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By installing the resolve pixel onto your website, business owners can start to put a name to the activity seen in analytics sources (i.e. GA4). With capture/resolve, you can identify up to 40% or more of your website traffic. Reach customers BEFORE they are ready to reveal themselves to you and customize messaging toward the right product or service.

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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.

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.'

Between July and September 2022, BYJU's emerged as the top Ed Tech platform for K12 and test preparation In India. It recorded approximately *** million website visits. Following closely behind was Toppr.com, with around *** million visits during the same period.

In November 2021, mobile devices accounted for nearly ** 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 ********* of its traffic originating from mobile devices.

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.

In the month of January 2024, the beauty and personal care retailer Nykaa had about **** million website visits. In comparison, the month of December in 2023 clocked over ten million monthly website visits.

The global website speed and performance test tool market size was valued at USD 1.84 billion in 2022 and is projected to reach USD 5.52 billion by 2033, exhibiting a CAGR of 12.0% during the forecast period. The escalating demand for website performance optimization services, the surge in website traffic, and the proliferation of mobile devices drive market growth. Moreover, the growing adoption of cloud-based solutions and the increasing preference for online shopping fuel market expansion. Key players in the website speed and performance test tool market include Pingdom, Yellow Lab Tools, Alerta, Sematext, Domsignal, Dareboost, New Relic, Google PageSpeed Insights, KeyCDN Website Speed Test, Yslow, Uptrends, GTmetrix, Site24x7, Datadog, Catchpoint WebPageTest, Dotcom-Monitor, Lighthouse, WebPagetest, and Load Impact. These companies are focusing on offering advanced features and enhancing the capabilities of their tools to gain a competitive edge. The market is fragmented, with several players offering a wide range of solutions catering to different customer needs and industries.

Website Down Checker Market Overview: The global website down checker market is expected to reach a value of approximately USD 65.6 million by 2033, exhibiting a CAGR of 6.7% during the forecast period (2025-2033). This growth can be attributed to the increasing reliance on websites for business operations and online transactions, coupled with the growing prevalence of sophisticated cyber threats. The demand for website down checkers is also driven by the need for proactive monitoring and rapid response to website outages. Cloud-based solutions are gaining traction due to their flexibility, scalability, and cost-effectiveness. The market is segmented based on type (cloud-based and on-premises) and application (personal and enterprise). Competitive Landscape and Regional Insights: Major players in the website down checker market include: • Website Down Checker • Website Status Checker • IsSiteDown.co.uk • Downdetector • Is My Website Down • Domsignal • Is Site Down • OnlineOrNot • Uptrends • Site24x7 Check Website Availability North America is expected to retain its dominant position in the market due to the high adoption of advanced technologies and stringent data privacy regulations. The Asia Pacific region is projected to exhibit significant growth potential due to the rapidly expanding digital landscape and increasing awareness about the importance of website uptime. Key factors shaping the market include the rise of mobile internet, growing adoption of the Internet of Things (IoT), and the need for ensuring uninterrupted online services.

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

Valuation Office Website Traffic and Stats . Published by Tailte Éireann – Surveying. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).This dataset provides the number of users to the Valuation Office website....

The website speed test market has witnessed significant growth, reaching a market size of XXX million in 2025. This growth is primarily attributed to the increasing demand for faster and more reliable internet speeds, driven by the widespread adoption of streaming video, online gaming, and cloud-based applications. The CAGR of the market is projected to remain strong over the forecast period from 2023 to 2033, reaching a value of XXX million by 2033. Key market trends include the growing adoption of 5G networks and the increasing popularity of fiber optic internet, both of which offer significantly faster speeds compared to traditional copper-based connections. In terms of segmentation, the market for website speed test can be divided into two main types: cable internet and fiber optic internet. Cable internet is currently the most widely used type of broadband internet connection, but fiber optic internet is rapidly gaining popularity due to its superior speed and reliability. Other types of broadband internet connections include fixed wireless internet, satellite internet, and DSL internet. The market can also be segmented based on its application, with individuals and businesses being the two primary user groups. Businesses typically require faster and more reliable internet speeds than individuals, and are therefore more likely to invest in higher-end solutions such as fiber optic internet. Major companies in the website speed test market include Fusion Connect, Bandwidth Place, Ookla, Netflix, and Measurement Lab, among others.

This Website Statistics dataset has four resources showing usage of the Lincolnshire Open Data website. Web analytics terms used in each resource are defined in their accompanying Metadata file.

• Website Usage Statistics: This document shows a statistical summary of usage of the Lincolnshire Open Data site for the latest calendar year.

• Website Statistics Summary: This dataset shows a website statistics summary for the Lincolnshire Open Data site for the latest calendar year.

