Among the ** most popular websites in Russia, Google.com had the highest average monthly traffic, at over five billion visits in November 2024. It was followed by the Russian search engine Yandex.ru, with around *** billion visits in the same period.

Traffic Volumes from SCATS Traffic Management System Jan-Jun 2025 DCC. Published by Dublin City Council. Available under the license cc-by (CC-BY-4.0).Traffic volumes data across Dublin City from the SCATS traffic management system. The Sydney Coordinated Adaptive Traffic System (SCATS) is an intelligent transportation system used to manage timing of signal phases at traffic signals. SCATS uses sensors at each traffic signal to detect vehicle presence in each lane and pedestrians waiting to cross at the local site. The vehicle sensors are generally inductive loops installed within the road.

3 resources are provided:

SCATS Traffic Volumes Data (Monthly) Contained in this report are traffic counts taken from the SCATS traffic detectors located at junctions. The primary function for these traffic detectors is for traffic signal control. Such devices can also count general traffic volumes at defined locations on approach to a junction. These devices are set at specific locations on approaches to the junction but may not be on all approaches to a junction. As there are multiple junctions on any one route, it could be expected that a vehicle would be counted multiple times as it progress along the route. Thus the traffic volume counts here are best used to represent trends in vehicle movement by selecting a specific junction on the route which best represents the overall traffic flows.

Information provided:

End Time: time that one hour count period finishes.

Region: location of the detector site (e.g. North City, West City, etc).

Site: this can be matched with the SCATS Sites file to show location

Detector: the detectors/ sensors at each site are numbered

Sum volume: total traffic volumes in preceding hour

Avg volume: average traffic volumes per 5 minute interval in preceding hour

All Dates Traffic Volumes Data

This file contains daily totals of traffic flow at each site location.

SCATS Site Location Data Contained in this report, the location data for the SCATS sites is provided. The meta data provided includes the following;

Site id – This is a unique identifier for each junction on SCATS

Site description( CAP) – Descriptive location of the junction containing street name(s) intersecting streets

Site description (lower) - – Descriptive location of the junction containing street name(s) intersecting streets

Region – The area of the city, adjoining local authority, region that the site is located

LAT/LONG – Coordinates

Disclaimer: the location files are regularly updated to represent the locations of SCATS sites under the control of Dublin City Council. However site accuracy is not absolute. Information for LAT/LONG and region may not be available for all sites contained. It is at the discretion of the user to link the files for analysis and to create further data. Furthermore, detector communication issues or faulty detectors could also result in an inaccurate result for a given period, so values should not be taken as absolute but can be used to indicate trends....

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

The Japanese review site my-best.com had the highest bounce rate among the most visited retail websites in Japan in July 2024. Operated by mybest, Inc. and part of LY Corporation, the website had a bounce of nearly ** percent, while ranking as the ****** most visited retail website in the same month.

Imagine you click an ad on Facebook for a spiffy set of binoculars. The ad claims they are perfect for bird watchers like yourself. The link sends you to a product page on an ecommerce website. You see the same binoculars but no mention of birds. It seems like a great device, but you wonder […]

At The Good, we love to use the phrase, “Let’s test it.” There’s no sense in making assumptions or guessing what an audience wants. It’s smarter – and better for your budget – to run experiments in order to determine what actually boosts your conversion rate. A/B testing is the standard experimentation methodology for digital marketing. […]

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.

Traffic analytics, rankings, and competitive metrics for best-hashtags.com as of May 2025

Construction site coordination in Hamburg The preservation of the infrastructure is of fundamental importance for the development of Hamburg. Therefore, construction sites in the street space are part of the normal picture - to the chagrin of local residents and road users. In many cases, however, it is not work on the road itself that leads to disabilities, but the many supply and disposal lines in the road body or the construction projects of private individuals. Approximately 25,000 jobs per year on Hamburg's road network, of which over 3,700 are on major roads, therefore require careful coordination to minimise obstacles to traffic flow. This is the task of the Traffic Optimization Department at the Department of Transport and Mobility Transition. Here, the incoming information of all road construction departments, pipeline companies and private builders is collected and evaluated. The information for the most important construction sites is published with a 7-day preview on the Internet at www.hamburg.de/baustellen. When coordinating construction sites, the aim is to prevent simultaneous construction sites, e.g. on important parallel roads, so that traffic has trouble-free alternative routes. However, no matter how good coordination can absolutely prevent congestion. The Hamburg road network is partly busy and partly overloaded in the morning and evening rush hour. Therefore, we recommend every road user to inform himself about the current traffic situation before starting the journey and only then to choose a suitable means of transport including route.

