checker.top is ranked #60106 in US with 582.82K Traffic. Categories: . Learn more about website traffic, market share, and more!

similarweb.com is ranked #1119 in IN with 18.51M Traffic. Categories: Information Technology, Online Services. Learn more about website traffic, market share, and more!

google.com is ranked #1 in US with 101.35B Traffic. Categories: Online Services. Learn more about website traffic, market share, and more!

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

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

The backlink checker tool market is experiencing robust growth, driven by the increasing importance of SEO and digital marketing for businesses of all sizes. The market's expansion is fueled by several factors, including the rising adoption of cloud-based solutions, the need for enhanced website authority assessment, and the growing complexity of search engine algorithms. Small and medium-sized enterprises (SMEs) are a significant market segment, adopting these tools to compete effectively against larger players. Large enterprises, however, represent a substantial revenue stream due to their higher budgets and more sophisticated SEO needs. The market is further segmented by deployment type – cloud-based solutions are gaining traction due to their accessibility and scalability. While on-premise solutions still maintain a niche presence for businesses with stringent security requirements, the overall market trend clearly favors the cloud. The competitive landscape is highly dynamic, with both established players like Ahrefs and SEMrush and emerging companies vying for market share. This competitive environment fosters innovation and pushes for continuous improvement in the features and capabilities of these tools. Geographical analysis shows strong market presence in North America and Europe, followed by the Asia-Pacific region experiencing rapid growth. This is primarily due to the increasing digitalization and e-commerce adoption in developing economies within this region. Forecasts indicate continued market expansion, with a projected CAGR of approximately 15% from 2025 to 2033, suggesting a significant potential for continued investment and growth within the backlink checker tool market. The forecast period (2025-2033) anticipates continued market expansion, influenced by factors like improved tool accuracy, increasing demand for competitive analysis features, and ongoing developments in SEO techniques. The integration of AI and machine learning into backlink checker tools is another key factor driving growth by offering more sophisticated insights and automating aspects of backlink analysis. The restraints on market growth primarily stem from the high cost of advanced tools, the availability of free (though often limited) alternatives, and the need for continuous updates to remain compatible with evolving search engine algorithms. However, these restraints are unlikely to significantly impede the overall growth trajectory, given the vital role backlink analysis plays in modern SEO strategies and the growing demand for sophisticated tools to streamline this process. The market shows promising prospects across all regions, with continued penetration in established markets and significant potential for expansion in emerging economies.

In November 2024, Google.com was the most popular website worldwide with 136 billion average monthly visits. The online platform has held the top spot as the most popular website since June 2010, when it pulled ahead of Yahoo into first place. Second-ranked YouTube generated more than 72.8 billion monthly visits in the measured period. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

chatgpt.com is ranked #10 in US with 5.24B Traffic. Categories: AI. Learn more about website traffic, market share, and more!

CRO tools offer a suite of features, including:

Website analytics: Track user behavior, identify bottlenecks, and optimize page performance. A/B testing: Compare different website variations to determine the most effective design or content. Heat mapping: Visualize user interactions, such as clicks and scroll patterns, to pinpoint areas for improvement. Personalization: Tailor website experiences based on user preferences and behaviors. Visitor segmentation: Divide visitors into specific segments for targeted marketing campaigns.

Report Coverage & Deliverables Market Segmentation:

Application: SMEs, Large Enterprises Type: Cloud-based, On-premises Industry: E-commerce, Travel, Healthcare, Education

Regional Insights:

North America: Dominates the market, with strong adoption in the US. Europe: Growing rapidly, driven by increasing demand for data privacy compliance. Asia-Pacific: Emerging market with significant potential for growth. Latin America: Underdeveloped market with limited infrastructure and resources.

