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 Website Visitor Tracking Software market is experiencing robust growth, driven by the increasing need for businesses to understand online customer behavior and optimize their digital strategies. This market, currently valued at approximately $5 billion in 2025, is projected to grow at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting both SMEs and large enterprises. Furthermore, the increasing sophistication of analytics features within these platforms allows for deeper insights into website traffic, user engagement, and conversion rates. This empowers businesses to personalize user experiences, refine marketing campaigns, and ultimately drive revenue growth. The market segmentation reveals a significant share held by cloud-based solutions due to their accessibility and flexibility, while the large enterprise segment is a primary revenue driver due to its higher spending capacity. Competition is intense, with established players like Google Analytics and Adobe Analytics alongside a burgeoning number of specialized providers offering unique features and functionalities. The competitive landscape is dynamic, with established players facing challenges from nimble startups innovating in areas like AI-powered behavioral analytics and personalized recommendations. While data privacy concerns and the increasing complexity of tracking regulations represent potential restraints, the overall market outlook remains positive. The continued growth of e-commerce, digital marketing, and the broader digital economy will fuel further demand for sophisticated visitor tracking solutions. Geographic expansion, particularly in rapidly developing economies within Asia-Pacific and Latin America, will contribute significantly to market expansion over the forecast period. The integration of website visitor tracking with other marketing automation and CRM tools is another key trend, further solidifying its importance within a comprehensive digital strategy. The market's future hinges on the continuous innovation in data analytics capabilities, the development of user-friendly interfaces, and the ability to adapt to evolving privacy regulations.

Explore our detailed website traffic dataset featuring key metrics like page views, session duration, bounce rate, traffic source, and conversion rates.

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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.

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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.

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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...

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.

description: Web traffic statistics for the top 2000 most visited pages on nyc.gov by month.; abstract: Web traffic statistics for the top 2000 most visited pages on nyc.gov by month.

This dataset provides the Austin Google Analytic. Google Analytics is a freemium web analytics service offered by Google that tracks and reports website traffic.

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The global website traffic analysis tool market is experiencing robust growth, driven by the increasing reliance on digital marketing and the need for businesses of all sizes to understand their online audience. The market, estimated at $15 billion in 2025, is projected to grow at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. The rising adoption of cloud-based solutions provides scalability and cost-effectiveness for businesses, particularly SMEs seeking affordable analytics. Moreover, the evolution of sophisticated analytics features, including advanced user behavior tracking and predictive analytics, enhances the value proposition for both SMEs and large enterprises. The market is segmented by application (SMEs and large enterprises) and by type (cloud-based and web-based), with cloud-based solutions dominating due to their accessibility and flexibility. Competitive pressures among numerous vendors, including established players like Google Analytics, Semrush, and Ahrefs, as well as emerging niche players, drive innovation and affordability, benefiting users. Geographic distribution shows strong growth across North America and Europe, with Asia-Pacific emerging as a high-growth region. However, factors such as data privacy concerns and the increasing complexity of website analytics can act as potential restraints. Despite these challenges, the continued expansion of e-commerce and digital marketing strategies across various industries will solidify the demand for robust website traffic analysis tools. The market is expected to witness further consolidation through mergers and acquisitions, with leading players investing heavily in research and development to enhance their offerings. The increasing need for real-time data analysis and integration with other marketing automation platforms will further shape market evolution. The emergence of AI-powered analytics, providing predictive insights and automated reporting, is transforming the industry and will continue to drive market expansion in the coming years. This makes this market an attractive landscape for investors and technology providers looking for strong future growth.

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?

Network Traffic Analysis Market is Segmented by Deployment (On-Premise, Cloud-Based, and Hybrid), Component (Solutions and Services), Organization Size (Large Enterprises and Small and Medium Enterprises), End-User Industry (BFSI, IT and Telecom, and More), and Geography. The Market Sizes and Forecasts are Provided in Value (in USD Million) for all the Above Segments.

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User-Centric Approach: Unlike traditional data collection methods, we take a user-centric approach by rewarding users for the data they willingly provide. This unique methodology ensures transparent data collection practices, encourages user participation, and establishes trust between data providers and consumers.

