29 datasets found
  1. e

    similarweb.com Traffic Analytics Data

    • analytics.explodingtopics.com
    Updated Aug 1, 2025
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    (2025). similarweb.com Traffic Analytics Data [Dataset]. https://analytics.explodingtopics.com/website/similarweb.com
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    Dataset updated
    Aug 1, 2025
    Variables measured
    Global Rank, Monthly Visits, Authority Score, US Country Rank, Online Services Category Rank
    Description

    Traffic analytics, rankings, and competitive metrics for similarweb.com as of August 2025

  2. Data from: Analysis of the Quantitative Impact of Social Networks General...

    • figshare.com
    • produccioncientifica.ucm.es
    doc
    Updated Oct 14, 2022
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    David Parra; Santiago Martínez Arias; Sergio Mena Muñoz (2022). Analysis of the Quantitative Impact of Social Networks General Data.doc [Dataset]. http://doi.org/10.6084/m9.figshare.21329421.v1
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    docAvailable download formats
    Dataset updated
    Oct 14, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    David Parra; Santiago Martínez Arias; Sergio Mena Muñoz
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    General data recollected for the studio " Analysis of the Quantitative Impact of Social Networks on Web Traffic of Cybermedia in the 27 Countries of the European Union". Four research questions are posed: what percentage of the total web traffic generated by cybermedia in the European Union comes from social networks? Is said percentage higher or lower than that provided through direct traffic and through the use of search engines via SEO positioning? Which social networks have a greater impact? And is there any degree of relationship between the specific weight of social networks in the web traffic of a cybermedia and circumstances such as the average duration of the user's visit, the number of page views or the bounce rate understood in its formal aspect of not performing any kind of interaction on the visited page beyond reading its content? To answer these questions, we have first proceeded to a selection of the cybermedia with the highest web traffic of the 27 countries that are currently part of the European Union after the United Kingdom left on December 31, 2020. In each nation we have selected five media using a combination of the global web traffic metrics provided by the tools Alexa (https://www.alexa.com/), which ceased to be operational on May 1, 2022, and SimilarWeb (https:// www.similarweb.com/). We have not used local metrics by country since the results obtained with these first two tools were sufficiently significant and our objective is not to establish a ranking of cybermedia by nation but to examine the relevance of social networks in their web traffic. In all cases, cybermedia whose property corresponds to a journalistic company have been selected, ruling out those belonging to telecommunications portals or service providers; in some cases they correspond to classic information companies (both newspapers and televisions) while in others they refer to digital natives, without this circumstance affecting the nature of the research proposed.
    Below we have proceeded to examine the web traffic data of said cybermedia. The period corresponding to the months of October, November and December 2021 and January, February and March 2022 has been selected. We believe that this six-month stretch allows possible one-time variations to be overcome for a month, reinforcing the precision of the data obtained. To secure this data, we have used the SimilarWeb tool, currently the most precise tool that exists when examining the web traffic of a portal, although it is limited to that coming from desktops and laptops, without taking into account those that come from mobile devices, currently impossible to determine with existing measurement tools on the market. It includes:

    Web traffic general data: average visit duration, pages per visit and bounce rate Web traffic origin by country Percentage of traffic generated from social media over total web traffic Distribution of web traffic generated from social networks Comparison of web traffic generated from social netwoks with direct and search procedures

  3. W

    Website Visitor Tracking Software Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Mar 5, 2025
    + more versions
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    Market Research Forecast (2025). Website Visitor Tracking Software Report [Dataset]. https://www.marketresearchforecast.com/reports/website-visitor-tracking-software-27553
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    doc, pdf, pptAvailable download formats
    Dataset updated
    Mar 5, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global 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. The market, estimated at $5 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $15 billion by 2033. This expansion is fueled by several key factors, including the rising adoption of digital marketing strategies, the growing importance of data-driven decision-making, and the increasing sophistication of website visitor tracking tools. Cloud-based solutions dominate the market due to their scalability, accessibility, and cost-effectiveness, particularly appealing to Small and Medium-sized Enterprises (SMEs). However, large enterprises continue to invest significantly in on-premise solutions for enhanced data security and control. The market is highly competitive, with numerous established players and emerging startups offering a range of features and functionalities. Technological advancements, such as AI-powered analytics and enhanced integration with other marketing tools, are shaping the future of the market. The market's geographical distribution reflects the global digital landscape. North America, with its mature digital economy and high adoption rates, holds a significant market share. However, regions like Asia-Pacific are showing rapid growth, driven by increasing internet penetration and digitalization across various industries. Despite the overall positive outlook, challenges such as data privacy regulations and the increasing complexity of website tracking technology are influencing market dynamics. The ongoing competition among vendors necessitates continuous innovation and the development of more user-friendly and insightful tools. The future growth of the website visitor tracking software market is promising, fueled by the continuing importance of data-driven decision-making within marketing and business strategies. A key factor will be the ongoing adaptation to evolving privacy regulations and user expectations.

