80 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or in part from Hamilton City Council data; the provided information may be updated at any time, and may at times be out of date, inaccurate, and/or incomplete.'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
    Explore at:
    Dataset updated
    Jun 12, 2024
    Dataset provided by
    Homan, Sophia
    Moran, Madeline
    Honig, Joshua
    Ferrell, Nathan
    Chan-Tin, Eric
    Soni, Shreena
    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. 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.

  4. 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, Sri Lanka, Finland, El Salvador, South Africa, Nauru, 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

  5. Impact of AI on website traffic anticipated by digital marketers worldwide...

    • statista.com
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    Statista, Impact of AI on website traffic anticipated by digital marketers worldwide 2023 [Dataset]. https://www.statista.com/statistics/1410386/impact-ai-website-traffic-worldwide/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Worldwide
    Description

    According to the results of a survey conducted worldwide in 2023, nearly **** of responding digital marketers believed artificial intelligence (AI) would have a positive impact on website search traffic in the next five years. Some ** percent stated AI would have a neutral effect, while ** percent agreed that the technology would negatively impact search traffic.

  6. 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.

  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 web traffic in Morocco 2025, by search engine

    • statista.com
    Updated Apr 23, 2025
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    Statista (2025). Share of web traffic in Morocco 2025, by search engine [Dataset]. https://www.statista.com/statistics/1365083/share-of-web-traffic-in-morocco-by-search-engine/
    Explore at:
    Dataset updated
    Apr 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    Morocco
    Description

    In 2025, Google was the most used search engine in Morocco, accounting for nearly 97 percent of the web traffic. The next most used search engine was Bing, which made up over two percent of web traffic in Morocco. The number of people using the internet in Morocco stood at 35.3 million in 2025, the fifth highest amount of internet users in Africa.

  9. d

    Swash Web Browsing Clickstream Data - 1.5M Worldwide Users - GDPR Compliant

    • datarade.ai
    .csv, .xls
    Updated Jun 27, 2023
    + more versions
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    Swash (2023). Swash Web Browsing Clickstream Data - 1.5M Worldwide Users - GDPR Compliant [Dataset]. https://datarade.ai/data-products/swash-blockchain-bitcoin-and-web3-enthusiasts-swash
    Explore at:
    .csv, .xlsAvailable download formats
    Dataset updated
    Jun 27, 2023
    Dataset authored and provided by
    Swash
    Area covered
    Jordan, Saint Vincent and the Grenadines, Belarus, Jamaica, India, Uzbekistan, Latvia, Liechtenstein, Russian Federation, Monaco
    Description

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

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

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

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

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

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

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

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

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

  10. Total global visitor traffic to Google.com 2024

    • statista.com
    • ai-chatbox.pro
    Updated Jan 22, 2025
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    Statista (2025). Total global visitor traffic to Google.com 2024 [Dataset]. https://www.statista.com/statistics/268252/web-visitor-traffic-to-googlecom/
    Explore at:
    Dataset updated
    Jan 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023 - Mar 2024
    Area covered
    Worldwide
    Description

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

  11. 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.

  12. 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
    

    Get more value with Technavio’s INSIGHTS subscription platform! Gain easy access to all of Technavio’s reports, along with on-demand services. Try the demo

    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.

  13. DataForSEO Labs API for keyword research and search analytics, real-time...

    • datarade.ai
    .json
    Updated Jun 4, 2021
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    DataForSEO (2021). DataForSEO Labs API for keyword research and search analytics, real-time data for all Google locations and languages [Dataset]. https://datarade.ai/data-products/dataforseo-labs-api-for-keyword-research-and-search-analytics-dataforseo
    Explore at:
    .jsonAvailable download formats
    Dataset updated
    Jun 4, 2021
    Dataset provided by
    Authors
    DataForSEO
    Area covered
    Armenia, Morocco, Cocos (Keeling) Islands, Mauritania, Micronesia (Federated States of), Tokelau, Kenya, Azerbaijan, Korea (Democratic People's Republic of), Isle of Man
    Description

    DataForSEO Labs API offers three powerful keyword research algorithms and historical keyword data:

    • Related Keywords from the “searches related to” element of Google SERP. • Keyword Suggestions that match the specified seed keyword with additional words before, after, or within the seed key phrase. • Keyword Ideas that fall into the same category as specified seed keywords. • Historical Search Volume with current cost-per-click, and competition values.

    Based on in-market categories of Google Ads, you can get keyword ideas from the relevant Categories For Domain and discover relevant Keywords For Categories. You can also obtain Top Google Searches with AdWords and Bing Ads metrics, product categories, and Google SERP data.

    You will find well-rounded ways to scout the competitors:

    • Domain Whois Overview with ranking and traffic info from organic and paid search. • Ranked Keywords that any domain or URL has positions for in SERP. • SERP Competitors and the rankings they hold for the keywords you specify. • Competitors Domain with a full overview of its rankings and traffic from organic and paid search. • Domain Intersection keywords for which both specified domains rank within the same SERPs. • Subdomains for the target domain you specify along with the ranking distribution across organic and paid search. • Relevant Pages of the specified domain with rankings and traffic data. • Domain Rank Overview with ranking and traffic data from organic and paid search. • Historical Rank Overview with historical data on rankings and traffic of the specified domain from organic and paid search. • Page Intersection keywords for which the specified pages rank within the same SERP.

