92 datasets found
  1. a

    Traffic Site

    • hub.arcgis.com
    • data-waikatolass.opendata.arcgis.com
    • +1more
    Updated Sep 9, 2021
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    Hamilton City Council (2021). Traffic Site [Dataset]. https://hub.arcgis.com/maps/hcc::traffic-site
    Explore at:
    Dataset updated
    Sep 9, 2021
    Dataset authored and provided by
    Hamilton City Council
    License

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

    Description

    Attributes of sites in Hamilton City which collect anonymised data from a sample of vehicles. Note: A Link is the section of the road between two sites

    Column_InfoSite_Id, int : Unique identiferNumber, int : Asset number. Note: If the site is at a signalised intersection, Number will match 'Site_Number' in the table 'Traffic Signal Site Location'Is_Enabled, varchar : Site is currently enabledDisabled_Date, datetime : If currently disabled, the date at which the site was disabledSite_Name, varchar : Description of the site locationLatitude, numeric : North-south geographic coordinatesLongitude, numeric : East-west geographic coordinates

    Relationship
    
    
    
    
    
    
    
    
    
    Disclaimer
    
    Hamilton City Council does not make any representation or give any warranty as to the accuracy or exhaustiveness of the data released for public download. Levels, locations and dimensions of works depicted in the data may not be accurate due to circumstances not notified to Council. A physical check should be made on all levels, locations and dimensions before starting design or works.
    
    Hamilton City Council shall not be liable for any loss, damage, cost or expense (whether direct or indirect) arising from reliance upon or use of any data provided, or Council's failure to provide this data.
    
    While you are free to crop, export and re-purpose the data, we ask that you attribute the Hamilton City Council and clearly state that your work is a derivative and not the authoritative data source. Please include the following statement when distributing any work derived from this data:
    
    ‘This work is derived entirely or in part from Hamilton City Council data; the provided information may be updated at any time, and may at times be out of date, inaccurate, and/or incomplete.'
    
  2. 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
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    Dataset updated
    Jun 12, 2024
    Dataset provided by
    Homan, Sophia
    Chan-Tin, Eric
    Honig, Joshua
    Moran, Madeline
    Soni, Shreena
    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.

  3. 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.

  4. W

    Website Visitor Tracking Software Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Apr 25, 2025
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    Archive Market Research (2025). Website Visitor Tracking Software Report [Dataset]. https://www.archivemarketresearch.com/reports/website-visitor-tracking-software-561091
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    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. 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
    Marshall Islands, Bermuda, Congo, Bosnia and Herzegovina, South Africa, El Salvador, Finland, Nauru, Montserrat, Sri Lanka
    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

  6. Global share of human and bot web traffic 2013-2023

    • statista.com
    Updated Dec 10, 2024
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    Statista (2024). Global share of human and bot web traffic 2013-2023 [Dataset]. https://www.statista.com/statistics/1264226/human-and-bot-web-traffic-share/
    Explore at:
    Dataset updated
    Dec 10, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In 2023, most of the global website traffic was still generated by humans but bot traffic is constantly growing. Fraudulent traffic through bad bot actors accounted for 32 percent of global web traffic in the most recently measured period, representing an increase of 1.8 percent from the previous year. Sophistication of Bad Bots on the rise The complexity of malicious bot activity has dramatically increased in recent years. Advanced bad bots have doubled in prevalence over the past two years, indicating a surge in the sophistication of cyber threats. Simultaneously, simple bad bots saw a 6 percent increase compared to the previous year, suggesting a shift in the landscape of automated threats. Meanwhile, areas like entertainment, and law & government face the highest amount of advanced bad bots, with more than 78 percent of their bot traffic affected by evasive applications. Good and bad bots across industries The impact of bot traffic varies across different sectors. Bad bots accounted for over 57.2 percent of the gaming segment's web traffic. Meanwhile, almost half of the online traffic for telecom and ISPs was moved by malicious applications. However, not all bot traffic is considered bad. Some of these applications help index websites for search engines or monitor website performance, assisting users throughout their online search. Therefore, areas like entertainment, food and groceries, and financial services experienced notable levels of good bot traffic, demonstrating the diverse applications of benign automated systems across different sectors.

  7. 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.

  8. 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.

