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

Results from Checkbot API to measure and collect 341 websites compatibility on multiple SEO variables (34 variables). Checkbot API indexes the website's code to find features capable of impacting SEO performance. Each website has been tested with the maximum number of links allowed to be crawled equally to 10.000 per test. In this way, we retrieved data about the overall websites performance including their sub-pages, and not only the main domain names. A scale from 0 (lowest rate) to 100 (highest rate) was adopted for each examined variable. This constitutes a useful managerial indicator of dealing with the quantification of websites performance while avoiding complex measurement systems that are difficult to be adopted by administrators. Websites tested were also categorized by the CMS type used. More information about the variables and the meaning of the results can be found at https://www.checkbot.io/

Context

Data-driven models help mobile app designers understand best practices and trends, and can be used to make predictions about design performance and support the creation of adaptive UIs. This paper presents Rico, the largest repository of mobile app designs to date, created to support five classes of data-driven applications: design search, UI layout generation, UI code generation, user interaction modeling, and user perception prediction. To create Rico, we built a system that combines crowdsourcing and automation to scalably mine design and interaction data from Android apps at runtime. The Rico dataset contains design data from more than 9.3k Android apps spanning 27 categories. It exposes visual, textual, structural, and interactive design properties of more than 66k unique UI screens. To demonstrate the kinds of applications that Rico enables, we present results from training an autoencoder for UI layout similarity, which supports query-by-example search over UIs.

Content

Rico was built by mining Android apps at runtime via human-powered and programmatic exploration. Like its predecessor ERICA, Rico’s app mining infrastructure requires no access to — or modification of — an app’s source code. Apps are downloaded from the Google Play Store and served to crowd workers through a web interface. When crowd workers use an app, the system records a user interaction trace that captures the UIs visited and the interactions performed on them. Then, an automated agent replays the trace to warm up a new copy of the app and continues the exploration programmatically, leveraging a content-agnostic similarity heuristic to efficiently discover new UI states. By combining crowdsourcing and automation, Rico can achieve higher coverage over an app’s UI states than either crawling strategy alone. In total, 13 workers recruited on UpWork spent 2,450 hours using apps on the platform over five months, producing 10,811 user interaction traces. After collecting a user trace for an app, we ran the automated crawler on the app for one hour.

Acknowledgements

UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN https://interactionmining.org/rico

Inspiration

The Rico dataset is large enough to support deep learning applications. We trained an autoencoder to learn an embedding for UI layouts, and used it to annotate each UI with a 64-dimensional vector representation encoding visual layout. This vector representation can be used to compute structurally — and often semantically — similar UIs, supporting example-based search over the dataset. To create training inputs for the autoencoder that embed layout information, we constructed a new image for each UI capturing the bounding box regions of all leaf elements in its view hierarchy, differentiating between text and non-text elements. Rico’s view hierarchies obviate the need for noisy image processing or OCR techniques to create these inputs.

Discover the booming web analytics software market! This in-depth analysis reveals a $15 billion market in 2025, projected to reach $45 billion by 2033, driven by cloud adoption and data-driven decision-making. Learn about key players, market trends, and regional growth.

Unlock the power of data-driven marketing! Explore the booming Marketing Data Analysis Software market, projected to reach [estimated 2033 value] by 2033. Discover key trends, leading companies, and regional insights to optimize your marketing strategies and achieve higher ROI. Learn more about software types, applications, and future growth potential.

Web Analytics Market Outlook

According to our latest research, the global web analytics market size was valued at USD 8.4 billion in 2024, reflecting robust growth driven by the increasing adoption of digital platforms across industries. The market is projected to expand at a compound annual growth rate (CAGR) of 17.2% from 2025 to 2033, reaching an estimated USD 36.8 billion by 2033. This significant upsurge is primarily attributed to the escalating demand for actionable insights, data-driven decision-making, and the proliferation of online consumer activity. As per the latest research, enterprises worldwide are leveraging advanced web analytics tools to enhance customer engagement, improve marketing strategies, and drive business outcomes.

One of the principal growth factors fueling the web analytics market is the exponential increase in digitalization and internet penetration. Organizations across various sectors are rapidly transitioning their operations online, resulting in a surge of data generation through multiple digital touchpoints. This digital transformation has heightened the need for sophisticated web analytics solutions that can process vast volumes of data, extract meaningful patterns, and provide actionable insights. Moreover, the rise in e-commerce activities, coupled with the growing popularity of social media platforms, has created a fertile environment for the adoption of web analytics, enabling businesses to track consumer behavior, measure campaign effectiveness, and optimize user experiences.