  4. f

    Summary of results comparing Google Analytics and SimilarWeb for total...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 13, 2023
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    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen (2023). Summary of results comparing Google Analytics and SimilarWeb for total visits, unique visitors, bounce rate, and average session duration. [Dataset]. http://doi.org/10.1371/journal.pone.0268212.t006
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    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Difference uses Google Analytics as the Baseline. Results based on Paired t-Test for Hypotheses Supported.

  5. Host country of organization for 86 websites in study.

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 15, 2023
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    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen (2023). Host country of organization for 86 websites in study. [Dataset]. http://doi.org/10.1371/journal.pone.0268212.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Host country of organization for 86 websites in study.

  6. r

    eBay Daily Traffic Statistics 2025

    • redstagfulfillment.com
    html
    Updated May 19, 2025
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    Red Stag Fulfillment (2025). eBay Daily Traffic Statistics 2025 [Dataset]. https://redstagfulfillment.com/how-many-daily-visits-does-ebay-receive/
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    htmlAvailable download formats
    Dataset updated
    May 19, 2025
    Dataset authored and provided by
    Red Stag Fulfillment
    Time period covered
    Jan 2025 - Jul 2025
    Area covered
    Brazil, Germany, Mexico, Canada, Japan, Global with focus on United States
    Variables measured
    Bounce rate, Daily visits, Monthly visits, Pages per visit, Session duration, Device usage patterns, Geographic traffic distribution
    Description

    Comprehensive dataset analyzing eBay's daily visitor traffic patterns, geographic distribution, device usage, and competitive positioning based on third-party analytics from Similarweb and Semrush.

  7. C

    Customer Behavior Analysis Tool Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Jul 5, 2025
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    Data Insights Market (2025). Customer Behavior Analysis Tool Report [Dataset]. https://www.datainsightsmarket.com/reports/customer-behavior-analysis-tool-1988618
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    ppt, pdf, docAvailable download formats
    Dataset updated
    Jul 5, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Customer Behavior Analysis Tool market is experiencing robust growth, driven by the increasing need for businesses to understand and optimize customer journeys for enhanced engagement and conversion rates. The market's expansion is fueled by the proliferation of digital channels, the rise of big data analytics, and the increasing sophistication of available tools. Businesses across various sectors, including e-commerce, retail, and finance, are leveraging these tools to gain actionable insights into user behavior, website navigation, and customer preferences. This allows for data-driven decision-making leading to improved website design, targeted marketing campaigns, and personalized customer experiences. The competitive landscape is highly fragmented, with a mix of established players like Google Analytics and Salesforce and emerging niche players offering specialized solutions. While the market is experiencing significant growth, challenges remain, including data privacy concerns, the complexity of implementing and integrating these tools, and the need for skilled professionals to interpret and utilize the data effectively. The market is expected to see continued expansion, driven by technological advancements in AI and machine learning, enabling more sophisticated analysis and predictive modeling. Over the forecast period (2025-2033), the market is projected to maintain a steady growth trajectory, with several factors contributing to its expansion. The increasing adoption of cloud-based solutions, the rise of mobile-first strategies, and the growing importance of customer experience management are all pushing demand for more advanced analytics capabilities. Furthermore, the integration of customer behavior analysis tools with CRM systems and marketing automation platforms is enhancing their effectiveness and creating new opportunities for growth. While pricing and competitive intensity are likely to remain key factors influencing market dynamics, the overall outlook for the Customer Behavior Analysis Tool market remains positive, driven by the fundamental need for businesses to understand and respond to the evolving needs and preferences of their customers. To maintain competitiveness, vendors are likely to focus on innovation, particularly in the areas of AI-powered insights and seamless integration with other enterprise software solutions.

  8. f

    Website type for the 86 websites in study.

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 13, 2023
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    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen (2023). Website type for the 86 websites in study. [Dataset]. http://doi.org/10.1371/journal.pone.0268212.t005
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    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Website type for the 86 websites in study.

  9. Most visited price comparison websites in Hungary 2021, by traffic share

    • statista.com
    Updated Apr 13, 2023
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    Statista (2023). Most visited price comparison websites in Hungary 2021, by traffic share [Dataset]. https://www.statista.com/statistics/1312875/hungary-traffic-share-of-the-most-popular-price-comparison-websites/
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    Dataset updated
    Apr 13, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    Hungary
    Description

    Árukereső was the most popular price comparison portal in Hungary in 2021, based on the traffic share measured by SimilarWeb. Árgép was the second most visited price comparison site over the same time period.

