Unlock the Potential of Your Web Traffic with Advanced Data Resolution

In the digital age, understanding and leveraging web traffic data is crucial for businesses aiming to thrive online. Our pioneering solution transforms anonymous website visits into valuable B2B and B2C contact data, offering unprecedented insights into your digital audience. By integrating our unique tag into your website, you unlock the capability to convert 25-50% of your anonymous traffic into actionable contact rows, directly deposited into an S3 bucket for your convenience. This process, known as "Web Traffic Data Resolution," is at the forefront of digital marketing and sales strategies, providing a competitive edge in understanding and engaging with your online visitors.

Comprehensive Web Traffic Data Resolution Our product stands out by offering a robust solution for "Web Traffic Data Resolution," a process that demystifies the identities behind your website traffic. By deploying a simple tag on your site, our technology goes to work, analyzing visitor behavior and leveraging proprietary data matching techniques to reveal the individuals and businesses behind the clicks. This innovative approach not only enhances your data collection but does so with respect for privacy and compliance standards, ensuring that your business gains insights ethically and responsibly.

Deep Dive into Web Traffic Data At the core of our solution is the sophisticated analysis of "Web Traffic Data." Our system meticulously collects and processes every interaction on your site, from page views to time spent on each section. This data, once anonymous and perhaps seen as abstract numbers, is transformed into a detailed ledger of potential leads and customer insights. By understanding who visits your site, their interests, and their contact information, your business is equipped to tailor marketing efforts, personalize customer experiences, and streamline sales processes like never before.

Benefits of Our Web Traffic Data Resolution Service Enhanced Lead Generation: By converting anonymous visitors into identifiable contact data, our service significantly expands your pool of potential leads. This direct enhancement of your lead generation efforts can dramatically increase conversion rates and ROI on marketing campaigns.

Targeted Marketing Campaigns: Armed with detailed B2B and B2C contact data, your marketing team can create highly targeted and personalized campaigns. This precision in marketing not only improves engagement rates but also ensures that your messaging resonates with the intended audience.

Improved Customer Insights: Gaining a deeper understanding of your web traffic enables your business to refine customer personas and tailor offerings to meet market demands. These insights are invaluable for product development, customer service improvement, and strategic planning.

Competitive Advantage: In a digital landscape where understanding your audience can make or break your business, our Web Traffic Data Resolution service provides a significant competitive edge. By accessing detailed contact data that others in your industry may overlook, you position your business as a leader in customer engagement and data-driven strategies.

Seamless Integration and Accessibility: Our solution is designed for ease of use, requiring only the placement of a tag on your website to start gathering data. The contact rows generated are easily accessible in an S3 bucket, ensuring that you can integrate this data with your existing CRM systems and marketing tools without hassle.

How It Works: A Closer Look at the Process Our Web Traffic Data Resolution process is streamlined and user-friendly, designed to integrate seamlessly with your existing website infrastructure:

Tag Deployment: Implement our unique tag on your website with simple instructions. This tag is lightweight and does not impact your site's loading speed or user experience.

Data Collection and Analysis: As visitors navigate your site, our system collects web traffic data in real-time, analyzing behavior patterns, engagement metrics, and more.

Resolution and Transformation: Using advanced data matching algorithms, we resolve the collected web traffic data into identifiable B2B and B2C contact information.

Data Delivery: The resolved contact data is then securely transferred to an S3 bucket, where it is organized and ready for your access. This process occurs daily, ensuring you have the most up-to-date information at your fingertips.

Integration and Action: With the resolved data now in your possession, your business can take immediate action. From refining marketing strategies to enhancing customer experiences, the possibilities are endless.

Security and Privacy: Our Commitment Understanding the sensitivity of web traffic data and contact information, our solution is built with security and privacy at its core. We adhere to strict data protection regulat...

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.

The dataset contains information about web requests to a single website. It's a time series dataset, which means it tracks data over time, making it great for machine learning analysis.

In the second quarter of 2025, mobile devices (excluding tablets) accounted for 62.54 percent of global website traffic. Since consistently maintaining a share of around 50 percent beginning in 2017, mobile usage surpassed this threshold in 2020 and has demonstrated steady growth in its dominance of global web access. 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.

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.

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

As of the second quarter of 2025, ***** percent of web traffic in the United States originated from mobile devices, down from over ** percent in the last quarter of 2024. In comparison, over ********** of web traffic worldwide was generated via mobile in the last examined period.