If you have any questions about construction sites in Hamburg, please contact the construction site hotline on 040 428 28 2020 or by post to

Free and Hanseatic City of Hamburg Transport and Mobility Transition Authority Old stone path 4 20459 Hamburg

While it would be nice to have an endless stream of traffic to your site, for many brands it’s more of a trickle–and, in some cases, a very, very small trickle. You may not be able to generate thousands of visitors overnight, so it’s difficult to run quick conversion optimization tests to improve your sales. […]

When Amazon was launched in July 16, 1995 as a website that only sold books, founder Jeff Bezos had a vision for the company's explosive growth and e-commerce domination. In December 2019, we note that around 6.5 percent of visits to Amazon came from paid traffic in France, that is to say, visits made through paid advertising. With a strong discrepancy to it's competitors, the next best performing company was Microsoft.

Traffic Volumes from SCATS Traffic Management System 2022. Published by Dún Laoghaire-Rathdown County Council. Available under the license cc-by (CC-BY-4.0).Traffic volumes data across Dun Laoghaire Rathdown from the SCATS traffic management system. The Sydney Coordinated Adaptive Traffic System (SCATS) is an intelligent transportation system used to manage timing of signal phases at traffic signals. SCATS uses sensors at each traffic signal to detect vehicle presence in each lane and pedestrians waiting to cross at the local site.

SCATS Traffic Volumes Data (Monthly) Contained in this report are traffic counts taken from the SCATS traffic detectors located at junctions. The primary function for these traffic detectors is for traffic signal control. Such devices can also count general traffic volumes at defined locations on approach to a junction. These devices are set at specific locations on approaches to the junction but may not be on all approaches to a junction. As there are multiple junctions on any one route, it could be expected that a vehicle would be counted multiple times as it progress along the route. Thus the traffic volume counts here are best used to represent trends in vehicle movement by selecting a specific junction on the route which best represents the overall traffic flows.

Please note this data is for information purposes only and may not be an exact representation of the infrastructure. Changes and upgrades occurring since then may not be represented....

This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. For a more detailed description, please go to https://tas.chicago.gov, click the About button at the bottom of the page, and then the MAP LAYERS tab.

The Chicago Traffic Tracker estimates traffic congestion on Chicago’s arterial streets (nonfreeway streets) in real-time by continuously monitoring and analyzing GPS traces received from Chicago Transit Authority (CTA) buses. Two types of congestion estimates are produced every ten minutes: 1) by Traffic Segments and 2) by Traffic Regions or Zones. Congestion estimate by traffic segments gives the observed speed typically for one-half mile of a street in one direction of traffic.

Traffic Segment level congestion is available for about 300 miles of principal arterials. Congestion by Traffic Region gives the average traffic condition for all arterial street segments within a region. A traffic region is comprised of two or three community areas with comparable traffic patterns. 29 regions are created to cover the entire city (except O’Hare airport area). This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. There is much volatility in traffic segment speed. However, the congestion estimates for the traffic regions remain consistent for relatively longer period. Most volatility in arterial speed comes from the very nature of the arterials themselves. Due to a myriad of factors, including but not limited to frequent intersections, traffic signals, transit movements, availability of alternative routes, crashes, short length of the segments, etc. speed on individual arterial segments can fluctuate from heavily congested to no congestion and back in a few minutes. The segment speed and traffic region congestion estimates together may give a better understanding of the actual traffic conditions.

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

In March 2024, Google.com was the leading website in the United States. The search platform accounted for over 19 percent of desktop web traffic in the United States, ahead of second-ranked YouTube.com with 10.71 percent.