Conversion Rate Optimization (CRO) Tool Trends

Personalization and automation Use of artificial intelligence (AI) for data processing and insights Focus on mobile optimization Real-time optimization capabilities Rise of AI-powered virtual assistants

Driving Forces: What's Propelling the Conversion Rate Optimization (CRO) Tool

Growing demand for increased website conversions Need for improved user experience and customer satisfaction E-commerce growth and the need for optimized online shopping experiences Advancements in analytics and data collection technologies

Challenges and Restraints in Conversion Rate Optimization (CRO) Tool

Data privacy concerns Lack of skilled CRO professionals Limited budgets for SMEs Competition from free and open-source CRO tools

Emerging Trends in Conversion Rate Optimization (CRO) Tool

Predictive analytics AI-powered automation Use of chatbots for customer engagement Personalization at scale Omnichannel CRO strategies

Growth Catalysts in Conversion Rate Optimization (CRO) Tool Industry

Government initiatives promoting e-commerce and digital transformation Increased awareness of CRO benefits Adoption of AI and machine learning technologies Growing investment in customer experience (CX)

Leading Players in the Conversion Rate Optimization (CRO) Tool

Google Heap Adobe CRO Checker Crazy Egg Hotjar Full Story Popupsmart Optinmonster FreeChat LiveChat MixPanel Amplitude Survey Monkey Optimizely VWO Nudgify UseProof

Significant developments in Conversion Rate Optimization (CRO) Tool Sector

Acquisition of CRO Checker by Adobe Partnership between Hotjar and Salesforce Launch of AI-powered optimization tools by Google Increasing investment in R&D by leading players

The global website speed and performance testing tools market is experiencing robust growth, driven by the increasing reliance on web applications across personal and enterprise sectors. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $7.2 billion by 2033. This expansion is fueled by several key factors. Firstly, the growing demand for enhanced user experience (UX) is pushing businesses to prioritize website optimization. Slow loading times lead to higher bounce rates, lost conversions, and damaged brand reputation, prompting widespread adoption of testing tools to proactively identify and rectify performance bottlenecks. Secondly, the rise of mobile internet usage necessitates tools that accurately assess performance across various devices and networks. Thirdly, the increasing complexity of modern websites, incorporating rich media and dynamic content, necessitates sophisticated testing capabilities beyond basic page load speed measurement. The market segmentation reveals a significant share for cloud-based solutions, reflecting the ongoing shift towards cloud infrastructure for ease of access and scalability. While North America currently holds a dominant market share, rapid growth is expected from regions like Asia-Pacific, driven by expanding internet penetration and e-commerce activities. However, factors such as the high initial investment cost for advanced tools and the availability of free, basic tools present challenges to market penetration. The competitive landscape is highly fragmented, with numerous established players and emerging startups offering a diverse range of features and pricing models. Major players like Pingdom, Google PageSpeed Insights, and New Relic cater to a broad spectrum of users, while specialized tools address niche requirements. The future trajectory of the market is marked by the continuous evolution of testing methodologies, incorporating emerging technologies like artificial intelligence (AI) and machine learning (ML) for performance analysis and optimization. This innovation will lead to more accurate, predictive, and actionable insights for website owners and developers. The market's expansion will be further supported by the growing adoption of DevOps practices and the increased emphasis on website security, integrating security testing within performance testing workflows. Ultimately, the website speed and performance testing tool market is poised for continued strong growth, driven by the ongoing demand for optimized website performance and the continuous evolution of testing capabilities.

Context

The data presented here was obtained in a Kali Machine from University of Cincinnati,Cincinnati,OHIO by carrying out packet captures for 1 hour during the evening on Oct 9th,2023 using Wireshark.This dataset consists of 394137 instances were obtained and stored in a CSV (Comma Separated Values) file.This large dataset could be used utilised for different machine learning applications for instance classification of Network traffic,Network performance monitoring,Network Security Management , Network Traffic Management ,network intrusion detection and anomaly detection.

The dataset can be used for a variety of machine learning tasks, such as network intrusion detection, traffic classification, and anomaly detection.

Content :

This network traffic dataset consists of 7 features.Each instance contains the information of source and destination IP addresses, The majority of the properties are numeric in nature, however there are also nominal and date kinds due to the Timestamp.