  10. Total global visitor traffic to Google.com 2024

    • statista.com
    Updated Aug 20, 2025
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    Statista (2025). Total global visitor traffic to Google.com 2024 [Dataset]. https://www.statista.com/statistics/268252/web-visitor-traffic-to-googlecom/
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    Dataset updated
    Aug 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023 - Mar 2024
    Area covered
    Worldwide
    Description

    In March 2024, search platform Google.com generated approximately 85.5 billion visits, down from 87 billion platform visits in October 2023. Google is a global search platform and one of the biggest online companies worldwide.

  11. W

    Website Visitor Tracking Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Aug 7, 2025
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    Data Insights Market (2025). Website Visitor Tracking Software Report [Dataset]. https://www.datainsightsmarket.com/reports/website-visitor-tracking-software-1413360
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Aug 7, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    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. The market, currently estimated at $5 billion in 2025, is projected to expand significantly over the next decade, with a Compound Annual Growth Rate (CAGR) of approximately 15% from 2025 to 2033. This growth is fueled by several key factors, including the rising adoption of e-commerce, the proliferation of sophisticated website analytics tools offering deeper insights into user engagement, and a growing emphasis on data-driven decision-making across various industries. Businesses are increasingly relying on these tools not only for basic website traffic analysis but also for advanced features like heatmap analysis, session recording, form analytics, and A/B testing, which enable personalized user experiences and targeted marketing campaigns. The market's competitive landscape is diverse, with a mix of established players like Google Analytics and Adobe Analytics, alongside emerging specialized solutions focusing on specific aspects of visitor tracking, like lead generation or user behavior analysis. This fragmentation offers businesses a wide range of options tailored to their specific needs and budgets. The continued advancement of artificial intelligence (AI) and machine learning (ML) is expected to significantly impact the future of website visitor tracking software. AI-powered tools are increasingly capable of providing predictive analytics, identifying high-value visitors, automating tasks, and personalizing the user journey with greater accuracy. While data privacy concerns and the increasing complexity of these tools pose challenges, the overall market outlook remains positive. The focus is shifting towards tools that offer more comprehensive, insightful, and privacy-compliant solutions, leading to further innovation and consolidation within the market. Furthermore, the integration of website visitor tracking with other marketing automation platforms is becoming increasingly crucial, enabling a more holistic view of the customer journey and streamlining marketing efforts. This trend is expected to drive further market growth and shape the competitive landscape in the coming years.

  12. f

    Comparison of user, site, and network-centric approaches to web analytics...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen (2023). Comparison of user, site, and network-centric approaches to web analytics data collection showing advantages, disadvantages, and examples of each approach at the time of the study. [Dataset]. http://doi.org/10.1371/journal.pone.0268212.t001
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Comparison of user, site, and network-centric approaches to web analytics data collection showing advantages, disadvantages, and examples of each approach at the time of the study.

  13. Z

    Traffic Acquisition to LAMs Websites

    • data.niaid.nih.gov
    Updated Apr 30, 2022
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    Ioannis C. Drivas (2022). Traffic Acquisition to LAMs Websites [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_6505276
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    Dataset updated
    Apr 30, 2022
    Dataset provided by
    Ioannis C. Drivas
    Dimitrios Kouis
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Preliminary research efforts regarding Social Media Platforms and their contribution to website traffic in LAMs. Through the Similar Web API, the leading social networks (Facebook, Twitter, Youtube, Instagram, Reddit, Pinterest, LinkedIn) that drove traffic to each one of the 220 cases in our dataset were identified and analyzed in the first sheet. Aggregated results proved that Facebook platform was responsible for 46.1% of social traffic (second sheet).

