, 2022

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data.brla.gov (2025). Website Analytics [Dataset]. https://catalog.data.gov/dataset/website-analytics-89ba5

Website Analytics

Explore at:
Dataset updated
Jun 29, 2025
Dataset provided by
data.brla.gov
Description

Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

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