    All DataForSEO Labs API endpoints function in the Live mode. This means you will be provided with the results in response right after sending the necessary parameters with a POST request.

    The limit is 2000 API calls per minute, however, you can contact our support team if your project requires higher rates.

    We offer well-rounded API documentation, GUI for API usage control, comprehensive client libraries for different programming languages, free sandbox API testing, ad hoc integration, and deployment support.

    We have a pay-as-you-go pricing model. You simply add funds to your account and use them to get data. The account balance doesn't expire.

  14. c

    Austin-Travis County Traffic Report Page

    • s.cnmilf.com
    • catalog.data.gov
    Updated Sep 25, 2024
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    data.austintexas.gov (2024). Austin-Travis County Traffic Report Page [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/austin-travis-county-traffic-report-page
    Explore at:
    Dataset updated
    Sep 25, 2024
    Dataset provided by
    data.austintexas.gov
    Area covered
    Travis County, Austin
    Description

    Contextual explainer page for the Austin-Travis County Traffic Report page

  15. 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.

  16. 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.

  17. Google Analytics Sample

    • kaggle.com
    zip
    Updated Sep 19, 2019
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    Google BigQuery (2019). Google Analytics Sample [Dataset]. https://www.kaggle.com/bigquery/google-analytics-sample
    Explore at:
    zip(0 bytes)Available download formats
    Dataset updated
    Sep 19, 2019
    Dataset provided by
    Googlehttp://google.com/
    BigQueryhttps://cloud.google.com/bigquery
    Authors
    Google BigQuery
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

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

    Content

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

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

    Fork this kernel to get started.

    Acknowledgements

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

    Banner Photo by Edho Pratama from Unsplash.

    Inspiration

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

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

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

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

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

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

    What is the sequence of pages viewed?

  18. a

    Traffic Counts Sites and Volume Data

    • l-a-mapping-services-lennoxaddington.hub.arcgis.com
    Updated Apr 2, 2019
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    County of Lennox & Addington (2019). Traffic Counts Sites and Volume Data [Dataset]. https://l-a-mapping-services-lennoxaddington.hub.arcgis.com/datasets/traffic-counts-sites-and-volume-data
    Explore at:
    Dataset updated
    Apr 2, 2019
    Dataset authored and provided by
    County of Lennox & Addington
    Description

    TERMS OF USE 1. Restriction on the use of Material on this websiteUsage and/or downloading this data indicates Your acceptance of the terms and conditions below.The data here controlled and operated by the Corporation of the County of Lennox and Addington (referred to the “County” herein) and is protected by copyright. No part of the information herein may be sold, copied, distributed, or transmitted in any form without the prior written consent of the County. All rights reserved. Copyright 2018 by the Corporation of the County of Lennox and Addington.2. DisclaimerThe County makes no representation, warranty or guarantee as to the content, accuracy, currency or completeness of any of the information provided on this website. The County explicitly disclaims any representations, warranties and guarantees, including, without limitation, the implied warranties of merchantability and fitness for a particular purpose.3. Limitation of LiabilityThe County is not responsible for any special, indirect, incidental or consequential damages that may arise from the use of or the inability to use, any web pages and/or the materials contained on the web page whether the materials are provided by the County or by a third party. Without limiting the generality of the foregoing, the County assumes no responsibility whatsoever for: any errors omissions, or inaccuracies in the information provided, regardless of how caused; or any decision made or action taken or not taken by the reader or other third party in reliance upon any information or data furnished on any web page.The Data is provided "as is" without warranty or any representation of accuracy, timeliness or completeness. The burden for determining accuracy, completeness, timeliness, merchantability and fitness for or the appropriateness for use rests solely on the requester. Lennox and Addington County makes no warranties, express or implied, as to the use of the Data. There are no implied warranties of merchantability or fitness for a particular purpose. The requester acknowledges and accepts the limitations of the Data, including the fact that the Data is dynamic and is in a constant state of maintenance, corrections and update.

  19. d

    Real-Time Traffic Incident Reports

    • catalog.data.gov
    • datahub.austintexas.gov
    • +1more
    Updated Jun 25, 2025
    + more versions
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    data.austintexas.gov (2025). Real-Time Traffic Incident Reports [Dataset]. https://catalog.data.gov/dataset/real-time-traffic-incident-reports
    Explore at:
    Dataset updated
    Jun 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    This dataset contains traffic incident information from the Austin-Travis County traffic reports collected from the various Public Safety agencies through a data feed from the Combined Transportation, Emergency, and Communications Center (CTECC). For further context, see: - Active Incidents: Map and Context - https://data.austintexas.gov/stories/s/Austin-Travis-County-Traffic-Report-Page/9qfg-4swh/ - Data Trends and Analysis - https://data.austintexas.gov/stories/s/48n7-m3me The dataset is updated every 5 minutes with the latest snapshot of active traffic incidents.

  20. 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

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

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

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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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