Wide Coverage and Varied Categories: Our clickstream data covers diverse categories, including search, shopping, and URL visits. Whether you are interested in understanding user preferences in e-commerce, analysing search behaviour across different industries, or tracking website visits, our data provides a rich and multi-dimensional view of user activities.

GDPR Compliance and Privacy: We prioritise data privacy and strictly adhere to GDPR guidelines. Our data collection methods are fully compliant, ensuring the protection of user identities and personal information. You can confidently leverage our clickstream data without compromising privacy or facing regulatory challenges.

Market Intelligence and Consumer Behaviuor: Gain deep insights into market intelligence and consumer behaviour using our clickstream data. Understand trends, preferences, and user behaviour patterns by analysing the comprehensive user-level, time-stamped raw or processed data feed. Uncover valuable information about user journeys, search funnels, and paths to purchase to enhance your marketing strategies and drive business growth.

High-Frequency Updates and Consistency: We provide high-frequency updates and consistent user participation, offering both historical data and ongoing daily delivery. This ensures you have access to up-to-date insights and a continuous data feed for comprehensive analysis. Our reliable and consistent data empowers you to make accurate and timely decisions.

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Data Quality and Credibility: We take data quality seriously. Our data sourcing practices are designed to ensure responsible and reliable data collection. We implement rigorous data cleaning, validation, and verification processes, guaranteeing the accuracy and reliability of our clickstream data. You can confidently rely on our data to drive your decision-making processes.

Web Analytics Market was valued at USD 6.16 Billion in 2024 and is projected to reach USD 13.6 Billion by 2032, growing at a CAGR of 18.58% from 2026 to 2032.

Web Analytics Market Drivers

Data-Driven Decision Making: Businesses increasingly rely on data-driven insights to optimize their online strategies. Web analytics provides valuable data on website traffic, user behavior, and conversion rates, enabling data-driven decision-making.

E-commerce Growth: The rapid growth of e-commerce has fueled the demand for web analytics tools to track online sales, customer behavior, and marketing campaign effectiveness.

Mobile Dominance: The increasing use of mobile devices for internet browsing has made mobile analytics a crucial aspect of web analytics. Businesses need to understand how users interact with their websites and apps on mobile devices.

analytics tools can be complex to implement and use, requiring technical expertise.

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.

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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

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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.

Global Network Traffic Analytics market size is expected to reach $6.22 billion by 2029 at 13.4%, segmented as by solution, network traffic analytics software, hardware appliances, cloud-based solutions

The global web analytics market, valued at $5529.7 million in 2025, is poised for substantial growth. While the provided CAGR is missing, considering the rapid advancements in digital technologies and the increasing reliance on data-driven decision-making across industries, a conservative estimate would place the Compound Annual Growth Rate (CAGR) between 15% and 20% for the forecast period 2025-2033. This growth is fueled by several key drivers: the rising adoption of cloud-based analytics solutions, the increasing demand for real-time data insights, and the growing need for personalized customer experiences. Furthermore, the expansion of e-commerce and the proliferation of mobile devices are significantly contributing to the market's expansion. Emerging trends such as artificial intelligence (AI) and machine learning (ML) integration within web analytics platforms are further enhancing analytical capabilities and driving market growth. While challenges like data privacy concerns and the complexity of integrating diverse data sources exist, the overall market outlook remains positive, suggesting a significant increase in market value by 2033. The competitive landscape is dynamic, with a mix of established players like Adobe, Google, and IBM alongside agile startups like Heap and Mouseflow. These companies offer a range of solutions catering to different business sizes and needs, from basic website traffic analysis to sophisticated predictive analytics. The market is witnessing a shift towards more user-friendly and visually appealing dashboards, making web analytics accessible to a broader range of users beyond dedicated data scientists. This democratization of data, coupled with ongoing technological advancements, promises to further accelerate market growth and consolidate the position of web analytics as a critical component of successful digital strategies across all sectors.

