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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.

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.

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.'

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

shopify.com is ranked #82 in US with 245.63M Traffic. Categories: Computer Software and Development, Online Services. Learn more about website traffic, market share, and more!

Context

This file contains 5 years of daily time series data for several measures of traffic on a statistical forecasting teaching notes website whose alias is statforecasting.com. The variables have complex seasonality that is keyed to the day of the week and to the academic calendar. The patterns you you see here are similar in principle to what you would see in other daily data with day-of-week and time-of-year effects. Some good exercises are to develop a 1-day-ahead forecasting model, a 7-day ahead forecasting model, and an entire-next-week forecasting model (i.e., next 7 days) for unique visitors.

Content

The variables are daily counts of page loads, unique visitors, first-time visitors, and returning visitors to an academic teaching notes website. There are 2167 rows of data spanning the date range from September 14, 2014, to August 19, 2020. A visit is defined as a stream of hits on one or more pages on the site on a given day by the same user, as identified by IP address. Multiple individuals with a shared IP address (e.g., in a computer lab) are considered as a single user, so real users may be undercounted to some extent. A visit is classified as "unique" if a hit from the same IP address has not come within the last 6 hours. Returning visitors are identified by cookies if those are accepted. All others are classified as first-time visitors, so the count of unique visitors is the sum of the counts of returning and first-time visitors by definition. The data was collected through a traffic monitoring service known as StatCounter.

Inspiration

This file and a number of other sample datasets can also be found on the website of RegressIt, a free Excel add-in for linear and logistic regression which I originally developed for use in the course whose website generated the traffic data given here. If you use Excel to some extent as well as Python or R, you might want to try it out on this dataset.

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.

As of the last quarter of 2023, ***** percent of web traffic in the United States originated from mobile devices, down from ***** percent in the fourth quarter of 2022. In comparison, over half of web traffic worldwide was generated via mobile in the last examined period.

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?

** Note: This dataset has been archived and is no longer being updated due to a change in analytics platform. You can find the new dataset relating to Website Statistics in the following link; https://lincolnshire.ckan.io/dataset/website-statistics ** This Website Statistics dataset has three 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. Note: The resources above show only UK users, and exclude API calls (automated requests for datasets). For further information, please contact the Lincolnshire County Council Open Data team.

The dataset provides 12 months (August 2016 to August 2017) of obfuscated Google Analytics 360 data from the Google Merchandise Store , a real ecommerce store that sells Google-branded merchandise, in BigQuery. It’s a great way analyze business data and learn the benefits of using BigQuery to analyze Analytics 360 data Learn more about the data The data includes The data is typical of what an ecommerce website would see and includes the following information:Traffic source data: information about where website visitors originate, including data about organic traffic, paid search traffic, and display trafficContent data: information about the behavior of users on the site, such as URLs of pages that visitors look at, how they interact with content, etc. Transactional data: information about the transactions on the Google Merchandise Store website.Limitations: All users have view access to the dataset. This means you can query the dataset and generate reports but you cannot complete administrative tasks. Data for some fields is obfuscated such as fullVisitorId, or removed such as clientId, adWordsClickInfo and geoNetwork. “Not available in demo dataset” will be returned for STRING values and “null” will be returned for INTEGER values when querying the fields containing no data.This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery

amazon.in is ranked #7 in IN with 237.37M Traffic. Categories: Retail, Online Services. Learn more about website traffic, market share, and more!

Explore the historical Whois records related to increase-website-traffic.org (Domain). Get insights into ownership history and changes over time.

Explore the historical Whois records related to website-traffic-ads.com (Domain). Get insights into ownership history and changes over time.

Introduction

Linux Statistics: Linux is a group of free operating systems that work like Unix. It runs on the Linux kernel, which was first made by Linus Torvalds in 1991. Most people use Linux through something called a distribution, or distro, which is a full package that includes the kernel along with tools, software, and libraries needed to run a computer. Today, Linux is widely used in many places, from laptops and smartphones to smart TVs, servers, and even supercomputers. People like it due to its reliable, safety features, and easy customization.