• Webpage Statistics: This dataset shows statistics for individual Webpages on the Lincolnshire Open Data site by calendar year.

• Dataset Statistics: This dataset shows cumulative totals for Datasets on the Lincolnshire Open Data site that have also been published on the national Open Data site Data.Gov.UK - see the Source link.

  Note: Website and Webpage statistics (the first three resources above) show only UK users, and exclude API calls (automated requests for datasets). The Dataset Statistics are confined to users with javascript enabled, which excludes web crawlers and API calls.

These Website Statistics resources are updated annually in January by the Lincolnshire County Council Business Intelligence team. For any enquiries about the information contact opendata@lincolnshire.gov.uk.

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 speeds Yellow (moderate): 65 - 85% Orange (slow); 45 - 65% Red (stop and go): 0 - 45%Esri's historical, live, and predictive traffic feeds come directly from TomTom (www.tomtom.com). Historical traffic is based on the average of observed speeds over the past year. 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.

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?

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.

Backlink Checker Tool Market Outlook

The global backlink checker tool market size was valued at approximately USD 2.1 billion in 2023 and is expected to reach USD 4.5 billion by 2032, expanding at a CAGR of 8.1% during the forecast period. The growth factor driving this market includes the increasing importance of search engine optimization (SEO) in digital marketing strategies and the need for businesses to maintain a competitive edge in their online presence.

One of the primary growth factors for the backlink checker tool market is the rising significance of SEO in the modern digital marketing landscape. As businesses increasingly rely on their online presence to attract and retain customers, the role of backlinks in improving website rankings on search engines like Google has become crucial. High-quality backlinks are recognized by search engines as a sign of a website's authority and relevance, thus directly impacting search engine rankings. This has led to a surge in demand for tools that can analyze and optimize backlinks, fueling the growth of the backlink checker tool market.

Another key driver for this market is the proliferation of digital content and the increasing number of websites and online platforms. With the internet becoming an integral part of daily life, businesses across various sectors are investing heavily in their digital marketing efforts. Backlink checker tools help these businesses monitor and analyze their backlink profiles, identify potential issues, and devise strategies to improve their SEO performance. This growing focus on digital marketing and SEO is expected to continue driving the demand for backlink checker tools in the coming years.

The growing competition among businesses to achieve higher search engine rankings is also a significant growth factor for the backlink checker tool market. As more companies recognize the importance of SEO in driving organic traffic and enhancing brand visibility, they are increasingly adopting backlink checker tools to gain insights into their backlink profiles and benchmark their performance against competitors. This competitive landscape is fostering innovation and advancements in backlink checker tools, further propelling market growth.

Regionally, North America is expected to dominate the backlink checker tool market during the forecast period, owing to the high adoption rate of advanced digital marketing strategies and the presence of numerous SEO agencies and tech-savvy enterprises. The region's strong emphasis on online business and the significant investments in digital marketing technologies are driving the demand for backlink checker tools. Furthermore, the growing awareness of the importance of backlinks in SEO among businesses in Europe and the Asia Pacific region is also contributing to the market's growth. These regions are witnessing increased adoption of backlink checker tools as companies strive to enhance their online presence and compete effectively in the global market.

Component Analysis

In the backlink checker tool market, the component segment is divided into software and services. The software segment accounts for the largest share of this market due to the increasing demand for advanced tools that offer comprehensive analysis and reporting capabilities. Backlink checker software helps users analyze the quality and quantity of backlinks, identify potential issues, and develop effective link-building strategies. These tools are continually evolving, incorporating new features such as artificial intelligence and machine learning to provide more accurate and insightful analyses.

The services segment, although smaller in comparison to the software segment, is also witnessing significant growth. This can be attributed to the growing need for professional SEO services, including consultancy, training, and technical support. SEO agencies and freelancers often require specialized services to optimize their backlink profiles and improve their clients' search engine rankings. As businesses increasingly outsource their SEO needs to external experts, the demand for backlink checker services is expected to rise accordingly.

