Daily utilization metrics for data.lacity.org and geohub.lacity.org. Updated monthly
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Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.
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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.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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Digital technology and Internet use, website traffic strategies, by North American Industry Classification System (NAICS) and size of enterprise for Canada from 2012 to 2013.
From February to July 2024, February was the month that had the most website traffic to ebay.com. The consumer-to-consumer (C2C) e-commerce website reached a total of over *** million visits in that month, with the majority being from mobile devices. Popularity on multiple fronts Although eBay is popular on mobile devices, monthly downloads of its mobile app have been trending in the wrong direction since peaking in June 2020 at **** million. Still, in April 2023, ebay.com was the second most popular e-commerce and shopping website worldwide, accounting for more than ***** percent of visits to sites in this category. Big numbers declining In the second quarter of 2023, eBay’s gross merchandise volume (GMV) amounted to nearly **** billion U.S. dollars. That is no small number, but is only a small increase compared to the lowest GMV recorded by the company since the first quarter of 2020 - **** billion U.S. dollars in the third quarter of 2022 - and that’s not the only figure on the decline for eBay. The e-commerce platform had approximately *** million active buyers in the second quarter of 2022, and a year later that number was down *** percent to *** million.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Unique visitors, total sessions, and bounce rate for lacity.org, the main website for the City of Los Angeles.
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
As of the last quarter of 2023, 31.57 percent of web traffic in the United States originated from mobile devices, down from 49.51 percent in the fourth quarter of 2022. In comparison, over half of web traffic worldwide was generated via mobile in the last examined period.
https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy
The global 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. The market, estimated at $5 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $15 billion by 2033. This expansion is fueled by several key factors, including the rising adoption of digital marketing strategies, the growing importance of data-driven decision-making, and the increasing sophistication of website visitor tracking tools. Cloud-based solutions dominate the market due to their scalability, accessibility, and cost-effectiveness, particularly appealing to Small and Medium-sized Enterprises (SMEs). However, large enterprises continue to invest significantly in on-premise solutions for enhanced data security and control. The market is highly competitive, with numerous established players and emerging startups offering a range of features and functionalities. Technological advancements, such as AI-powered analytics and enhanced integration with other marketing tools, are shaping the future of the market. The market's geographical distribution reflects the global digital landscape. North America, with its mature digital economy and high adoption rates, holds a significant market share. However, regions like Asia-Pacific are showing rapid growth, driven by increasing internet penetration and digitalization across various industries. Despite the overall positive outlook, challenges such as data privacy regulations and the increasing complexity of website tracking technology are influencing market dynamics. The ongoing competition among vendors necessitates continuous innovation and the development of more user-friendly and insightful tools. The future growth of the website visitor tracking software market is promising, fueled by the continuing importance of data-driven decision-making within marketing and business strategies. A key factor will be the ongoing adaptation to evolving privacy regulations and user expectations.
U.S. Government Workshttps://www.usa.gov/government-works
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Weekly Number of Page Views on the Littlerock.gov Website
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Popular Website Traffic Over Time ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/popular-website-traffice on 13 February 2022.
--- Dataset description provided by original source is as follows ---
Background
Have you every been in a conversation and the question comes up, who uses Bing? This question comes up occasionally because people wonder if these sites have any views. For this research study, we are going to be exploring popular website traffic for many popular websites.
Methodology
The data collected originates from SimilarWeb.com.
Source
For the analysis and study, go to The Concept Center
This dataset was created by Chase Willden and contains around 0 samples along with 1/1/2017, Social Media, technical information and other features such as: - 12/1/2016 - 3/1/2017 - and more.
- Analyze 11/1/2016 in relation to 2/1/2017
- Study the influence of 4/1/2017 on 1/1/2017
- More datasets
If you use this dataset in your research, please credit Chase Willden
--- Original source retains full ownership of the source dataset ---
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Explore the historical Whois records related to increase-website-traffic.org (Domain). Get insights into ownership history and changes over time.
As of 2019, direct traffic accounts for the largest percentage of website traffic worldwide, with a share of 55 percent. Additionally, search traffic accounts for 29 percent of worldwide website traffic.