  14. A

    Advertisement Intelligence Software Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Jul 22, 2025
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    Archive Market Research (2025). Advertisement Intelligence Software Report [Dataset]. https://www.archivemarketresearch.com/reports/advertisement-intelligence-software-563735
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    pdf, ppt, docAvailable download formats
    Dataset updated
    Jul 22, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Advertisement Intelligence Software market is experiencing robust growth, driven by the increasing need for data-driven decision-making in the digital advertising landscape. The market's complexity and the constant evolution of advertising platforms necessitate sophisticated tools for campaign optimization, performance analysis, and competitor benchmarking. This demand fuels the adoption of advertisement intelligence software across various industry verticals, including media agencies, marketing departments, and advertising technology companies. While precise market size figures are not provided, based on industry reports and the presence of numerous established players like Sensor Tower, App Annie, and SimilarWeb, we can estimate the 2025 market size at approximately $5 billion. Considering a plausible CAGR of 15% (a conservative estimate considering market dynamism), the market is projected to reach approximately $10 billion by 2033. This growth trajectory is fueled by several key trends, including the increasing adoption of mobile advertising, the rise of programmatic advertising, and the growing emphasis on cross-channel marketing attribution. However, challenges such as data privacy concerns and the complexity of integrating various data sources represent potential restraints on market expansion. The competitive landscape is characterized by a mix of established players and emerging startups. The established players benefit from extensive data networks and robust analytical capabilities. New entrants often focus on niche segments or innovative analytical approaches. The market is witnessing increased competition, pushing companies to constantly enhance their offerings through advanced features, improved user interfaces, and broader data coverage. This competitive pressure should further drive market expansion and innovation, leading to more sophisticated and user-friendly solutions. Regional variations in market penetration and growth rates are expected, with North America and Europe likely to maintain significant shares, while other regions experience accelerated growth. The ongoing refinement of data analytics techniques, coupled with increased automation capabilities, will likely reshape the market in the coming years.

  15. A

    Advertising Intelligence Tool Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Jun 17, 2025
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    Data Insights Market (2025). Advertising Intelligence Tool Report [Dataset]. https://www.datainsightsmarket.com/reports/advertising-intelligence-tool-1966874
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Jun 17, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The advertising intelligence tool market is experiencing robust growth, driven by the increasing need for brands to optimize their advertising campaigns across diverse digital channels. The market's expansion is fueled by several key factors, including the proliferation of digital advertising platforms, the rising complexity of advertising strategies, and the growing demand for data-driven decision-making in marketing. Businesses are increasingly relying on these tools to gain competitive insights, track campaign performance, identify emerging trends, and ultimately enhance their return on ad spend (ROAS). This necessitates sophisticated tools that provide comprehensive data analysis, competitive intelligence, and predictive analytics capabilities. The market is highly competitive, with established players like Semrush, SimilarWeb, and Sensor Tower alongside newer entrants continuously innovating to meet evolving market demands. The integration of artificial intelligence (AI) and machine learning (ML) is transforming the landscape, enabling more precise targeting, automated campaign optimization, and advanced predictive modeling. The projected Compound Annual Growth Rate (CAGR) suggests a significant expansion in market size over the forecast period (2025-2033). While precise figures are not provided, a reasonable estimation based on industry reports and observed growth trends indicates a market valued at approximately $5 billion in 2025, potentially reaching $8 billion by 2030, driven by increasing adoption across various industry verticals. Challenges include the high cost of sophisticated tools, the need for specialized expertise to interpret data effectively, and the ever-evolving landscape of digital advertising requiring continuous updates and adaptations of the tools themselves. Despite these challenges, the long-term outlook for the advertising intelligence tool market remains positive, fueled by consistent advancements in technology and the continued importance of data-driven advertising strategies.

  16. Bounce rate of leading consumer electronics sites worldwide 2024

    • statista.com
    Updated Jul 23, 2025
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    Statista (2025). Bounce rate of leading consumer electronics sites worldwide 2024 [Dataset]. https://www.statista.com/statistics/1325859/consumer-electronics-websites-bounce-rate-worldwide/
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    Dataset updated
    Jul 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2024
    Area covered
    Worldwide
    Description

    Among selected consumer electronics retailers worldwide, apple.com recorded the highest bounce rate in April 2024, at approximately **** percent. Rival samsung.com had a slightly lower bounce rate of nearly ** percent. Among selected consumer electronics e-tailers, huawei.com had the lowest bounce rate at ***** percent. Bounce rate is a marketing term used in web traffic analysis reflecting the percentage of visitors who enter the site and then leave without taking any further action like making a purchase or viewing other pages within the website ("bounce"). A sector with growth potential With one of the lowest online shopping cart abandonment rates globally in 2022, consumer electronics is a burgeoning e-commerce segment that places itself at the crossroads between technological progress and digital transformation. Boosted by the pandemic-induced surge in online shopping, the global market size of consumer electronics e-commerce was estimated at more than *** billion U.S. dollars in 2021 and forecast to nearly double less than five years later. Amazon and Apple lead the charts in electronics e-commerce With more than ** billion U.S. dollars in e-commerce net sales in the consumer electronics segment in 2022, apple.com was the uncontested industry leader. The global powerhouse surpassed e-commerce giants amazon.com and jd.com with more than *** billion U.S. dollars difference in online sales in the consumer electronics category.