Traffic analytics, rankings, and competitive metrics for web.dev as of May 2025

Snapshot img

Web Analytics Market Size 2025-2029

The web analytics market size is forecast to increase by USD 3.63 billion, at a CAGR of 15.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the rising preference for online shopping and the increasing adoption of cloud-based solutions. The shift towards e-commerce is fueling the demand for advanced web analytics tools that enable businesses to gain insights into customer behavior and optimize their digital strategies. Furthermore, cloud deployment models offer flexibility, scalability, and cost savings, making them an attractive option for businesses of all sizes. However, the market also faces challenges associated with compliance to data privacy and regulations. With the increasing amount of data being generated and collected, ensuring data security and privacy is becoming a major concern for businesses.
Regulatory compliance, such as GDPR and CCPA, adds complexity to the implementation and management of web analytics solutions. Companies must navigate these challenges effectively to maintain customer trust and avoid potential legal issues. To capitalize on market opportunities and address these challenges, businesses should invest in robust web analytics solutions that prioritize data security and privacy while providing actionable insights to inform strategic decision-making and enhance customer experiences.

What will be the Size of the Web Analytics Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, with dynamic market activities unfolding across various sectors. Entities such as reporting dashboards, schema markup, conversion optimization, session duration, organic traffic, attribution modeling, conversion rate optimization, call to action, content calendar, SEO audits, website performance optimization, link building, page load speed, user behavior tracking, and more, play integral roles in this ever-changing landscape. Data visualization tools like Google Analytics and Adobe Analytics provide valuable insights into user engagement metrics, helping businesses optimize their content strategy, website design, and technical SEO. Goal tracking and keyword research enable marketers to measure the return on investment of their efforts and refine their content marketing and social media marketing strategies.

Mobile optimization, form optimization, and landing page optimization are crucial aspects of website performance optimization, ensuring a seamless user experience across devices and improving customer acquisition cost. Search console and page speed insights offer valuable insights into website traffic analysis and help businesses address technical issues that may impact user behavior. Continuous optimization efforts, such as multivariate testing, data segmentation, and data filtering, allow businesses to fine-tune their customer journey mapping and cohort analysis. Search engine optimization, both on-page and off-page, remains a critical component of digital marketing, with backlink analysis and page authority playing key roles in improving domain authority and organic traffic.

The ongoing integration of user behavior tracking, click-through rate, and bounce rate into marketing strategies enables businesses to gain a deeper understanding of their audience and optimize their customer experience accordingly. As market dynamics continue to evolve, the integration of these tools and techniques into comprehensive digital marketing strategies will remain essential for businesses looking to stay competitive in the digital landscape.

How is this Web Analytics Industry segmented?

The web analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  Cloud-based
  On-premises


Application

  Social media management
  Targeting and behavioral analysis
  Display advertising optimization
  Multichannel campaign analysis
  Online marketing


Component

  Solutions
  Services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

.

By Deployment Insights

The cloud-based segment is estimated to witness significant growth during the forecast period.

In today's digital landscape, web analytics plays a pivotal role in driving business growth and optimizing online performance. Cloud-based deployment of web analytics is a game-changer, enabling on-demand access to computing resources for data analysis. This model streamlines business intelligence processes by collecting,

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.

Network traffic datasets created by Single Flow Time Series Analysis

Datasets were created for the paper: Network Traffic Classification based on Single Flow Time Series Analysis -- Josef Koumar, Karel Hynek, Tomáš Čejka -- which was published at The 19th International Conference on Network and Service Management (CNSM) 2023. Please cite usage of our datasets as:

J. Koumar, K. Hynek and T. Čejka, "Network Traffic Classification Based on Single Flow Time Series Analysis," 2023 19th International Conference on Network and Service Management (CNSM), Niagara Falls, ON, Canada, 2023, pp. 1-7, doi: 10.23919/CNSM59352.2023.10327876.

This Zenodo repository contains 23 datasets created from 15 well-known published datasets which are cited in the table below. Each dataset contains 69 features created by Time Series Analysis of Single Flow Time Series. The detailed description of features from datasets is in the file: feature_description.pdf

In the following table is a description of each dataset file: