A complete list of live websites using the angular-storage technology, compiled through global website indexing conducted by WebTechSurvey.

While kmart.com.au generated one of the highest web traffics across popular department store websites in Australia in February 2025 at over 20.5 million site visits, users of the department store website viewed only an average of 4.95 pages per visit. While harrisscarfe.com.au had a lower overall web traffic, it scored a higher page engagement rate, with an average of 6.28 pages per visit. Nonetheless, higher page visits in a single session does not necessarily equate to greater overall engagement, as more pages may have been viewed due to user difficulties in navigating web layouts and finding products.

A complete list of live websites using the Store Schema technology, compiled through global website indexing conducted by WebTechSurvey.

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In 2022, shopping apps were the most commonly used when shopping on online devices. Following were websites, with ** percent of responses.

A complete list of live websites using the Google Trusted Stores technology, compiled through global website indexing conducted by WebTechSurvey.

Websites scraped by browsertrix-crawler.

This statistic shows the share of dresses at department store websites that are available in plus sizes in the United States in 2016. In that year, *** percent of dresses at Nordstrom's website were available in plus-sizes.

Cookie and Website Tracker Scanning Software Market Outlook

The global cookie and website tracker scanning software market is poised for significant growth, with its market size valued at approximately $1.5 billion in 2023 and projected to reach around $4.2 billion by 2032, reflecting a compound annual growth rate (CAGR) of approximately 12.5%. This market's expansion is largely driven by the increasing emphasis on data privacy regulations and compliance, which necessitates businesses to implement robust solutions for monitoring and managing cookies and website trackers. The growing digitalization across various sectors and the rising consumer awareness regarding data privacy are also contributing significantly to the market's upward trajectory.

One of the primary growth factors propelling the cookie and website tracker scanning software market is the proliferation of stringent data privacy regulations worldwide. Laws such as the General Data Protection Regulation (GDPR) in Europe, the California Consumer Privacy Act (CCPA) in the United States, and other similar legislation globally mandate businesses to enhance their data protection measures. These regulations require organizations to provide transparency regarding data collection practices and ensure that users have control over their personal information. As a result, companies are increasingly adopting cookie and tracker scanning solutions to comply with these legal requirements and avoid potential penalties and reputational damage, thus driving market growth.

Another significant factor contributing to the market's expansion is the escalating awareness and concern among consumers regarding their online privacy. In an era where digital interactions are part and parcel of daily life, consumers are becoming more vigilant about how their data is collected, stored, and utilized by websites. This heightened awareness compels businesses to adopt ethical data practices and implement technologies that offer consumers clear insights into cookie usage and tracking activities. Consequently, organizations are integrating cookie and website tracker scanning software into their operations to enhance user trust and ensure transparency, thereby fostering market growth.

The rapid advancement of technology, leading to increased digitalization, is also a key driver for this market. As businesses across various industries embrace digital transformation, the online ecosystem becomes more complex with an influx of data tracking methods. This complexity necessitates the use of sophisticated tools to monitor, analyze, and manage website trackers effectively. The integration of advanced analytics and AI capabilities into scanning software enables organizations to gain deeper insights into user behavior while ensuring compliance with privacy regulations. This technological evolution is anticipated to further fuel the market's growth over the forecast period.

As the digital landscape continues to evolve, the role of a Consent Management Platform (CMP) becomes increasingly crucial in the realm of data privacy. A CMP serves as a centralized solution for managing user consent across various digital platforms, ensuring that businesses comply with data protection regulations such as GDPR and CCPA. By providing users with clear options to manage their consent preferences, these platforms enhance transparency and trust. Organizations are increasingly integrating CMPs into their operations to streamline consent management processes and reduce the risk of non-compliance. This integration not only helps in maintaining regulatory compliance but also strengthens the relationship between businesses and their users by respecting their privacy choices.