  9. World Traffic Web Map

    • walmart-event-collaboration-portal-walmarttech.hub.arcgis.com
    Updated Jun 18, 2021
    + more versions
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    Walmart Emergency Management (2021). World Traffic Web Map [Dataset]. https://walmart-event-collaboration-portal-walmarttech.hub.arcgis.com/maps/world-traffic-web-map
    Explore at:
    Dataset updated
    Jun 18, 2021
    Dataset provided by
    Walmarthttp://walmart.com/
    Authors
    Walmart Emergency Management
    Area covered
    Description

    This is a dynamic traffic map service with capabilities for visualizing traffic speeds relative to free-flow speeds as well as traffic incidents which can be visualized and identified. The traffic data is updated every five minutes. Traffic speeds are displayed as a percentage of free-flow speeds, which is frequently the speed limit or how fast cars tend to travel when unencumbered by other vehicles. The streets are color coded as follows:Green (fast): 85 - 100% of free flow speedsYellow (moderate): 65 - 85%Orange (slow); 45 - 65%Red (stop and go): 0 - 45%Esri's historical, live, and predictive traffic feeds come directly from HERE (www.HERE.com). HERE collects billions of GPS and cell phone probe records per month and, where available, uses sensor and toll-tag data to augment the probe data collected. An advanced algorithm compiles the data and computes accurate speeds. Historical traffic is based on the average of observed speeds over the past three years. The live and predictive traffic data is updated every five minutes through traffic feeds. The color coded traffic map layer can be used to represent relative traffic speeds; this is a common type of a map for online services and is used to provide context for routing, navigation and field operations. The traffic map layer contains two sublayers: Traffic and Live Traffic. The Traffic sublayer (shown by default) leverages historical, live and predictive traffic data; while the Live Traffic sublayer is calculated from just the live and predictive traffic data only. A color coded traffic map image can be requested for the current time and any time in the future. A map image for a future request might be used for planning purposes. The map layer also includes dynamic traffic incidents showing the location of accidents, construction, closures and other issues that could potentially impact the flow of traffic. Traffic incidents are commonly used to provide context for routing, navigation and field operations. Incidents are not features; they cannot be exported and stored for later use or additional analysis. The service works globally and can be used to visualize traffic speeds and incidents in many countries. Check the service coverage web map to determine availability in your area of interest. In the coverage map, the countries color coded in dark green support visualizing live traffic. The support for traffic incidents can be determined by identifying a country. For detailed information on this service, including a data coverage map, visit the directions and routing documentation and ArcGIS Help.

  10. e

    outage.report Traffic Analytics Data

    • analytics.explodingtopics.com
    Updated May 1, 2025
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    (2025). outage.report Traffic Analytics Data [Dataset]. https://analytics.explodingtopics.com/website/outage.report
    Explore at:
    Dataset updated
    May 1, 2025
    Variables measured
    Global Rank, Monthly Visits, Authority Score, US Country Rank
    Description

    Traffic analytics, rankings, and competitive metrics for outage.report as of May 2025

  11. W

    Customs and Border Protection Network Web Trends Server Master Dataset

    • cloud.csiss.gmu.edu
    Updated Mar 6, 2021
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    United States (2021). Customs and Border Protection Network Web Trends Server Master Dataset [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/customs-and-border-protection-network-web-trends-server-master-dataset
    Explore at:
    Dataset updated
    Mar 6, 2021
    Dataset provided by
    United States
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    The CBPnet Web Trends Server is a COTS report generation product uses proprietary data storage and standard web server logs as input and supports the Office of Public Affairs in providing advanced reports for web traffic analysis for CBPnet and related web sites. It utilizes product specific database to support it's functionality.

  12. Most visited websites Thailand 2023, by monthly traffic

    • statista.com
    Updated Feb 26, 2024
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    Statista (2024). Most visited websites Thailand 2023, by monthly traffic [Dataset]. https://www.statista.com/statistics/1097824/thailand-most-visited-websites-by-monthly-traffic/
    Explore at:
    Dataset updated
    Feb 26, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2022 - Nov 2023
    Area covered
    Thailand
    Description

    According to a report published by DataReportal, as of November 2023, the most visited website in Thailand was Google.com with approximately 885 million monthly visits. This was followed by Youtube.com with around 456 million monthly visits in that year.

  13. 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.