This dataset originates from DataCamp. Many users have reposted copies of the CSV on Kaggle, but most of those uploads omit the original instructions, business context, and problem framing. In this upload, I’ve included that missing context in the About Dataset so the reader of my notebook or any other notebook can fully understand how the data was intended to be used and the intended problem framing.

Note: I have also uploaded a visualization of the workflow I personally took to tackle this problem, but it is not part of the dataset itself. Additionally, I created a PowerPoint presentation based on my work in the notebook, which you can download from here:
PPTX Presentation

Recipe Site Traffic

From: Head of Data Science
Received: Today
Subject: New project from the product team

Hey!

I have a new project for you from the product team. Should be an interesting challenge. You can see the background and request in the email below.

I would like you to perform the analysis and write a short report for me. I want to be able to review your code as well as read your thought process for each step. I also want you to prepare and deliver the presentation for the product team - you are ready for the challenge!

They want us to predict which recipes will be popular 80% of the time and minimize the chance of showing unpopular recipes. I don't think that is realistic in the time we have, but do your best and present whatever you find.

You can find more details about what I expect you to do here. And information on the data here.

I will be on vacation for the next couple of weeks, but I know you can do this without my support. If you need to make any decisions, include them in your work and I will review them when I am back.

Good Luck!

From: Product Manager - Recipe Discovery
To: Head of Data Science
Received: Yesterday
Subject: Can you help us predict popular recipes?

Hi,

We haven't met before but I am responsible for choosing which recipes to display on the homepage each day. I have heard about what the data science team is capable of and I was wondering if you can help me choose which recipes we should display on the home page?

At the moment, I choose my favorite recipe from a selection and display that on the home page. We have noticed that traffic to the rest of the website goes up by as much as 40% if I pick a popular recipe. But I don't know how to decide if a recipe will be popular. More traffic means more subscriptions so this is really important to the company.

Can your team: - Predict which recipes will lead to high traffic? - Correctly predict high traffic recipes 80% of the time?

We need to make a decision on this soon, so I need you to present your results to me by the end of the month. Whatever your results, what do you recommend we do next?

Look forward to seeing your presentation.

About Tasty Bytes

Tasty Bytes was founded in 2020 in the midst of the Covid Pandemic. The world wanted inspiration so we decided to provide it. We started life as a search engine for recipes, helping people to find ways to use up the limited supplies they had at home.

Now, over two years on, we are a fully fledged business. For a monthly subscription we will put together a full meal plan to ensure you and your family are getting a healthy, balanced diet whatever your budget. Subscribe to our premium plan and we will also deliver the ingredients to your door.

Example Recipe

This is an example of how a recipe may appear on the website, we haven't included all of the steps but you should get an idea of what visitors to the site see.

Tomato Soup

Servings: 4
Time to make: 2 hours
Category: Lunch/Snack
Cost per serving: $

Nutritional Information (per serving) - Calories 123 - Carbohydrate 13g - Sugar 1g - Protein 4g

Ingredients: - Tomatoes - Onion - Carrot - Vegetable Stock

Method: 1. Cut the tomatoes into quarters….

Data Information

The product manager has tried to make this easier for us and provided data for each recipe, as well as whether there was high traffic when the recipe was featured on the home page.

As you will see, they haven't given us all of the information they have about each recipe.

You can find the data here.

I will let you decide how to process it, just make sure you include all your decisions in your report.

Don't forget to double check the data really does match what they say - it might not.

In November 2025, mobile devices excluding tablets accounted for over ***** percent of web page views worldwide. Meanwhile, over ***** percent of webpage views in Africa were generated via mobile. In contrast, just over half of web traffic in North America still took place via desktop connections, with mobile only accounting for ***** percent of total web traffic. While regional infrastructure remains an important factor in broadband vs. mobile coverage, most of the world has had their eyes on the recent 5G rollout across the globe, spearheaded by tech leaders China and the United States. The number of mobile 5G subscriptions worldwide is forecast to reach more than ***** billion by 2028. Social media: room for growth in Africa and southern Asia Overall, more than ** percent of the world’s mobile internet subscribers are also active on social media. A fast-growing market, with newcomers such as TikTok taking the world by storm, marketers have been cashing in on social media’s reach. Overall, social media penetration is highest in Europe and America, while in Africa and southern Asia, there is still room for growth. As of 2021, Facebook and Google-owned YouTube are the most popular social media platforms worldwide. Facebook and Instagram are most effective With nearly ***** billion users, it is no wonder that Facebook remains the social media avenue of choice for the majority of marketers across the world. Instagram, meanwhile, was the second most popular outlet. Both platforms are low-cost and support short-form content, known for its universal consumer appeal and answering to the most important benefits of using these kinds of platforms for business and advertising purposes.