Another critical driver for the web analytics market is the integration of artificial intelligence (AI) and machine learning (ML) technologies. These advanced technologies are revolutionizing the way organizations analyze web data by enabling predictive analytics, real-time reporting, and personalized recommendations. AI-powered web analytics tools can automatically identify trends, anomalies, and customer preferences, empowering businesses to make data-driven decisions faster and more accurately. Furthermore, the increasing focus on omnichannel marketing strategies and the need to unify customer data across different platforms have further accelerated the demand for comprehensive web analytics solutions.

The regulatory landscape and growing emphasis on data privacy and compliance are also shaping the web analytics market. With the implementation of stringent data protection regulations such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States, organizations are compelled to adopt web analytics tools that ensure data security and privacy. This has led to the development of privacy-centric analytics platforms that offer enhanced data governance features, enabling businesses to comply with global regulatory requirements while still deriving valuable insights from web data. The ability to balance data-driven innovation with privacy considerations is becoming a key differentiator for vendors in this dynamic market.

In the realm of digital transformation, Construction Analytics is emerging as a pivotal tool for the construction industry. As companies strive to enhance operational efficiency and project management, the integration of analytics solutions is becoming increasingly vital. Construction Analytics enables firms to harness data from various sources, such as project timelines, resource allocation, and financial metrics, to gain actionable insights. This data-driven approach facilitates better decision-making, risk management, and cost optimization, ultimately leading to improved project outcomes. The growing adoption of IoT devices and smart construction technologies is further fueling the demand for Construction Analytics, as it allows for real-time monitoring and predictive maintenance. By leveraging these advanced analytics capabilities, construction companies can enhance productivity, reduce delays, and ensure compliance with safety regulations, thereby gaining a competitive edge in the market.

From a regional perspective, North America continues to dominate the web analytics market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The regionÂ’s leadership is attributed to the presence of major technology providers, a mature digital ecosystem, and high levels of investment in analytics infrastructu

Explore the booming Web Analytics market, projected to reach USD 3144.1 million by 2025 with a 10.4% CAGR. Discover key drivers, applications like social media management, and regional growth trends. Optimize your digital strategy with data-driven insights.

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Web Development Market Size 2025-2029

The web development market size is forecast to increase by USD 40.98 billion at a CAGR of 10.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing digital transformation across industries and the integration of artificial intelligence (AI) into web applications. This trend is fueled by the need for businesses to enhance user experience, streamline operations, and gain a competitive edge in the market. Furthermore, the rapid evolution of technologies such as Progressive Web Apps (PWAs), serverless architecture, and the Internet of Things (IoT) is creating new opportunities for innovation and expansion. However, this market is not without challenges. The ever-changing technological landscape requires web developers to continuously update their skills and knowledge. Additionally, ensuring web applications are secure and compliant with data protection regulations is becoming increasingly complex.
Companies seeking to capitalize on market opportunities and navigate challenges effectively should focus on building a team of skilled developers, investing in continuous learning and development, and prioritizing security and compliance in their web development projects. By staying abreast of the latest trends and technologies, and adapting quickly to market shifts, organizations can successfully navigate the dynamic the market and drive business growth.

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

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The market continues to evolve at an unprecedented pace, driven by advancements in technology and shifting consumer preferences. Key trends include the adoption of Agile methodologies, DevOps tools, and version control systems for streamlined project management. JavaScript frameworks, such as React and Angular, dominate front-end development, while Magento, Shopify, and WordPress lead in content management and e-commerce. Back-end development sees a rise in Python, PHP, and Ruby on Rails frameworks, enabling faster development and more efficient scalability. Interaction design, user-centered design, and mobile-first design prioritize user experience, while security audits, penetration testing, and disaster recovery solutions ensure website safety.
Marketing automation, email marketing platforms, and CRM systems enhance digital marketing efforts, while social media analytics and Google Analytics provide valuable insights for data-driven decision-making. Progressive enhancement, headless CMS, and cloud migration further expand the market's potential. Overall, the market remains a dynamic, innovative space, with continuous growth fueled by evolving business needs and technological advancements.

How is this Web Development Industry segmented?

The web development 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.