This article includes several current statistical analyses from different sources, including key features, popular Linux distributions, reasons for using, use cases, how to get started, various challenges, significance in today’s world, and many others.

For more information on CDC.gov metrics please see http://www.cdc.gov/metrics/

Below you’ll find a month by month breakdown of traffic on the australia.gov.au website along the following lines:

• Pageviews
• Visits
• Pages per visit
• Average time on page
• Devices

This data is generated using Google analytics.

Please Note: This is an initial version of the data only. We’re looking forward to hearing your feedback on what other metrics are of interest to you. Please let us know by sending an email to data@digital.gov.au.

Website Visitor Tracking Tool Market Outlook

The global website visitor tracking tool market size was valued at $1.1 billion in 2023 and is projected to reach $4.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 15.2%. The growth factor driving this market includes the rising need for businesses to understand and enhance customer engagement, optimize marketing strategies, and increase conversion rates.

One of the primary growth drivers for the website visitor tracking tool market is the increasing reliance on digital marketing and online sales channels. As businesses across various industries pivot towards online platforms to attract, engage, and convert customers, the need for robust tools to track and analyze website visitors has become paramount. These tools provide invaluable insights into user behavior, preferences, and engagement patterns, enabling companies to tailor their marketing efforts more effectively and drive higher conversion rates. Additionally, advancements in data analytics and artificial intelligence are further enhancing the capabilities of these tools, making them more precise and insightful.

Another significant factor contributing to market growth is the rising adoption of customer-centric business strategies. In todayÂ’s competitive business environment, understanding customer needs and preferences is crucial for gaining a competitive edge. Website visitor tracking tools enable businesses to gather comprehensive data about their visitors, such as their browsing history, time spent on different pages, and interaction with various elements on the site. This data can be used to create personalized experiences, improve customer retention, and drive customer loyalty. Furthermore, the integration of these tools with customer relationship management (CRM) systems and other business applications is making it easier for companies to leverage visitor data for better decision-making.

The growing emphasis on data-driven marketing is also playing a significant role in the expansion of the website visitor tracking tool market. Businesses are increasingly recognizing the importance of data in understanding customer behavior and optimizing marketing strategies. Website visitor tracking tools provide detailed analytics and reporting features that help marketers assess the performance of their campaigns, identify areas for improvement, and measure return on investment (ROI). Additionally, these tools facilitate A/B testing and other optimization techniques, enabling marketers to fine-tune their strategies and achieve better outcomes.

Affiliate Tracking Software plays a crucial role in the digital marketing ecosystem, particularly for businesses looking to expand their reach through affiliate partnerships. This software enables companies to track the performance of their affiliate marketing campaigns by monitoring clicks, conversions, and sales generated by affiliate links. By providing detailed insights into which affiliates are driving the most traffic and revenue, businesses can optimize their affiliate programs for better results. Additionally, Affiliate Tracking Software helps in managing payouts and commissions, ensuring transparency and efficiency in affiliate relationships. As the demand for performance-based marketing continues to rise, the adoption of robust affiliate tracking solutions is becoming increasingly important for businesses aiming to maximize their marketing ROI.

Regionally, North America holds a significant share of the website visitor tracking tool market, driven by the high adoption of digital marketing technologies and the presence of numerous leading market players. The region's advanced technological infrastructure and the growing emphasis on data-driven decision-making are further propelling market growth. Europe and Asia Pacific are also witnessing substantial growth, supported by the increasing digital transformation initiatives and the rising number of online businesses in these regions. The Middle East & Africa and Latin America markets are expected to grow at a steady pace, driven by the gradual adoption of digital marketing tools and the growing awareness about the benefits of website visitor tracking.

Component Analysis

The website visitor tracking tool market can be segmented by component into software and services. The software segment holds the largest share of the market, driven by the high demand for advanced tracking and analytics solutions. These software solut

A global study found that the number of referrals to news and media sites from Facebook fell from 2.3 billion in December 2022 to as low as 1.2 billion in November 2023, marking a 48 percent decline year on year. X (formerly Twitter) and Instagram also saw decreases in aggregate traffic to news and media properties.