We provide foot traffic data across the web with 30+ enriched attributes, including demographics, devices, web activity, intent and foot traffic insights. We help marketers, agencies, and platforms build precise foot traffic audience segments, optimize foot traffic targeting, attribute locations, and understand cross-device journeys. Our continuously updated foot traffic datasets deliver real-time foot traffic insights that power smarter location-based campaigns and future-ready strategies.

Leverage our foot traffic data solutions for the following use cases: - Foot Traffic Data Validation & Model Building - Cultural & Seasonal Foot Traffic Insights - Targeted, Data-Driven Foot Traffic Advertising - Foot Traffic & Location-Based Targeting - Trial & Partnership Transparency

With AdPreference, expect the following key benefits through our partnership: - Augment Foot Traffic Data Attributes - Enrich CRM - Personalize Foot Traffic Audiences - Fraud Prevention - Foot Traffic Audience Curation

Access the largest and most customizable foot traffic data segments with AdPreference today. Supercharge your needs with unique and enriched foot traffic data not found anywhere else.

For more information, please visit https://www.adpreference.co/

Snapshot img

Global network traffic analytics Industry Overview

Technavio’s analysts have identified the increasing use of network traffic analytics solutions to be one of major factors driving market growth. With the rapidly changing IT infrastructure, security hackers can steal valuable information through various modes. With the increasing dependence on web applications and websites for day-to-day activities and financial transactions, the instances of theft have increased globally. Also, the emergence of social networking websites has aided the malicious attackers to extract valuable information from vulnerable users. The increasing consumer dependence on web applications and websites for day-to-day activities and financial transactions are further increasing the risks of theft. This encourages the organizations to adopt network traffic analytics solutions.

Want a bigger picture? Try a FREE sample of this report now!

See the complete table of contents and list of exhibits, as well as selected illustrations and example pages from this report.

Companies covered

The network traffic analytics market is fairly concentrated due to the presence of few established companies offering innovative and differentiated software and services. By offering a complete analysis of the competitiveness of the players in the network monitoring tools market offering varied software and services, this network traffic analytics industry analysis report will aid clients identify new growth opportunities and design new growth strategies.

The report offers a complete analysis of a number of companies including:

Allot
Cisco Systems
IBM
Juniper Networks
Microsoft
Symantec

Network traffic analytics market growth based on geographic regions

Americas
APAC
EMEA

With a complete study of the growth opportunities for the companies across regions such as the Americas, APAC, and EMEA, our industry research analysts have estimated that countries in the Americas will contribute significantly to the growth of the network monitoring tools market throughout the predicted period.

Network traffic analytics market growth based on end-user

Telecom
BFSI
Healthcare
Media and entertainment

According to our market research experts, the telecom end-user industry will be the major end-user of the network monitoring tools market throughout the forecast period. Factors such as increasing use of network traffic analytics solutions and increasing use of mobile devices at workplaces will contribute to the growth of the market shares of the telecom industry in the network traffic analytics market.

Key highlights of the global network traffic analytics market for the forecast years 2018-2022:

CAGR of the market during the forecast period 2018-2022
Detailed information on factors that will accelerate the growth of the network traffic analytics market during the next five years
Precise estimation of the global network traffic analytics market size and its contribution to the parent market
Accurate predictions on upcoming trends and changes in consumer behavior
Growth of the network traffic analytics industry across various geographies such as the Americas, APAC, and EMEA
A thorough analysis of the market’s competitive landscape and detailed information on several vendors
Comprehensive information about factors that will challenge the growth of network traffic analytics companies

Get more value with Technavio’s INSIGHTS subscription platform! Gain easy access to all of Technavio’s reports, along with on-demand services. Try the demo

This market research report analyzes the market outlook and provides a list of key trends, drivers, and challenges that are anticipated to impact the global network traffic analytics market and its stakeholders over the forecast years.

The global network traffic analytics market analysts at Technavio have also considered how the performance of other related markets in the vertical will impact the size of this market till 2022. Some of the markets most likely to influence the growth of the network traffic analytics market over the coming years are the Global Network as a Service Market and the Global Data Analytics Outsourcing Market.

Technavio’s collection of market research reports offer insights into the growth of markets across various industries. Additionally, we also provide customized reports based on the specific requirement of our clients.

