Altosight | AI Custom Web Scraping Data

✦ Altosight provides global web scraping data services with AI-powered technology that bypasses CAPTCHAs, blocking mechanisms, and handles dynamic content.

We extract data from marketplaces like Amazon, aggregators, e-commerce, and real estate websites, ensuring comprehensive and accurate results.

✦ Our solution offers free unlimited data points across any project, with no additional setup costs.

We deliver data through flexible methods such as API, CSV, JSON, and FTP, all at no extra charge.

― Key Use Cases ―

➤ Price Monitoring & Repricing Solutions

🔹 Automatic repricing, AI-driven repricing, and custom repricing rules 🔹 Receive price suggestions via API or CSV to stay competitive 🔹 Track competitors in real-time or at scheduled intervals

➤ E-commerce Optimization

🔹 Extract product prices, reviews, ratings, images, and trends 🔹 Identify trending products and enhance your e-commerce strategy 🔹 Build dropshipping tools or marketplace optimization platforms with our data

➤ Product Assortment Analysis

🔹 Extract the entire product catalog from competitor websites 🔹 Analyze product assortment to refine your own offerings and identify gaps 🔹 Understand competitor strategies and optimize your product lineup

➤ Marketplaces & Aggregators

🔹 Crawl entire product categories and track best-sellers 🔹 Monitor position changes across categories 🔹 Identify which eRetailers sell specific brands and which SKUs for better market analysis

➤ Business Website Data

🔹 Extract detailed company profiles, including financial statements, key personnel, industry reports, and market trends, enabling in-depth competitor and market analysis

🔹 Collect customer reviews and ratings from business websites to analyze brand sentiment and product performance, helping businesses refine their strategies

➤ Domain Name Data

🔹 Access comprehensive data, including domain registration details, ownership information, expiration dates, and contact information. Ideal for market research, brand monitoring, lead generation, and cybersecurity efforts

➤ Real Estate Data

🔹 Access property listings, prices, and availability 🔹 Analyze trends and opportunities for investment or sales strategies

― Data Collection & Quality ―

► Publicly Sourced Data: Altosight collects web scraping data from publicly available websites, online platforms, and industry-specific aggregators

► AI-Powered Scraping: Our technology handles dynamic content, JavaScript-heavy sites, and pagination, ensuring complete data extraction

► High Data Quality: We clean and structure unstructured data, ensuring it is reliable, accurate, and delivered in formats such as API, CSV, JSON, and more

► Industry Coverage: We serve industries including e-commerce, real estate, travel, finance, and more. Our solution supports use cases like market research, competitive analysis, and business intelligence

► Bulk Data Extraction: We support large-scale data extraction from multiple websites, allowing you to gather millions of data points across industries in a single project

► Scalable Infrastructure: Our platform is built to scale with your needs, allowing seamless extraction for projects of any size, from small pilot projects to ongoing, large-scale data extraction

― Why Choose Altosight? ―

✔ Unlimited Data Points: Altosight offers unlimited free attributes, meaning you can extract as many data points from a page as you need without extra charges

✔ Proprietary Anti-Blocking Technology: Altosight utilizes proprietary techniques to bypass blocking mechanisms, including CAPTCHAs, Cloudflare, and other obstacles. This ensures uninterrupted access to data, no matter how complex the target websites are

✔ Flexible Across Industries: Our crawlers easily adapt across industries, including e-commerce, real estate, finance, and more. We offer customized data solutions tailored to specific needs

✔ GDPR & CCPA Compliance: Your data is handled securely and ethically, ensuring compliance with GDPR, CCPA and other regulations

✔ No Setup or Infrastructure Costs: Start scraping without worrying about additional costs. We provide a hassle-free experience with fast project deployment

✔ Free Data Delivery Methods: Receive your data via API, CSV, JSON, or FTP at no extra charge. We ensure seamless integration with your systems

✔ Fast Support: Our team is always available via phone and email, resolving over 90% of support tickets within the same day

― Custom Projects & Real-Time Data ―

✦ Tailored Solutions: Every business has unique needs, which is why Altosight offers custom data projects. Contact us for a feasibility analysis, and we’ll design a solution that fits your goals

✦ Real-Time Data: Whether you need real-time data delivery or scheduled updates, we provide the flexibility to receive data when you need it. Track price changes, monitor product trends, or gather...

Here are a few use cases for this project:

1. Web Accessibility Improvement: The "Web Page Object Detection" model can be used to identify and label various elements on a web page, making it easier for people with visual impairments to navigate and interact with websites using screen readers and other assistive technologies.