The network traffic flow statistics (No. Time Source Destination Protocol Length Info) were obtained using Wireshark (https://www.wireshark.org/).

Dataset Columns:

No : Number of Instance. Timestamp : Timestamp of instance of network traffic Source IP: IP address of Source Destination IP: IP address of Destination Portocol: Protocol used by the instance Length: Length of Instance Info: Information of Traffic Instance

Acknowledgements :

I would like thank University of Cincinnati for giving the infrastructure for generation of network traffic data set.

Ravikumar Gattu , Susmitha Choppadandi

Inspiration : This dataset goes beyond the majority of network traffic classification datasets, which only identify the type of application (WWW, DNS, ICMP,ARP,RARP) that an IP flow contains. Instead, it generates machine learning models that can identify specific applications (like Tiktok,Wikipedia,Instagram,Youtube,Websites,Blogs etc.) from IP flow statistics (there are currently 25 applications in total).

**Dataset License: ** CC0: Public Domain

Dataset Usages : This dataset can be used for different machine learning applications in the field of cybersecurity such as classification of Network traffic,Network performance monitoring,Network Security Management , Network Traffic Management ,network intrusion detection and anomaly detection.

ML techniques benefits from this Dataset :

This dataset is highly useful because it consists of 394137 instances of network traffic data obtained by using the 25 applications on a public,private and Enterprise networks.Also,the dataset consists of very important features that can be used for most of the applications of Machine learning in cybersecurity.Here are few of the potential machine learning applications that could be benefited from this dataset are :

1. Network Performance Monitoring : This large network traffic data set can be utilised for analysing the network traffic to identifying the network patterns in the network .This help in designing the network security algorithms for minimise the network probelms.

2. Anamoly Detection : Large network traffic dataset can be utilised training the machine learning models for finding the irregularitues in the traffic which could help identify the cyber attacks.

3.Network Intrusion Detection : This large dataset could be utilised for machine algorithms training and designing the models for detection of the traffic issues,Malicious traffic network attacks and DOS attacks as well.

x.com is ranked #11 in US with 3.96B Traffic. Categories: . Learn more about website traffic, market share, and more!

This map contains 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 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 can be requested for the current time and any time in the future. A map for a future request might be used for planning purposes. The map 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.

alexa.com is ranked #34662 in MX with 62.5K Traffic. Categories: Advertising and Marketing, Computer Software and Development, Information Technology, Online Services. Learn more about website traffic, market share, and more!

Comparison of Seconds to Output 500 Tokens, including reasoning model 'thinking' time; Lower is better by Model

facebook.com is ranked #4 in US with 9.94B Traffic. Categories: Online Services. Learn more about website traffic, market share, and more!

Comparison of Seconds to First Answer Token Received; Accounts for Reasoning Model 'Thinking' time by Model

Comparison of Output Tokens per Second; Higher is better by Model

reddit.com is ranked #5 in US with 4.66B Traffic. Categories: Online Services. Learn more about website traffic, market share, and more!

Locations of signalised intersections and signalised pedestrian crossings in Hamilton City

Column_InfoSite_Number, int : SCATS ID - Unique identifierRoad_1, varchar : First road descriptorRoad_2, varchar : Second road descriptor - 'Ped xing' means it is a mid-block pedestrian signalRoad_3, varchar : Third road descriptor if relevantSite_Type, varchar : Pedestrian crossing or intersection, and whether on a state highway or council roadIs_CBD, int : Site is within the CBD boundaryEasting, decimal : Eastward-measured distance in NZTM projectionNorthing, decimal : Northward-measured distance in NZTM projectionLatitude, decimal : North-south geographic coordinatesLongitude, decimal : East-west geographic coordinates

Relationship

This table is referenced by Traffic_Signal_Detector

Analytics

For convenience Hamilton City Council has also built a Quick Analytics Dashboard over this dataset that you can access here.

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.'