A study released in June 2025 that looked at about 82,000 websites found that Google was responsible for almost ** percent of the traffic generated to these domains. Direct traffic corresponded to around **** percent of the investigated websites' traffic volume. While traditional search engines like Bing and social networks like Facebook represented larger shares, ChatGPT overtook Reddit and LinkedIn with a slightly larger share, indicating an increase in traffic from these platforms.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Please refer to the original data article for further data description: Jan Luxemburk et al. CESNET-QUIC22: A large one-month QUIC network traffic dataset from backbone lines, Data in Brief, 2023, 108888, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2023.108888. We recommend using the CESNET DataZoo python library, which facilitates the work with large network traffic datasets. More information about the DataZoo project can be found in the GitHub repository https://github.com/CESNET/cesnet-datazoo. The QUIC (Quick UDP Internet Connection) protocol has the potential to replace TLS over TCP, which is the standard choice for reliable and secure Internet communication. Due to its design that makes the inspection of QUIC handshakes challenging and its usage in HTTP/3, there is an increasing demand for research in QUIC traffic analysis. This dataset contains one month of QUIC traffic collected in an ISP backbone network, which connects 500 large institutions and serves around half a million people. The data are delivered as enriched flows that can be useful for various network monitoring tasks. The provided server names and packet-level information allow research in the encrypted traffic classification area. Moreover, included QUIC versions and user agents (smartphone, web browser, and operating system identifiers) provide information for large-scale QUIC deployment studies. Data capture The data was captured in the flow monitoring infrastructure of the CESNET2 network. The capturing was done for four weeks between 31.10.2022 and 27.11.2022. The following list provides per-week flow count, capture period, and uncompressed size:
W-2022-44
Uncompressed Size: 19 GB Capture Period: 31.10.2022 - 6.11.2022 Number of flows: 32.6M W-2022-45
Uncompressed Size: 25 GB Capture Period: 7.11.2022 - 13.11.2022 Number of flows: 42.6M W-2022-46
Uncompressed Size: 20 GB Capture Period: 14.11.2022 - 20.11.2022 Number of flows: 33.7M W-2022-47
Uncompressed Size: 25 GB Capture Period: 21.11.2022 - 27.11.2022 Number of flows: 44.1M CESNET-QUIC22
Uncompressed Size: 89 GB Capture Period: 31.10.2022 - 27.11.2022 Number of flows: 153M
Data description The dataset consists of network flows describing encrypted QUIC communications. Flows were created using ipfixprobe flow exporter and are extended with packet metadata sequences, packet histograms, and with fields extracted from the QUIC Initial Packet, which is the first packet of the QUIC connection handshake. The extracted handshake fields are the Server Name Indication (SNI) domain, the used version of the QUIC protocol, and the user agent string that is available in a subset of QUIC communications. Packet Sequences Flows in the dataset are extended with sequences of packet sizes, directions, and inter-packet times. For the packet sizes, we consider payload size after transport headers (UDP headers for the QUIC case). Packet directions are encoded as ±1, +1 meaning a packet sent from client to server, and -1 a packet from server to client. Inter-packet times depend on the location of communicating hosts, their distance, and on the network conditions on the path. However, it is still possible to extract relevant information that correlates with user interactions and, for example, with the time required for an API/server/database to process the received data and generate the response to be sent in the next packet. Packet metadata sequences have a length of 30, which is the default setting of the used flow exporter. We also derive three fields from each packet sequence: its length, time duration, and the number of roundtrips. The roundtrips are counted as the number of changes in the communication direction (from packet directions data); in other words, each client request and server response pair counts as one roundtrip. Flow statistics Flows also include standard flow statistics, which represent aggregated information about the entire bidirectional flow. The fields are: the number of transmitted bytes and packets in both directions, the duration of flow, and packet histograms. Packet histograms include binned counts of packet sizes and inter-packet times of the entire flow in both directions (more information in the PHISTS plugin documentation There are eight bins with a logarithmic scale; the intervals are 0-15, 16-31, 32-63, 64-127, 128-255, 256-511, 512-1024, >1024 [ms or B]. The units are milliseconds for inter-packet times and bytes for packet sizes. Moreover, each