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Daily utilization metrics for data.lacity.org and geohub.lacity.org. Updated monthly

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.

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.

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.

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.

Click Web Traffic Combined with Transaction Data: A New Dimension of Shopper Insights

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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

Relationship









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.'

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.

The number of unique visitors to the Smithsonian Institution's websites declined by 11.6 percent in 2024 over the previous fiscal year. In the fiscal year ending September 30, 2024, the combined number of visits across all Smithsonian websites totaled almost 150 million.

Unique visitors, total sessions, and bounce rate for lacity.org, the main website for the City of Los Angeles.

TrueCar is a marketplace and e-commerce site which provides new and used car buyers with pricing and information related to the car buying experience. In the second quarter of 2021, the company recorded *** million average monthly unique visitors to its site, the most of any quarter listed. Since then, quarterly website traffic has been declining, reaching *** million unique visitors in the most recent quarter.

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?

This dataset was used in the Kaggle Wikipedia Web Traffic forecasting competition. It contains 145063 daily time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2017-09-10.

The original dataset contains missing values. They have been simply replaced by zeros.

Visitor Tracking Software Tools Market Outlook

As of 2023, the global market size for Visitor Tracking Software Tools is estimated to be approximately USD 1.2 billion, and it is projected to reach USD 3.5 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 12.5% from 2024 to 2032. The continuous growth in digital marketing and the increasing need for businesses to optimize their customer engagement strategies are primary factors driving this market expansion.

The surge in digital transformation across various industries is a significant factor propelling the growth of the visitor tracking software tools market. With more businesses moving online, there is an amplified need for tools that can track visitor interactions, behaviors, and preferences. These tools provide invaluable insights that help businesses understand their customer base, improve user experience, and increase conversion rates. Moreover, the rising adoption of data-driven decision-making processes is bolstering the demand for such software solutions, as they offer precise analytics and reporting functionalities.

Another pivotal driver of market growth is the increasing emphasis on personalized customer experiences. In today's competitive business environment, understanding and catering to the unique needs and preferences of each customer is crucial. Visitor tracking software tools enable businesses to gather detailed data about their website visitors, allowing them to tailor their marketing strategies and offers accordingly. This personalized approach not only enhances customer satisfaction but also fosters brand loyalty and boosts sales, further fueling the market growth.

The proliferation of e-commerce and the growing importance of online presence have also significantly contributed to the market expansion. As more consumers prefer online shopping and digital interactions, businesses are investing heavily in advanced technologies to monitor and analyze visitor activities on their websites. Visitor tracking software tools provide comprehensive insights into visitor behavior, helping businesses enhance their online strategies, improve customer retention, and drive revenue growth. Additionally, the increasing adoption of mobile devices and the rising internet penetration globally are further augmenting the demand for these tools.

In addition to these factors, the integration of Customer Journey Mapping Tools is becoming increasingly essential for businesses aiming to enhance their visitor tracking capabilities. These tools allow companies to visualize and analyze the entire customer journey, from initial contact to conversion, providing a comprehensive view of customer interactions across various touchpoints. By leveraging customer journey mapping, businesses can identify pain points and opportunities for improvement, enabling them to create more personalized and effective marketing strategies. This integration not only enhances the overall customer experience but also contributes to higher conversion rates and customer retention, driving further growth in the visitor tracking software tools market.

Regionally, North America holds a dominant position in the visitor tracking software tools market, owing to the high adoption rate of advanced technologies and the presence of numerous key market players in the region. The growing emphasis on digital marketing strategies and the increasing investments in customer analytics solutions are driving the market growth in this region. Additionally, Asia Pacific is expected to witness substantial growth during the forecast period, attributed to the rapid digitalization of businesses, significant advancements in IT infrastructure, and the burgeoning e-commerce sector in countries like China, India, and Japan.

Component Analysis

The visitor tracking software tools market can be segmented by component into Software and Services. The Software segment encompasses various types of tracking software, including web analytics tools, heat map tools, session replay software, and others. These software solutions are designed to provide businesses with detailed insights into visitor behavior, helping them enhance their online presence and improve customer engagement. Advancements in software technologies, such as artificial intelligence and machine learning, are further enhancing the capabilities of these tools, making them more efficient and accurate.

Services, on the other hand, inclu

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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 ---

About this dataset

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.

How to use this dataset

• Analyze 11/1/2016 in relation to 2/1/2017
• Study the influence of 4/1/2017 on 1/1/2017
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Chase Willden

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

In December 2024, social video platform YouTube recorded approximately ** billion visits on ****** and over ** billion visits from users on ******* devices. The web visitors traffic count from *********************** appeared consistently higher than the ******* visit count in the examined months.

Moving away from plain-text DNS communications