End-user

  Retail and e-commerce
  BFSI
  IT and telecom
  Healthcare
  Others


Business Segment

  SMEs
  Large enterprise


Service Type

  Front-End Development
  Back-End Development
  Full-Stack Development
  E-Commerce Development


Deployment Type

  Cloud-Based
  On-Premises


Technology Specificity

  JavaScript
  Python
  PHP
  Ruby


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Spain
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By End-user Insights

The retail and e-commerce segment is estimated to witness significant growth during the forecast period. The market is experiencing significant growth due to the digital transformation sweeping various industries. E-commerce and retail sectors lead the market, driven by the increasing preference for online shopping and improved Internet penetration. To cater to this trend, businesses demand user-engaging web applications with smooth navigation, secure payment gateways, and seamless product search and purchase features. Mobile shopping's rise necessitates mobile app development and mobile-optimized websites. Agile development, microservices architecture, and UI/UX design are essential elements in creating engaging and efficient web solutions. Furthermore, AI, machine learning, and data analytics enable data-driven decision making, customer loyalty, and business intelligence.

Web hosting, cloud computing, API integration, and growth hacking are other critical components. Ensuring web accessibility, data security, and e-commerce development is also crucial for businesses in the digital age. Online advertising, email marketing, content strategy, brand building, and data visualization are essential aspects of digital marketing. Serverless computing, u

Data-driven modeling has emerged as a new paradigm for biocatalyst design and discovery. Biocatalytic databases that integrate enzyme structure and function data are in urgent need. Here we describe IntEnzyDB as an integrated structure–kinetics database for facile statistical modeling and machine learning. IntEnzyDB employs a relational database architecture with a flattened data structure, which allows rapid data operation. This architecture also makes it easy for IntEnzyDB to incorporate more types of enzyme function data. IntEnzyDB contains enzyme kinetics and structure data from six enzyme commission classes. Using 1050 enzyme structure–kinetics pairs, we investigated the efficiency-perturbing propensities of mutations that are close or distal to the active site. The statistical results show that efficiency-enhancing mutations are globally encoded and that deleterious mutations are much more likely to occur in close mutations than in distal mutations. Finally, we describe a web interface that allows public users to access enzymology data stored in IntEnzyDB. IntEnzyDB will provide a computational facility for data-driven modeling in biocatalysis and molecular evolution.

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.

This dataset is about books. It has 1 row and is filtered where the book is MySQL and JSP Web applications : data-driven programming using Tomcat and MySQL. It features 7 columns including author, publication date, language, and book publisher.

Web scraped text of data-driven start-ups founded between 2010 and 2023. The data was used for data-driven business models analysis, identifying emergent trends and business models transformation over time. The dataset contains the text split into sentences along a reference text (description) and respective embeddings. The foundation model used for the embeddings is: paraphrase-multilingual-MiniLM-L12-v2.

The data collection process not only respected websites' privacy but also adhered to best practices. The scraper tool was configured to read the robots.txt file at the root of each website and proceed only with actions explicitly allowed by the respective site. Additionally, the collection was limited to 50 pages per firm to avoid excessive harvesting.

Discover the booming website visitor tracking software market! Our analysis reveals a $5 billion market in 2025, projected to reach $15 billion by 2033, driven by digital marketing, data-driven decisions, and AI-powered analytics. Learn about key players, market trends, and regional insights.

The Top Websites in the World

How They Change Over Time

About this dataset

This dataset consists of the top 50 most visited websites in the world, as well as the category and principal country/territory for each site. The data provides insights into which sites are most popular globally, and what type of content is most popular in different parts of the world

How to use the dataset

This dataset can be used to track the most popular websites in the world over time. It can also be used to compare website popularity between different countries and categories

Research Ideas

• To track the most popular websites in the world over time
• To see how website popularity changes by region
• To find out which website categories are most popular

Acknowledgements

Dataset by Alexa Internet, Inc. (2019), released on Kaggle under the Open Data Commons Public Domain Dedication and License (ODC-PDDL)

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: df_1.csv | Column name | Description | |:--------------------------------|:---------------------------------------------------------------------| | Site | The name of the website. (String) | | Domain Name | The domain name of the website. (String) | | Category | The category of the website. (String) | | Principal country/territory | The principal country/territory where the website is based. (String) |

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...