2. Web Design Analysis: The model can be employed to analyze the structure and layout of popular websites, helping web designers understand best practices and trends in web design. This information can inform the creation of new, user-friendly websites or redesigns of existing pages.

3. Automatic Web Page Summary Generation: By identifying and extracting key elements, such as titles, headings, content blocks, and lists, the model can assist in generating concise summaries of web pages, which can aid users in their search for relevant information.

4. Web Page Conversion and Optimization: The model can be used to detect redundant or unnecessary elements on a web page and suggest their removal or modification, leading to cleaner designs and faster-loading pages. This can improve user experience and, potentially, search engine rankings.

5. Assisting Web Developers in Debugging and Testing: By detecting web page elements, the model can help identify inconsistencies or errors in a site's code or design, such as missing or misaligned elements, allowing developers to quickly diagnose and address these issues.

Analysis of ‘Website Analytics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ecee4df3-8149-4b74-8927-428ea920b758 on 13 February 2022.

--- Dataset description provided by original source is as follows ---

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.

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

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.

Web design service companies have experienced significant growth over the past few years, driven by the expanding use of the Internet. As online operations have become more widespread, businesses and consumers have increasingly recognized the importance of maintaining an online presence, leading to robust demand for web design services and boosting the industry’s profit. The rise in broadband connections and online business activities further spotlight this trend, making web design a vital component of modern commerce and communication. This solid foundation suggests the industry has been thriving despite facing some economic turbulence related to global events and shifting financial climates. Over the past few years, web design companies have navigated a dynamic landscape marked by both opportunities and challenges. Strong economic conditions have typically favored the industry, with rising disposable incomes and low unemployment rates encouraging both consumers and businesses to invest in professional web design. Despite this, the sector also faced hurdles such as high inflation, which made cost increases necessary and pushed some customers towards cheaper substitutes such as website templates and in-house production, causing a slump in revenue in 2022. Despite these obstacles, the industry has demonstrated resilience against rising interest rates and economic uncertainties by focusing on enhancing user experience and accessibility. Overall, revenue for web design service companies is anticipated to rise at a CAGR of 2.2% during the current period, reaching $43.5 billion in 2024. This includes a 2.2% jump in revenue in that year. Looking ahead, web design companies will continue to do well, as the strong performance of the US economy will likely support ongoing demand for web design services, bolstered by higher consumer spending and increased corporate profit. On top of this, government investment, especially at the state and local levels, will provide further revenue streams as public agencies seek to upgrade their web presence. Innovation remains key, with a particular emphasis on designing for mobile devices as more activities shift to on-the-go platforms. Companies that can effectively adapt to these trends and invest in new technologies will likely capture a significant market share, fostering an environment where entry remains feasible yet competitive. Overall, revenue for web design service providers is forecast to swell at a CAGR of 1.9% during the outlook period, reaching $47.7 billion in 2029.

Web Analytics Tools Market Outlook

The global web analytics tools market size was valued at approximately USD 4.5 billion in 2023 and is projected to reach USD 13.2 billion by 2032, growing at a CAGR of around 12.5% from 2024 to 2032. This growth is driven by the increasing utilization of data-driven decision-making processes across various industries. As organizations strive to enhance their digital presence and optimize their online strategies, the demand for advanced web analytics tools continues to surge.

One of the primary growth factors of the web analytics tools market is the rising adoption of digital marketing and online advertising. Companies are increasingly investing in digital channels to reach a broader audience and engage customers more effectively. Web analytics tools provide valuable insights into user behavior, campaign performance, and conversion rates, enabling businesses to refine their marketing strategies and achieve better ROI. As the digital landscape evolves, the need for sophisticated analytics tools to track and measure the effectiveness of online activities becomes more critical.

Another significant growth driver is the proliferation of e-commerce and the shift towards online shopping. With the exponential growth of online retail, businesses are seeking ways to optimize their websites, improve user experience, and increase sales. Web analytics tools play a crucial role in understanding customer preferences, identifying bottlenecks in the purchase process, and personalizing the shopping experience. As e-commerce continues to expand globally, the demand for robust web analytics solutions is expected to rise correspondingly.

The integration of artificial intelligence (AI) and machine learning (ML) technologies into web analytics tools is also propelling market growth. AI-powered analytics tools can analyze vast amounts of data in real-time, uncover hidden patterns, and generate actionable insights. By leveraging AI and ML capabilities, businesses can gain deeper insights into customer behavior, predict trends, and make data-driven decisions with greater accuracy. The incorporation of these advanced technologies is enhancing the efficiency and effectiveness of web analytics, driving higher adoption rates among enterprises.