  14. Leading website traffic in Kenya 2021, by device

    • statista.com
    Updated Jun 11, 2025
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    Statista (2025). Leading website traffic in Kenya 2021, by device [Dataset]. https://www.statista.com/statistics/1316963/web-traffic-distribution-of-leading-websites-in-kenya-by-device/
    Explore at:
    Dataset updated
    Jun 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2021
    Area covered
    Kenya
    Description

    In November 2021, mobile devices accounted for nearly 80 percent of the web traffic to Google.com in Kenya. The website had the highest number of total visits in the country. Among the leading websites, most of them had a higher share of traffic from mobile. Youtube.com was an exception, with only one-third of its traffic originating from mobile devices.

  15. Global Network Traffic Analytics Market 2018-2022

    • technavio.com
    Updated Jun 21, 2018
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    Technavio (2018). Global Network Traffic Analytics Market 2018-2022 [Dataset]. https://www.technavio.com/report/global-network-traffic-analytics-market-analysis-share-2018
    Explore at:
    Dataset updated
    Jun 21, 2018
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Global
    Description

    Snapshot img

    Global network traffic analytics Industry Overview

    Technavio’s analysts have identified the increasing use of network traffic analytics solutions to be one of major factors driving market growth. With the rapidly changing IT infrastructure, security hackers can steal valuable information through various modes. With the increasing dependence on web applications and websites for day-to-day activities and financial transactions, the instances of theft have increased globally. Also, the emergence of social networking websites has aided the malicious attackers to extract valuable information from vulnerable users. The increasing consumer dependence on web applications and websites for day-to-day activities and financial transactions are further increasing the risks of theft. This encourages the organizations to adopt network traffic analytics solutions.

    Want a bigger picture? Try a FREE sample of this report now!

    See the complete table of contents and list of exhibits, as well as selected illustrations and example pages from this report.

    Companies covered

    The network traffic analytics market is fairly concentrated due to the presence of few established companies offering innovative and differentiated software and services. By offering a complete analysis of the competitiveness of the players in the network monitoring tools market offering varied software and services, this network traffic analytics industry analysis report will aid clients identify new growth opportunities and design new growth strategies.

    The report offers a complete analysis of a number of companies including:

    Allot
    Cisco Systems
    IBM
    Juniper Networks
    Microsoft
    Symantec
    

    Network traffic analytics market growth based on geographic regions

    Americas
    APAC
    EMEA
    

    With a complete study of the growth opportunities for the companies across regions such as the Americas, APAC, and EMEA, our industry research analysts have estimated that countries in the Americas will contribute significantly to the growth of the network monitoring tools market throughout the predicted period.

    Network traffic analytics market growth based on end-user

    Telecom
    BFSI
    Healthcare
    Media and entertainment
    

    According to our market research experts, the telecom end-user industry will be the major end-user of the network monitoring tools market throughout the forecast period. Factors such as increasing use of network traffic analytics solutions and increasing use of mobile devices at workplaces will contribute to the growth of the market shares of the telecom industry in the network traffic analytics market.

    Key highlights of the global network traffic analytics market for the forecast years 2018-2022:

    CAGR of the market during the forecast period 2018-2022
    Detailed information on factors that will accelerate the growth of the network traffic analytics market during the next five years
    Precise estimation of the global network traffic analytics market size and its contribution to the parent market
    Accurate predictions on upcoming trends and changes in consumer behavior
    Growth of the network traffic analytics industry across various geographies such as the Americas, APAC, and EMEA
    A thorough analysis of the market’s competitive landscape and detailed information on several vendors
    Comprehensive information about factors that will challenge the growth of network traffic analytics companies
    

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    This market research report analyzes the market outlook and provides a list of key trends, drivers, and challenges that are anticipated to impact the global network traffic analytics market and its stakeholders over the forecast years.

    The global network traffic analytics market analysts at Technavio have also considered how the performance of other related markets in the vertical will impact the size of this market till 2022. Some of the markets most likely to influence the growth of the network traffic analytics market over the coming years are the Global Network as a Service Market and the Global Data Analytics Outsourcing Market.

    Technavio’s collection of market research reports offer insights into the growth of markets across various industries. Additionally, we also provide customized reports based on the specific requirement of our clients.