Regionally, North America holds a substantial share in the global cookie and website tracker scanning software market, owing to the early adoption of technology and stringent data privacy regulations in the region. The presence of major technology companies further fuels innovation and development in this market. Europe is also a significant market player, driven by the stringent GDPR regulations that necessitate robust compliance solutions. Meanwhile, the Asia Pacific region is expected to witness the fastest growth rate due to increasing internet penetration, digitalization initiatives, and growing awareness regarding data privacy. As economies in the region continue to develop, the demand for effective data protection solutions is likely to surge, contributing to the market's overall growth.

C

More than 60 percent of surveyed consumers in the United States between 18 and 24 years visited the website store before going to the store in person, according to a survey in 2024. Almost half of those aged between 55 and 64 did not visit the website of the store at any point of the purchase process.

A complete list of live websites using the Image Store technology, compiled through global website indexing conducted by WebTechSurvey.

1) Data Introduction • The Website dataset designed to facilitate the development of models for URL-based website classification.

2) Data Utilization (1) Website data has characteristics that: • This dataset is crucial for training models that can automatically classify websites based on their URL structures. (2) Website data can be used to: • Enhancing cybersecurity measures by detecting malicious websites. • Improving content filtering systems for safer browsing experiences.

Across popular department store websites among Australian shoppers in February 2025, kmart.com.au registered the highest number of site visits. Of these site visits, mobile visits were the leading traffic source and held a share of around 61 percent. bigw.com.au came in second by number of site visits, with mobile visits holding the largest share at over 66 percent of its total site visits.

This dataset is about stocks. It has 1 row and is filtered where the company is Global Self Storage. It features 8 columns including stock name, company, exchange, and exchange symbol.

Code:

Packet_Features_Generator.py & Features.py

To run this code:

pkt_features.py [-h] -i TXTFILE [-x X] [-y Y] [-z Z] [-ml] [-s S] -j

-h, --help show this help message and exit -i TXTFILE input text file -x X Add first X number of total packets as features. -y Y Add first Y number of negative packets as features. -z Z Add first Z number of positive packets as features. -ml Output to text file all websites in the format of websiteNumber1,feature1,feature2,... -s S Generate samples using size s. -j

Purpose:

Turns a text file containing lists of incomeing and outgoing network packet sizes into separate website objects with associative features.

Uses Features.py to calcualte the features.

startMachineLearning.sh & machineLearning.py

To run this code:

bash startMachineLearning.sh

This code then runs machineLearning.py in a tmux session with the nessisary file paths and flags

Options (to be edited within this file):

--evaluate-only to test 5 fold cross validation accuracy

--test-scaling-normalization to test 6 different combinations of scalers and normalizers

Note: once the best combination is determined, it should be added to the data_preprocessing function in machineLearning.py for future use

--grid-search to test the best grid search hyperparameters - note: the possible hyperparameters must be added to train_model under 'if not evaluateOnly:' - once best hyperparameters are determined, add them to train_model under 'if evaluateOnly:'

Purpose:

Using the .ml file generated by Packet_Features_Generator.py & Features.py, this program trains a RandomForest Classifier on the provided data and provides results using cross validation. These results include the best scaling and normailzation options for each data set as well as the best grid search hyperparameters based on the provided ranges.

Data

Encrypted network traffic was collected on an isolated computer visiting different Wikipedia and New York Times articles, different Google search queres (collected in the form of their autocomplete results and their results page), and different actions taken on a Virtual Reality head set.

Data for this experiment was stored and analyzed in the form of a txt file for each experiment which contains:

First number is a classification number to denote what website, query, or vr action is taking place.

The remaining numbers in each line denote:

The size of a packet,

and the direction it is traveling.

negative numbers denote incoming packets

positive numbers denote outgoing packets

Figure 4 Data

This data uses specific lines from the Virtual Reality.txt file.

The action 'LongText Search' refers to a user searching for "Saint Basils Cathedral" with text in the Wander app.

The action 'ShortText Search' refers to a user searching for "Mexico" with text in the Wander app.

The .xlsx and .csv file are identical

Each file includes (from right to left):

The origional packet data,

each line of data organized from smallest to largest packet size in order to calculate the mean and standard deviation of each packet capture,

and the final Cumulative Distrubution Function (CDF) caluclation that generated the Figure 4 Graph.