The concept of Analytics of Things (AoT) is gaining traction as businesses increasingly seek to harness the power of connected devices and the data they generate. By integrating AoT into web analytics tools, organizations can gain deeper insights into device interactions, user behavior, and operational efficiencies. This integration allows businesses to make more informed decisions, optimize processes, and enhance customer experiences. As the Internet of Things (IoT) continues to expand, the role of AoT in web analytics is expected to grow, providing businesses with a competitive edge in the digital landscape.

In terms of regional outlook, North America holds the largest share of the web analytics tools market, driven by the presence of major technology companies and the high adoption of digital technologies in the region. The Asia Pacific region is expected to witness significant growth during the forecast period, fueled by the rapid digital transformation, increasing internet penetration, and the burgeoning e-commerce sector. Europe is also a key market, with growing awareness about the benefits of web analytics tools among businesses.

Component Analysis

The web analytics tools market is segmented based on components into software and services. The software segment holds a significant share of the market, driven by the increasing demand for advanced analytics solutions that provide real-time insights and comprehensive data analysis. Web analytics software includes various tools and platforms that help businesses track and measure website performance, user behavior, and marketing campaigns. The software segment is expected to continue its dominance during the forecast period, supported by continuous advancements in analytics technologies and the integration of AI and ML capabilities.

Services play a crucial role in the web analytics tools market by providing essential support, implementation, and consulting services to businesses. Professional services include consulting, training, and support services that help organizations effectively utilize web analytics tools and maximize their benefits. Managed services, on the other hand, offer ongoing monitoring,

A comprehensive list of websites that use Ada technology, ranked by popularity.

Analysis of ‘New York State Locality Hierarchy with Websites’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/113a63bc-1105-4ad6-aedf-9cc1dcdd9b32 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

The dataset contains a hierarchal listing of New York State counties, cities, towns, and villages, as well as official locality websites

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

A comprehensive list of websites that use Adobe Client Data Layer technology, ranked by popularity.

The global web page performance testing tools market is anticipated to expand at a 4.6% CAGR over the forecast period (2023-2030), rising from a valuation of USD 1,350 million in 2022 to reach USD 1,782.5 million by 2030. This growth is primarily driven by the increasing demand for optimizing user experience and performance on websites and web applications, as well as the need to ensure website reliability and responsiveness. Key market trends include the rise of cloud-based testing tools, the adoption of AI and machine learning for test automation, and the growing focus on performance testing in DevOps and agile development processes. The increasing popularity of cloud-based tools is attributed to their cost-effectiveness, flexibility, and scalability benefits. Furthermore, the integration of AI and machine learning capabilities into testing tools is enhancing their performance and efficiency by automating repetitive tasks, identifying bottlenecks, and providing actionable insights. The convergence of performance testing within DevOps and agile development workflows is also driving market growth as it enables real-time feedback and continuous improvement of software quality and performance.

Website Screenshot Software Market Outlook

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

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

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

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

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

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

Deployment Type Analysis

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

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

An observation study was conducted with undergraduate students. The study includes a video analysis of coding activities, an analysis of the source code written during coding, and a structured interview with participants.

This dataset contains transcripts of interviews with participants.

[1] was analyzed with [2]. The deposited files are the result.

[1] Steeg, Fabian et al.. (2016). URLs von Webseiten mit Typ Bibliothek aus Lobid.org. Zenodo. 10.5281/zenodo.50969

[2] Tim Libert et al.. (2016). webXray: First Release. Zenodo. 10.5281/zenodo.57272

The recipe website market is experiencing significant growth, driven by the increasing popularity of home cooking, the convenience of online recipe access, and the rise of social media platforms that foster recipe sharing. In 2025, the market was valued at million and is projected to reach a staggering million by 2033, exhibiting a CAGR of XX% during the forecast period. Key trends driving this growth include the integration of artificial intelligence and machine learning into recipe websites, providing personalized recommendations and improved search functionality. Additionally, the emergence of meal delivery services and the increasing focus on healthy eating are fueling the demand for reliable and accessible recipe resources. Major players in the market include AllRecipes, FoodNetwork, Genius Kitchen, and Yummly, who continue to enhance their offerings and engage with users through social media and community forums.

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,

The global website speed test market size was valued at USD 363.9 million in 2022 and is projected to expand at a compound annual growth rate (CAGR) of 15.3% from 2023 to 2032. The growth of the market is attributed to the increasing adoption of online platforms and the need for businesses to optimize their websites for better user experience. Key drivers of the website speed test market include the growing demand for mobile web browsing, the proliferation of content-heavy websites, and the increasing use of personalized content. Additionally, the increasing adoption of cloud-based solutions and the growing awareness of the importance of website performance are expected to drive the growth of the market over the forecast period.