  16. Share of website traffic from mobile phones Thailand 2020, by website

    • statista.com
    Updated Dec 14, 2022
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    Statista (2022). Share of website traffic from mobile phones Thailand 2020, by website [Dataset]. https://www.statista.com/statistics/1253279/thailand-share-of-website-traffic-from-mobile-phones-by-website/
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    Dataset updated
    Dec 14, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2020
    Area covered
    Thailand
    Description

    According to a report published by DataReportal, the share of website traffic from mobile phones for gool.in.th accounted for around 95.1 percent among other devices in Thailand in December 2020. Meanwhile, the share of web traffic on computers for the same website accounted for only five percent.

  17. s

    Traffic Volumes from SCATS Traffic Management System Jul-Dec 2024 DCC -...

    • data.smartdublin.ie
    Updated Dec 31, 2024
    + more versions
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    (2024). Traffic Volumes from SCATS Traffic Management System Jul-Dec 2024 DCC - Dataset - data.smartdublin.ie [Dataset]. https://data.smartdublin.ie/dataset/dcc-scats-detector-volume-jul-dec-2024
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    Dataset updated
    Dec 31, 2024
    License

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

    Description

    Traffic volumes data across Dublin City from the SCATS traffic management system. The Sydney Coordinated Adaptive Traffic System (SCATS) is an intelligent transportation system used to manage timing of signal phases at traffic signals. SCATS uses sensors at each traffic signal to detect vehicle presence in each lane and pedestrians waiting to cross at the local site. The vehicle sensors are generally inductive loops installed within the road. 3 resources are provided: SCATS Traffic Volumes Data (Monthly) Contained in this report are traffic counts taken from the SCATS traffic detectors located at junctions. The primary function for these traffic detectors is for traffic signal control. Such devices can also count general traffic volumes at defined locations on approach to a junction. These devices are set at specific locations on approaches to the junction but may not be on all approaches to a junction. As there are multiple junctions on any one route, it could be expected that a vehicle would be counted multiple times as it progress along the route. Thus the traffic volume counts here are best used to represent trends in vehicle movement by selecting a specific junction on the route which best represents the overall traffic flows. Information provided: End Time: time that one hour count period finishes. Region: location of the detector site (e.g. North City, West City, etc). Site: this can be matched with the SCATS Sites file to show location Detector: the detectors/ sensors at each site are numbered Sum volume: total traffic volumes in preceding hour Avg volume: average traffic volumes per 5 minute interval in preceding hour All Dates Traffic Volumes Data This file contains daily totals of traffic flow at each site location. SCATS Site Location Data Contained in this report, the location data for the SCATS sites is provided. The meta data provided includes the following; Site id – This is a unique identifier for each junction on SCATS Site description( CAP) – Descriptive location of the junction containing street name(s) intersecting streets Site description (lower) - – Descriptive location of the junction containing street name(s) intersecting streets Region – The area of the city, adjoining local authority, region that the site is located LAT/LONG – Coordinates Disclaimer: the location files are regularly updated to represent the locations of SCATS sites under the control of Dublin City Council. However site accuracy is not absolute. Information for LAT/LONG and region may not be available for all sites contained. It is at the discretion of the user to link the files for analysis and to create further data. Furthermore, detector communication issues or faulty detectors could also result in an inaccurate result for a given period, so values should not be taken as absolute but can be used to indicate trends.

  18. s

    Data from: Traffic Volumes

    • data.sandiego.gov
    Updated Jul 29, 2016
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    (2016). Traffic Volumes [Dataset]. https://data.sandiego.gov/datasets/traffic-volumes/
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    csv csv is tabular data. excel, google docs, libreoffice calc or any plain text editor will open files with this format. learn moreAvailable download formats
    Dataset updated
    Jul 29, 2016
    Description

    The census count of vehicles on city streets is normally reported in the form of Average Daily Traffic (ADT) counts. These counts provide a good estimate for the actual number of vehicles on an average weekday at select street segments. Specific block segments are selected for a count because they are deemed as representative of a larger segment on the same roadway. ADT counts are used by transportation engineers, economists, real estate agents, planners, and others professionals for planning and operational analysis. The frequency for each count varies depending on City staff’s needs for analysis in any given area. This report covers the counts taken in our City during the past 12 years approximately.