Data from Transnational Mod Languages (09-2018)/05 TML Website/TML Website Storage

As of May 2023, the most popular channel where U.S. shoppers research or buy beauty products they've never purchased before is a specialty beauty retailer’s website, with 71 percent of respondents going that route. Brand websites followed on the list with 57 percent of respondents, and Amazon was right behind them with 54 percent.

This statistic shows the results of a survey conducted in the United States in 2017 on website design as a criterion for online fashion stores. Some ** percent of respondents stated that to them the design of the website is not important when it comes to online fashion stores.The Survey Data Table for the Statista survey Online Fashion Retail in the United States 2017 contains the complete tables for the survey including various column headings.

Website Screenshot Software Market Outlook

The global website screenshot software market size was valued at USD 250 million in 2023 and is projected to reach USD 550 million by 2032, growing at a compound annual growth rate (CAGR) of 9.1% from 2024 to 2032. The primary growth driver for this market is the increasing need for detailed website analytics and competitive analysis, facilitated by the enhanced functionality that website screenshot software provides.

One of the significant growth factors contributing to the expansion of the website screenshot software market is the booming e-commerce sector. As businesses increasingly move online, the demand for tools that can capture, analyze, and archive website content has surged. E-commerce companies, in particular, rely heavily on website screenshot software to track their competitors' pricing strategies, promotional activities, and website design changes. Moreover, the emphasis on digital marketing strategies necessitates frequent monitoring and analysis of various web pages, propelling the demand for such software.

The rise in remote work is another critical factor driving the market growth. With teams working from various locations, the need for collaborative tools that facilitate real-time sharing of web content has become imperative. Website screenshot software allows team members to capture and share web pages seamlessly, aiding in better communication and faster decision-making. Such tools are particularly beneficial for web development and digital marketing teams, enabling them to provide visual feedback and suggestions efficiently.

Technological advancements and the integration of advanced features like automated screenshot capture, scheduling, and cloud storage capabilities are also contributing to market growth. These advancements make it easier for users to capture, store, and manage large volumes of web content. Additionally, the increasing adoption of cloud-based solutions offers flexibility and scalability, further boosting the adoption of website screenshot software. The continuous innovation in software capabilities is expected to sustain market growth over the forecast period.

In the realm of digital tools, Web Scraper Software plays a pivotal role in complementing website screenshot software. While screenshot software captures static images of web pages, web scraper software goes a step further by extracting data from websites for analysis. This capability is crucial for businesses that require detailed insights into competitor activities, market trends, and consumer behavior. By automating the data extraction process, web scraper software saves time and resources, allowing companies to focus on strategic decision-making. The synergy between website screenshot and web scraper software can significantly enhance a company's ability to conduct comprehensive web analytics and competitive analysis.

Regionally, North America holds a significant share of the website screenshot software market, driven by the presence of major technology companies and a high adoption rate of advanced digital tools. However, Asia Pacific is projected to witness the highest growth rate during the forecast period, thanks to the rapid digital transformation in emerging economies, increasing internet penetration, and the burgeoning e-commerce sector. Europe is also a key market, with growing investments in digital marketing and web development driving the demand for website screenshot software.

Deployment Type Analysis

The website screenshot software market is segmented into cloud-based and on-premises deployment. Cloud-based deployment is expected to dominate the market owing to its benefits such as ease of access, scalability, and lower upfront costs. Cloud-based solutions allow users to access the software from anywhere, making it highly suitable for remote teams and enterprises with multiple locations. This flexibility is a significant advantage, especially in the current scenario where remote working has become the norm for many organizations. Furthermore, cloud-based deployment facilitates automatic updates and maintenance, reducing the burden on in-house IT teams.

On-premises deployment, however, holds its significance in the market, particularly among large enterprises with stringent data security and compliance requirements. These organizations prefer to have complete control over their data and infrastructure, which is achievable through on-p

A complete list of live websites using the Top Store technology, compiled through global website indexing conducted by WebTechSurvey.