The global Enterprise Website Analytics Software market is experiencing robust growth, driven by the increasing need for businesses to understand their online presence and optimize their digital strategies. The market's expansion is fueled by several key factors, including the rising adoption of cloud-based solutions offering scalability and cost-effectiveness, the proliferation of mobile devices and diverse digital channels requiring sophisticated analytics, and a growing focus on data-driven decision-making across all departments. Large enterprises are leading the adoption, leveraging these tools for detailed customer journey mapping, performance optimization, and enhanced ROI on marketing investments. However, the market faces challenges such as the complexity of integrating various analytics platforms and the need for specialized expertise to effectively interpret and utilize the vast amounts of data generated. The segment showing the fastest growth is likely cloud-based solutions due to their flexibility and accessibility. We estimate the 2025 market size to be around $15 billion, based on observable growth trends in related software markets and considering the increasing adoption of analytics solutions across various industries. A Compound Annual Growth Rate (CAGR) of 12% is projected for the forecast period (2025-2033), indicating substantial market expansion over the coming years. The competitive landscape is highly dynamic, with both established tech giants (Google, IBM) and specialized analytics providers (Adobe, SEMrush, Mixpanel) vying for market share. The ongoing trend towards mergers and acquisitions further shapes the industry. Companies are continually innovating to offer more comprehensive solutions, incorporating features like artificial intelligence (AI) for predictive analytics, real-time data visualization, and seamless integration with CRM systems. Geographic growth will vary, with North America and Europe expected to maintain significant market share due to high technological adoption rates. However, Asia-Pacific is projected to witness substantial growth driven by increasing digitalization and economic expansion. The market's future trajectory hinges on continuous innovation within analytics capabilities, addressing the challenges of data privacy and security, and fostering greater user-friendliness within these sophisticated platforms.

Consumer behavior has changed due to digitization. Online shoppers now refer to user reviews containing comprehensive data produced in real-time, which can be used to determine users’ needs. This paper combines Kansei engineering and natural language processing techniques to extract information on users’ needs from online reviews and provide guidance for subsequent product improvements and development. A crawler tool was used to collect a large number of online reviews for a target product. Frequency analysis was then applied to the text to filter out the product components worth analyzing. The results were categorized and aggregated by experts before sentiment analysis was performed on statements containing the selected adjectives. Finally, the user needs identified could be inputted to Kansei engineering for further product design. This paper verifies the merit of the above method when applied to the mountain bike product category on Amazon. The method proved to be a quick and efficient way to attain accurate product evaluations from end-users and thus represents a feasible approach to intelligently determining user preferences.

The goal of this study was to identify and evaluate case management and supervision strategies most effective in achieving successful parole outcomes. As part of an evaluation of 3 new supervision practice protocols on a cohort of parolees, a total of 1,964 parolees who began supervision in Georgia between March 1, 2007, and December 31, 2007, were assigned to experimental and control groups. Parolees in the experimental group were subjected to the new practice protocols: positive drug test resulting in a referral to treatment, job loss followed by referral to an employment program and increased contact, and chronic technical violations responded to with an administrative hearing and enrollment in a cognitive skills program. In the control sites, the parole officer's response to a parolee's violation or success was still defined by the Board's Behavior Response and Adjustment Guide (BRAG). Each parolee was tracked for a 12-month follow-up period. The research team collected data on the parolees using two Georgia Department of Corrections and Board of Pardons and Paroles agency databases: the Offender Tracking Information System (OTIS) and the Parole Field Log of Interaction Data (FLOID) database. Outcomes during a 12-month follow-up period were defined as employment, general violations of the conditions of supervision, positive drug tests, arrests for technical violations, misdemeanor and felony arrests, and revocation of parole. The dataset includes a total of 218 variables including supervision protocol variables, demographic and other parolee characteristics variables, offense and parole supervision variables, drug test results, employment activity, as well as arrests, violations, sanctions, programs, and referrals information.

The Mobile Apps and Web Analytics Market size was valued at USD 9.1 Billion in the year 2024 and it is expected to reach USD 38.35 Billion in 2032, growing at a CAGR of 16.3% over the forecast period of 2026 to 2032.Global Mobile Apps And Web Analytics Market DriversIncreasing Adoption of Mobile Devices and Apps: The surge in smartphone use boosts the mobile apps and web analytics market, as businesses analyze mobile app performance to enhance user satisfaction and maintain competitiveness.Growing Importance of Data-Driven Decision Making: Companies across sectors are embracing data-driven strategies to stay ahead, using mobile apps and web analytics for insights on user behavior and preferences, influencing product and marketing decisions.Need for Enhanced User Experience and Engagement: Mobile apps and web analytics are critical for improving user experiences by identifying issues and optimizing interactions, leading to increasing user satisfaction and loyalty.Shift towards Digital Transformation and Omnichannel Strategies: The move towards digital transformation and omnichannel approaches fuels the demand for mobile apps and web analytics, helping businesses measure effectiveness and optimize customer engagement across multiple channels.

Learn how to maximize Twitter content marketing ROI through data-driven recirculation. Analysis shows posts gain 75% of original retweets with each reshare.