The Institute for Municipal and Regional Policy (IMRP) at Central Connecticut State University, in consultation with the Office of Policy and Management (OPM), has established a Racial Profiling Prohibition Advisory Board to help oversee the design, evaluation, and management of the racial profiling study mandated by PA 12-74, “An Act Concerning Traffic Stop Information.” The IMRP is working with the advisory board and all appropriate parties to enhance the collection and analysis of traffic stop data in Connecticut. Resources for the project are being made available through the National Highway Traffic and Safety Administration (NHTSA) grant, as administered through the Connecticut Department of Transportation. The primary purpose of the project is to monitor and prohibit racial profiling in Connecticut and to comply with NHTSA grant requirements and are outlined below. Analyze current racial profiling law and make recommendations to the Connecticut General Assembly to better align the statute to legislative intent and current best practices. Ensure compliance with the racial profiling law in as efficient, effective, transparent and inclusive a manner possible. Ensure compliance with NHTSA requirements of Section 1906 funding to include: Fund activities to prohibit racial profiling in the enforcement of State laws regulating the use of Federal-aid highways Collect, maintain and provide public access to traffic stop data Evaluate the results of such data; and develop and implement programs to reduce the occurrence of racial profiling, including programs to train law enforcement officers. The Racial Profiling Prohibition Project Advisory Board and the project staff have been meeting since May 2012 in an effort to outline a plan to successfully implement PA 12-74. The focus of this early phase of the project has been to better understand traffic stop data collection in other states. Four working groups were established to advise on various aspects of the process including; the standardized method for collecting, recording, reporting, and analyzing racial profiling data required by PA 12-74 and to accomplish tasks required to complete the Racial Profiling Prohibition Project. For more information contact: Ken Barrone Policy & Research Specialist Institute for Municipal & Regional Policy, Central Connecticut State University Tel: 860.832.1872 or Email: baroneket@ccsu.edu

Department of Transport dataset. The excess delay in minutes, calculated every 30 seconds. This is the difference between the thick blue and thick red lines in the previous chart. Unlike the delay parameter that has a fixed baseline travel time, excess delay has a baseline that changes depending on the time of day. In the previous figure at about 8:20, the expected travel time (red line) was 4 minutes. The actual travel time (blue line) was about 6 minutes. This equates to an excess delay of 2 minutes (6 minus 4) and a delay of 5 minutes (6 minus 1). Excess delays greater than zero indicates the link is operating worse than expected for this time of day. You can have negative values when the link is travelling better than expected.

This dataset contains the current estimated congestion for the 29 traffic regions. For a detailed description, please go to https://tas.chicago.gov, click the About button at the bottom of the page, and then the MAP LAYERS tab. The Chicago Traffic Tracker estimates traffic congestion on Chicago’s arterial streets (non-freeway streets) in real-time by continuously monitoring and analyzing GPS traces received from Chicago Transit Authority (CTA) buses. Two types of congestion estimates are produced every 10 minutes: 1) by Traffic Segments and 2) by Traffic Regions or Zones. Congestion estimates by traffic segments gives observed speed typically for one-half mile of a street in one direction of traffic. Traffic Segment level congestion is available for about 300 miles of principal arterials. Congestion by Traffic Region gives the average traffic condition for all arterial street segments within a region. A traffic region is comprised of two or three community areas with comparable traffic patterns. 29 regions are created to cover the entire city (except O’Hare airport area). There is much volatility in traffic segment speed. However, the congestion estimates for the traffic regions remain consistent for a relatively longer period. Most volatility in arterial speed comes from the very nature of the arterials themselves. Due to a myriad of factors, including but not limited to frequent intersections, traffic signals, transit movements, availability of alternative routes, crashes, short length of the segments, etc. Speed on individual arterial segments can fluctuate from heavily congested to no congestion and back in a few minutes. The segment speed and traffic region congestion estimates together may give a better understanding of the actual traffic conditions.

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

Here are a few use cases for this project:

1. Traffic Flow Analysis: The dataset can be used in machine learning models to analyze traffic flow in cities. It can identify the type of vehicles on the city roads at different times of the day, helping in planning and traffic management.

2. Vehicle Class Based Toll Collection: Toll booths can use this model to automatically classify and charge vehicles based on their type, enabling a more efficient and automated system.

3. Parking Management System: Parking lot owners can use this model to easily classify vehicles as they enter for better space management. Knowing the vehicle type can help assign it to the most suitable parking spot.

4. Traffic Rule Enforcement: The dataset can be used to create a computer vision model to automatically detect any traffic violations like wrong lane driving by different vehicle types, and notify law enforcement agencies.

5. Smart Ambulance Tracking: The system can help in identifying and tracking ambulances and other emergency vehicles, enabling traffic management systems to provide priority routing during emergencies.