Domain: The URL itself. Ranking: Page Ranking isIp: Is there an IP address in the weblink valid: This data is fetched from google's whois API that tells us more about the current status of the URL's registration. activeDuration: Also from whois API. Gives the duration of the time since the registration up until now. urlLen: It is simply the length of the URL is@: If the link has a '@' character then it's value = 1 isredirect: If the link has double dashes, there is a chance that it is a redirect. 1-> multiple dashes present together. haveDash: If there are any dashes in the domain name. domainLen: The length of just the domain name. noOfSubdomain: The number of subdomains preset in the URL. Labels: 0 -> Legitimate website , 1 -> Phishing Link/ Spam Link

The custom website design market is projected to reach a value of 81380 million in 2025, exhibiting a CAGR of 8.4% during the forecast period (2025-2033). The increasing demand for personalized and user-centric websites, coupled with the proliferation of e-commerce, has been driving market growth. Furthermore, the rising adoption of mobile devices and the growing number of internet users have spurred the demand for responsive and mobile-friendly website designs. The key drivers of the custom website design market include the increasing number of businesses establishing an online presence, the demand for improved user experience and engagement, and the growing adoption of cloud-based design tools. The market is segmented based on application (enterprise and individual) and type (independent team and crowdsourcing model). North America and Europe are major regional markets for custom website design, with significant contributions from the United States, Canada, Germany, and the United Kingdom. The market is characterized by the presence of both established players and emerging startups, with key vendors including Web.com, Digital.com, DreamHost, Thrive Internet Marketing Agency, and crowdspring.

Analysis of the websites and ICT uses of Walloon municipalities

Full edition for scientific use. The dataset “AUTNES Content Analysis of Party Websites 2013” covers all party websites of parties gaining at least two percent of the votes in the 2013 national election. The party websites were saved each day during the six weeks prior to the general election in 2013. The coding units are graphical or textual elements on the website. The coding procedure applies the AUTNES relational approach of recording subjects, predicates, and objects to party websites. The subject is the party that operates the website. There are two types of objects: issues and object actors. Coders record issues by selecting from the AUTNES issue coding scheme the dominant policy issue and the dominant campaign issue in the coding unit. The issue predicate numerically records whether the subject’s position towards the policy issue is one of support, rejection, or conveys a neutral/ambivalent stance. Up to ten object actors are recorded from each coding unit, each with their name (if an individual is present) and organisational affiliation, as well as the evaluation by the subject actor (positive, negative or neutral) and appearance in the coding unit (text only, text and image, image only). In addition to the basic subject–predicate–object structure we code several additional variables: character traits and party records for all actors, and justifications for issue statements. Also, the dataset contains variables describing the website, the coding units and images visible on the website. List of variables: ID, coder-ID; variables referring to the homepage: URL; type of homepage (party homepage); date and time of saving; variables referring to the coding unit: unit-ID; number of days a unit was online; new unit (unit is online for the first time); visible on a screen of standard size when opening the homepage; category (start picture, head, menu, news, policies, campaign, schedule, twitterwall, facebook, blogs); continuous text; picture; video; variables referring to the author (the party that operated the homepage): author is mentioned; author’s characteristics (competence, character, leadership, appearance, not classifiable); author’s record (no record, record referring to policy issue, record not referring to policy issue); variables referring to issues: coded campaign issue; predicate (author’s position towards the coded policy issue: rejection/criticism, neutral, support); policy issue; reference to policy at the EU level; justification of policy issue (no justification, economy, welfare state: expansive / protective, environment, security, education, governance, ethnic-national, religious, universalistic, not classifiable); variables referring to up to ten object actors: object actor was coded; names of the object actors if individuals; object actor’s organisation; appearance (object actor is mentioned in written form, as a picture or both); predicate (relation between the author of the homepage and the object actor: rejection/criticism, neutral, support, picture); object actor’s outfit (if the unit contains a picture); object actor makes a reference to the coded campaign issue and to the coded policy issue; object actor’s attributes (competence, character, leadership, appearance, not classifiable); object actor’s record referring to policy issue or not; number of additional object actors that were not coded; variables referring to pictures: pictures of individuals that were not coded as object actors; groups of individuals (or category) in pictures (i.e. voter/people, political activist, woman, man, etc.); number of people (individuals of the respective category or group on the picture); the individuals on the picture support a party (reference to party x).