  19. W

    Website Analytics Tool Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated May 17, 2025
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    Archive Market Research (2025). Website Analytics Tool Report [Dataset]. https://www.archivemarketresearch.com/reports/website-analytics-tool-559436
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    ppt, pdf, docAvailable download formats
    Dataset updated
    May 17, 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 tool market is experiencing robust growth, driven by the increasing need for businesses of all sizes to understand their online audience and optimize their digital strategies. The market, valued at approximately $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This substantial growth is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability, cost-effectiveness, and accessibility for businesses, regardless of their technical expertise. Furthermore, the expanding use of mobile devices and the proliferation of data are creating a surge in demand for sophisticated analytics tools capable of providing real-time insights into user behavior, campaign performance, and website effectiveness. The market is segmented by deployment (cloud-based and on-premises) and user type (SMEs and large enterprises), with the cloud-based segment dominating due to its inherent advantages. Competitive pressures are intensifying, with established players like Google Analytics and Adobe Analytics facing competition from agile startups offering innovative features and pricing models. While data privacy concerns and the complexity of implementing and interpreting analytics data pose challenges, the overall market trajectory remains overwhelmingly positive, underpinned by continued digital transformation across industries and a growing awareness of the importance of data-driven decision-making. The regional distribution of the market reflects the global landscape of digital adoption, with North America and Europe currently holding significant market shares. However, the Asia-Pacific region is expected to witness the fastest growth in the coming years, driven by rapid economic development and increasing internet penetration. This presents substantial opportunities for both established players and new entrants in the market. The future will likely see further integration of website analytics with other marketing technologies, the rise of AI-powered analytics capabilities offering predictive insights, and a greater emphasis on data security and compliance. This dynamic environment necessitates continuous innovation and adaptation for businesses operating within the website analytics tool market.

  20. Global Website Traffic Analysis Tool Market Research and Development Focus...

    • statsndata.org
    excel, pdf
    Updated Jun 2025
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    Stats N Data (2025). Global Website Traffic Analysis Tool Market Research and Development Focus 2025-2032 [Dataset]. https://www.statsndata.org/report/website-traffic-analysis-tool-market-46877
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    excel, pdfAvailable download formats
    Dataset updated
    Jun 2025
    Dataset authored and provided by
    Stats N Data
    License

    https://www.statsndata.org/how-to-orderhttps://www.statsndata.org/how-to-order

    Area covered
    Global
    Description

    In today's digital landscape, the Website Traffic Analysis Tool market has emerged as an essential component for businesses aiming to enhance their online presence and optimize their digital strategies. These tools empower organizations to monitor their website performance, analyze visitor behavior, and derive actio

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Hamilton City Council (2021). Traffic Site [Dataset]. https://hub.arcgis.com/maps/hcc::traffic-site

Traffic Site

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Dataset updated
Sep 9, 2021
Dataset authored and provided by
Hamilton City Council
License

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

Description

Attributes of sites in Hamilton City which collect anonymised data from a sample of vehicles. Note: A Link is the section of the road between two sites

Column_InfoSite_Id, int : Unique identiferNumber, int : Asset number. Note: If the site is at a signalised intersection, Number will match 'Site_Number' in the table 'Traffic Signal Site Location'Is_Enabled, varchar : Site is currently enabledDisabled_Date, datetime : If currently disabled, the date at which the site was disabledSite_Name, varchar : Description of the site locationLatitude, numeric : North-south geographic coordinatesLongitude, numeric : East-west geographic coordinates

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Disclaimer

Hamilton City Council does not make any representation or give any warranty as to the accuracy or exhaustiveness of the data released for public download. Levels, locations and dimensions of works depicted in the data may not be accurate due to circumstances not notified to Council. A physical check should be made on all levels, locations and dimensions before starting design or works.

Hamilton City Council shall not be liable for any loss, damage, cost or expense (whether direct or indirect) arising from reliance upon or use of any data provided, or Council's failure to provide this data.

While you are free to crop, export and re-purpose the data, we ask that you attribute the Hamilton City Council and clearly state that your work is a derivative and not the authoritative data source. Please include the following statement when distributing any work derived from this data:

‘This work is derived entirely or in part from Hamilton City Council data; the provided information may be updated at any time, and may at times be out of date, inaccurate, and/or incomplete.'
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