Moreover, the integration of backlink checker tools with other digital marketing software is another factor driving the growth of the software segment. Many businesses prefer integrated solutions that offer a holistic view of their digital marketing efforts, including SEO, social media, and content marketing. By incorporating backlink checker functionalities into comprehensive digital marketing platforms,

The website speed and performance testing tool market is experiencing robust growth, driven by the increasing importance of website speed for user experience, SEO rankings, and overall business success. The market, estimated at $2 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $6 billion by 2033. This growth is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting both personal and enterprise users. Furthermore, the increasing complexity of websites and the growing reliance on mobile devices necessitate sophisticated testing tools to ensure optimal performance across various platforms and browsers. The competitive landscape is dynamic, with established players like Pingdom and New Relic alongside emerging innovative solutions. The market is segmented by application (personal, enterprise, other) and type (cloud-based, on-premises), with cloud-based solutions dominating due to their accessibility and flexible pricing models. Geographic expansion is also a significant driver, with North America and Europe currently holding the largest market share, but Asia-Pacific showing strong potential for future growth fueled by increasing internet penetration and e-commerce activity. The market's restraints primarily involve the initial investment costs associated with implementing advanced testing tools and the need for technical expertise to effectively utilize these solutions. However, the long-term benefits significantly outweigh these initial challenges, leading to continued market expansion. The market’s segmentation into cloud-based and on-premises solutions reflects the ongoing shift towards cloud adoption. Cloud-based tools offer advantages such as easy accessibility, automatic updates, and scalability, making them attractive to a wide range of users. The enterprise segment is a major contributor to market revenue, driven by the need for comprehensive performance monitoring and optimization of business-critical websites. The diverse range of tools available caters to various user needs and technical expertise, from simple speed tests for individual websites to sophisticated platforms for large-scale performance monitoring. The ongoing development of innovative features, such as AI-powered performance analysis and automated testing, will further drive market growth. Competition among vendors is fierce, leading to continuous improvements in the functionality and user experience of these testing tools. Therefore, the website speed and performance testing tool market represents a significant and rapidly evolving sector with substantial opportunities for growth and innovation in the coming years.

Our Web Data dataset includes such data points as company name, location, headcount, industry, and size, among others. It offers extensive fresh and historical data, including even companies that operate in stealth mode.

For lead generation

With millions of companies worldwide, Web Company Database helps you filter potential clients based on custom criteria and speed up the conversion process.

Use cases

1. Filter potential clients according to location, size, and other criteria
2. Enrich your existing database
3. Improve conversion rates
4. Use predictive models to identify potential leads
5. Group your leads in segments for more accurate targeting

For market and business analysis

Our Web Company Data provides information about millions of companies, allowing you to find your competitors and see their weaknesses and strengths.

Use cases

1. Pinpoint your competitors
2. Learn about your competitors' size, headcount, and revenue
3. Prepare a data-driven plan for the next quarter

For Investors

We recommend B2B Web Data for investors to discover and evaluate businesses with the highest potential.

Gain strategic business insights, enhance decision-making, and maintain algorithms that signal investment opportunities with Coresignal’s global B2B Web Dataset.

Use cases

1. Screen startups and industries showing early signs of growth
2. Identify companies hungry for the next investment
3. Check if a startup is about to reach the next maturity phase
4. Identify and predict a startup's potential at the founding moment
5. Choose companies that fit you in terms of size and headcount

For sales prospecting

B2B Web Database saves time your employees would otherwise use to search for potential clients manually.

Use cases

1. Make a short list of the top prospects
2. Define which companies are large or small enough to buy your product
3. Based on the revenue, determine which companies are ready to convert
4. Sort the companies by their distance from your warehouse to draw a line where selling won't result in satisfactory profit

The global market for Website Accessibility Evaluation Tools is experiencing robust growth, projected to reach $178 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 7.2% from 2025 to 2033. This expansion is fueled by several key factors. Increasing regulatory pressure to comply with accessibility standards like WCAG (Web Content Accessibility Guidelines) is a primary driver, compelling businesses of all sizes to invest in tools ensuring digital inclusivity. Furthermore, growing awareness of the ethical and business benefits of website accessibility, including broader audience reach and improved brand reputation, is significantly impacting market demand. The rising adoption of cloud-based solutions offers scalability and cost-effectiveness, further accelerating market growth. Segment-wise, the large enterprise sector currently dominates, driven by their greater resources and complex website architectures demanding comprehensive accessibility assessments. However, the SME (Small and Medium-sized Enterprises) segment shows significant potential for future growth as awareness increases and user-friendly, affordable solutions emerge. Geographical analysis reveals strong market presence in North America and Europe, with substantial growth opportunities anticipated in the Asia-Pacific region, particularly in rapidly developing economies like India and China. The competitive landscape is marked by a mix of established players and emerging startups. While companies like Equalweb and UserWay hold significant market share, the market's relatively nascent stage presents opportunities for new entrants offering innovative solutions and specialized services. Future growth will likely be shaped by advancements in Artificial Intelligence (AI) and Machine Learning (ML) technologies, enabling more accurate and efficient accessibility audits. The continued evolution of accessibility standards and increasing user expectations for seamless digital experiences will also play a crucial role in shaping the market's trajectory. The focus on proactive accessibility implementation, moving beyond reactive compliance, suggests a sustained period of strong growth within this vital sector.