We provide location data across the web with 30+ enriched attributes, including demographics, devices, web activity, intent and location insights. We help marketers, agencies, and platforms build precise location audience segments, optimize location targeting, attribute locations, and understand cross-device journeys. Our continuously updated location datasets deliver real-time location insights that power smarter location-based campaigns and future-ready strategies.

Leverage our location data solutions for the following use cases: - Location Data Validation & Model Building - Cultural & Seasonal Campaign Insights - Targeted, Data-Driven Location Advertising - Travel & Location-Based Targeting - Trial & Partnership Transparency

With AdPreference, expect the following key benefits through our partnership: - Augment Location Data Attributes - Enrich CRM - Personalize Location Audiences - Fraud Prevention - Location Audience Curation

Access the largest and most customizable location data segments with AdPreference today. Supercharge your needs with unique and enriched location data not found anywhere else.

For more information, please visit https://www.adpreference.co/

Data dictionary: Page_Title: Title of webpage used for pages of the website www.cityofrochester.gov Pageviews: Total number of pages viewed over the course of the calendar year listed in the year column. Repeated views of a single page are counted. Unique_Pageviews: Unique Pageviews - The number of sessions during which a specified page was viewed at least once. A unique pageview is counted for each URL and page title combination. Avg_Time: Average amount of time users spent looking at a specified page or screen. Entrances: The number of times visitors entered the website through a specified page.Bounce_Rate: " A bounce is a single-page session on your site. In Google Analytics, a bounce is calculated specifically as a session that triggers only a single request to the Google Analytics server, such as when a user opens a single page on your site and then exits without triggering any other requests to the Google Analytics server during that session. Bounce rate is single-page sessions on a page divided by all sessions that started with that page, or the percentage of all sessions on your site in which users viewed only a single page and triggered only a single request to the Google Analytics server. These single-page sessions have a session duration of 0 seconds since there are no subsequent hits after the first one that would let Google Analytics calculate the length of the session. "Exit_Rate: The number of exits from a page divided by the number of pageviews for the page. This is inclusive of sessions that started on different pages, as well as “bounce” sessions that start and end on the same page. For all pageviews to the page, Exit Rate is the percentage that were the last in the session. Year: Calendar year over which the data was collected. Data reflects the counts for each metric from January 1st through December 31st.

The data set provided (traffic.csv) contains web traffic data ("events") from a few different pages ("links") over 7 days including various categorical dimensions about the geographic origin of that traffic as well as a page's content: isrc.

We provide foot traffic data across the web with 30+ enriched attributes, including demographics, devices, web activity, intent and foot traffic insights. We help marketers, agencies, and platforms build precise foot traffic audience segments, optimize foot traffic targeting, attribute locations, and understand cross-device journeys. Our continuously updated foot traffic datasets deliver real-time foot traffic insights that power smarter location-based campaigns and future-ready strategies.

Leverage our foot traffic data solutions for the following use cases: - Foot Traffic Data Validation & Model Building - Cultural & Seasonal Foot Traffic Insights - Targeted, Data-Driven Foot Traffic Advertising - Foot Traffic & Location-Based Targeting - Trial & Partnership Transparency

With AdPreference, expect the following key benefits through our partnership: - Augment Foot Traffic Data Attributes - Enrich CRM - Personalize Foot Traffic Audiences - Fraud Prevention - Foot Traffic Audience Curation

Access the largest and most customizable foot traffic data segments with AdPreference today. Supercharge your needs with unique and enriched foot traffic data not found anywhere else.

For more information, please visit https://www.adpreference.co/

Traffic analytics, rankings, and competitive metrics for cargo.site as of October 2025

Our Data Center Traffic web traffic dataset adds a critical layer of protection to your marketing stack by identifying and filtering web traffic generated from the IP addresses of suspicious data center sources. These signals often come from bots, scrapers, or emulators that disguise themselves as real users but deliver no value to your campaigns. Left unchecked, they can distort performance metrics, inflate engagement numbers, and drain your ad budget.

Leverage our web traffic data solutions for the following use cases: - Invalid Web Traffic Prevention - Data Hygiene & Model Building - Audience Quality Assurance - Trial & Partnership Transparency

With AdPreference, expect the following key benefits through our partnership: - Protect Your Ad Spend - Enhance Cybersecurity - Improve Campaign Performance - Strengthen Brand Integrity - Reduce Ad Fraud

By continuously monitoring and updating our web traffic intelligence, we empower marketers, agencies, and platforms to distinguish legitimate human activity from fraudulent traffic at scale. The result is cleaner datasets, more accurate audience models, and campaigns that perform against true user engagement. With our web traffic dataset, you can protect ad spend, maintain data integrity, and reinforce trust across your digital ecosystem.