flow has its end reason - either it was idle, reached the active timeout, or ended due to other reasons. This corresponds with the official IANA IPFIX-specified values. The FLOW_ENDREASON_OTHER field represents the forced end and lack of resources reasons. The end of flow detected reason is not considered because it is not relevant for UDP connections. Dataset structure The dataset flows are delivered in compressed CSV files. CSV files contain one flow per row; data columns are summarized in the provided list below. For each flow data file, there is a JSON file with the number of saved and seen (before sampling) flows per service and total counts of all received (observed on the CESNET2 network), service (belonging to one of the dataset's services), and saved (provided in the dataset) flows. There is also the stats-week.json file aggregating flow counts of a whole week and the stats-dataset.json file aggregating flow counts for the entire dataset. Flow counts before sampling can be used to compute sampling ratios of individual services and to resample the dataset back to the original service distribution. Moreover, various dataset statistics, such as feature distributions and value counts of QUIC versions and user agents, are provided in the dataset-statistics folder. The mapping between services and service providers is provided in the servicemap.csv file, which also includes SNI domains used for ground truth labeling. The following list describes flow data fields in CSV files:
ID: Unique identifier SRC_IP: Source IP address DST_IP: Destination IP address DST_ASN: Destination Autonomous System number SRC_PORT: Source port DST_PORT: Destination port PROTOCOL: Transport protocol QUIC_VERSION QUIC: protocol version QUIC_SNI: Server Name Indication domain QUIC_USER_AGENT: User agent string, if available in the QUIC Initial Packet TIME_FIRST: Timestamp of the first packet in format YYYY-MM-DDTHH-MM-SS.ffffff TIME_LAST: Timestamp of the last packet in format YYYY-MM-DDTHH-MM-SS.ffffff DURATION: Duration of the flow in seconds BYTES: Number of transmitted bytes from client to server BYTES_REV: Number of transmitted bytes from server to client PACKETS: Number of packets transmitted from client to server PACKETS_REV: Number of packets transmitted from server to client PPI: Packet metadata sequence in the format: [[inter-packet times], [packet directions], [packet sizes]] PPI_LEN: Number of packets in the PPI sequence PPI_DURATION: Duration of the PPI sequence in seconds PPI_ROUNDTRIPS: Number of roundtrips in the PPI sequence PHIST_SRC_SIZES: Histogram of packet sizes from client to server PHIST_DST_SIZES: Histogram of packet sizes from server to client PHIST_SRC_IPT: Histogram of inter-packet times from client to server PHIST_DST_IPT: Histogram of inter-packet times from server to client APP: Web service label CATEGORY: Service category FLOW_ENDREASON_IDLE: Flow was terminated because it was idle FLOW_ENDREASON_ACTIVE: Flow was terminated because it reached the active timeout FLOW_ENDREASON_OTHER: Flow was terminated for other reasons
Link to other CESNET datasets
https://www.liberouter.org/technology-v2/tools-services-datasets/datasets/ https://github.com/CESNET/cesnet-datazoo Please cite the original data article:
@article{CESNETQUIC22, author = {Jan Luxemburk and Karel Hynek and Tomáš Čejka and Andrej Lukačovič and Pavel Šiška}, title = {CESNET-QUIC22: a large one-month QUIC network traffic dataset from backbone lines}, journal = {Data in Brief}, pages = {108888}, year = {2023}, issn = {2352-3409}, doi = {https://doi.org/10.1016/j.dib.2023.108888}, url = {https://www.sciencedirect.com/science/article/pii/S2352340923000069} }
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Explore the historical Whois records related to hitt-traffic.net (Domain). Get insights into ownership history and changes over time.
Datos brings to market anonymized, at scale, consolidated privacy-secured datasets with a granularity rarely found in the market. Get access to the desktop and mobile browsing behavior for millions of users across the globe, packaged into clean, easy-to-understand data products and reports.
The Datos Domain Traffic Feed reports on panelist visitation to domains, benchmarking the popularity of internet properties worldwide by country. Additionally, we offer the ability to track the availability of domains with respect to whether traffic is being sent to sites which are currently unregistered. Customers can elect to focus on specific domains, countries, or domain registration status.
Now available with Datos Low-Latency Feed This add-on ensures delivery of approximately 99% of all devices before markets open in New York (the lowest latency product on the market). Our clickstream data is made up of an array of upstream sources. The DLLF makes the daily output of these sources available as they arrive and are processed, rather than a once-daily batch.
Daily utilization metrics for data.lacity.org and geohub.lacity.org. Updated monthly