For more information, please visit https://www.adpreference.co/

We provide location data across the web with 30+ enriched attributes, including demographics, devices, web activity, intent and location insights. We help marketers, agencies, and platforms build precise location audience segments, optimize location targeting, attribute locations, and understand cross-device journeys. Our continuously updated location datasets deliver real-time location insights that power smarter location-based campaigns and future-ready strategies.

Leverage our location data solutions for the following use cases: - Location Data Validation & Model Building - Cultural & Seasonal Campaign Insights - Targeted, Data-Driven Location Advertising - Travel & Location-Based Targeting - Trial & Partnership Transparency

With AdPreference, expect the following key benefits through our partnership: - Augment Location Data Attributes - Enrich CRM - Personalize Location Audiences - Fraud Prevention - Location Audience Curation

Access the largest and most customizable location data segments with AdPreference today. Supercharge your needs with unique and enriched location data not found anywhere else.

For more information, please visit https://www.adpreference.co/

Web Analytics Market size was valued at USD 6.16 Billion in 2024 and is projected to reach USD 24.07 Billion by 2032, growing at a CAGR of 18.58% during the forecast period 2026-2032.Global Web Analytics Market DriversThe digital landscape is in constant flux, and at its core, understanding user behavior is paramount for any business aiming to thrive. This imperative fuels the robust expansion of the Web Analytics Market, driven by a confluence of technological advancements, evolving business needs, and shifting consumer behaviors. Let's delve into the major forces propelling this vital industry forward.Digitalization and the Explosive Growth of Online Presence: The most fundamental driver is the relentless march of digitalization. Businesses across every sector are establishing, expanding, and optimizing their online presence, whether through sophisticated e-commerce platforms, informative corporate websites, or engaging mobile applications. As more operations, customer interactions, and commerce migrate to the digital realm, the sheer volume of online activity creates an insatiable demand for tools that can decipher user journeys, measure website performance, and identify areas for improvement. This foundational shift necessitates web analytics to transform raw digital interactions into actionable insights, making it indispensable for strategic decision-making in the modern business environment.The Imperative for Data-Driven Decision Making: In today's competitive landscape, gut feelings and anecdotal evidence are no longer sufficient. Businesses are increasingly recognizing the critical importance of basing their strategies on empirical data. Web analytics provides this crucial foundation, offering deep insights into customer behavior, site usage patterns, conversion funnels, and potential drop-off points. From optimizing marketing spend to refining product offerings and enhancing user experience, data-driven decision-making, powered by comprehensive web analytics, allows companies to minimize risks, maximize opportunities, and achieve measurable growth, thereby solidifying its position as a core business intelligence tool.Proliferation of Mobile Devices and Mobile Web Traffic: The smartphone revolution has profoundly reshaped how users interact with the internet. With billions of people globally accessing the web predominantly via mobile devices and tablets, understanding mobile-specific behaviors has become a paramount concern. Web analytics tools are evolving rapidly to effectively capture and analyze interactions across a myriad of devices, operating systems, and browser types. This includes tracking mobile app usage, responsive website performance, and ensuring a seamless cross-device user experience. The pervasive nature of mobile traffic means that robust mobile analytics capabilities are no longer a luxury but a necessity for any comprehensive web analytics solution.

The people from Czech are publishing a dataset for the HTTPS traffic classification.

Since the data were captured mainly in the real backbone network, they omitted IP addresses and ports. The datasets consist of calculated from bidirectional flows exported with flow probe Ipifixprobe. This exporter can export a sequence of packet lengths and times and a sequence of packet bursts and time. For more information, please visit ipfixprobe repository (Ipifixprobe).

During research, they divided HTTPS into five categories: L -- Live Video Streaming, P -- Video Player, M -- Music Player, U -- File Upload, D -- File Download, W -- Website, and other traffic.

They have chosen the service representatives known for particular traffic types based on the Alexa Top 1M list and Moz's list of the most popular 500 websites for each category. They also used several popular websites that primarily focus on the audience in Czech. The identified traffic classes and their representatives are provided below:

Live Video Stream Twitch, Czech TV, YouTube Live Video Player DailyMotion, Stream.cz, Vimeo, YouTube Music Player AppleMusic, Spotify, SoundCloud File Upload/Download FileSender, OwnCloud, OneDrive, Google Drive Website and Other Traffic Websites from Alexa Top 1M list