  17. A

    Alternative Data Platform Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 3, 2025
    + more versions
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    Market Report Analytics (2025). Alternative Data Platform Report [Dataset]. https://www.marketreportanalytics.com/reports/alternative-data-platform-55013
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    ppt, pdf, docAvailable download formats
    Dataset updated
    Apr 3, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Alternative Data Platform market is experiencing robust growth, driven by the increasing need for businesses across diverse sectors to leverage non-traditional data sources for improved decision-making. The market, estimated at $5 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a Compound Annual Growth Rate (CAGR) of 25%. This growth is primarily attributed to several key factors. Firstly, the rising adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting businesses of all sizes. Secondly, the expanding application of alternative data in areas like fraud detection (BFSI), supply chain optimization (Retail and Logistics), and market prediction (IT and Telecommunications) is pushing market expansion. Furthermore, the increasing availability and affordability of alternative data sources, combined with advancements in data analytics and machine learning, are enabling businesses to extract greater value from these non-traditional datasets. While data security and privacy concerns present a challenge, the overall market outlook remains overwhelmingly positive. The market segmentation reveals strong growth across various applications and types. The BFSI sector is a major driver due to its need for enhanced risk management and fraud prevention. The cloud-based segment dominates the market due to its flexibility and accessibility. North America currently holds the largest market share, followed by Europe and Asia Pacific, reflecting the higher level of technological advancement and adoption in these regions. However, the Asia Pacific region is poised for significant growth due to increasing digitalization and rising investments in data analytics infrastructure. The competitive landscape is dynamic, with a mix of established players and emerging startups offering diverse solutions. The success of individual companies depends on their ability to innovate, provide reliable data, ensure data security, and offer user-friendly platforms. Competition is likely to intensify as more companies enter this rapidly evolving market.

  18. Information Organizations and Websites Performance

    • kaggle.com
    zip
    Updated Sep 17, 2020
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    Information Management Research Lab (2020). Information Organizations and Websites Performance [Dataset]. https://www.kaggle.com/imrlab/information-organizations-websites-global-report
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    zip(3013660 bytes)Available download formats
    Dataset updated
    Sep 17, 2020
    Authors
    Information Management Research Lab
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    Notice: You can check the new version 0.9.6 at the official page of Information Management Lab and at the Google Data Studio as well.

    Description of the Report and Topic Justification

    Now that the ICTs have matured, Information Organizations such as Libraries, Archives and Museums, also known as LAMs, proceed into the utilization of web technologies that are capable to expand the visibility and findability of their content. Within the current flourishing era of the semantic web, LAMs have voluminous amounts of web-based collections that are presented and digitally preserved through their websites. However, prior efforts indicate that LAMs suffer from fragmentation regarding the determination of well-informed strategies for improving the visibility and findability of their content on the Web (Vállez and Ventura, 2020; Krstić and Masliković, 2019; Voorbij, 2010). Several reasons related to this drawback. As such, administrators’ lack of data analytics competency in extracting and utilizing technical and behavioral datasets for improving visibility and awareness from analytics platforms; the difficulties in understanding web metrics that integrated into performance measurement systems; and hence the reduced capabilities in defining key performance indicators for greater usability, visibility, and awareness.

    In this enriched and updated technical report, the authors proceed into an examination of 504 unique websites of Libraries, Archives and Museums from all over the world. It is noted that the current report has been expanded by up to 14,81% of the prior one Version 0.9.5 of 439 domains examinations. The report aims to visualize the performance of the websites in terms of technical aspects such as their adequacy to metadata description of their content and collections, their loading speed, and security. This constitutes an important stepping-stone for optimization, as the higher the alignment with the technical compliencies, the greater the users’ behavior and usability within the examined websites, and thus their findability and visibility level in search engines (Drivas et al. 2020; Mavridis and Symeonidis 2015; Agarwal et al. 2012).

    One step further, within this version, we include behavioral analytics about users engagement with the content of the LAMs websites. More specifically, web analytics metrics are included such as Visit Duration, Pages per Visit, and Bounce Rates for 121 domains. We also include web analytics regarding the channels that these websites acquire their users, such as Direct traffic, Search Engines, Referral, Social Media, Email, and Display Advertising. SimilarWeb API was used to gather web data about the involved metrics.

    In the first pages of this report, general information is presented regarding the names of the examined organizations. This also includes their type, their geographical location, information about the adopted Content Management Systems (CMSs), and web server software types of integration per website. Furthermore, several other data are visualized related to the size of the examined Information Organizations in terms of the number of unique webpages within a website, the number of images, internal and external links and so on.

    Moreover, as a team, we proceed into the development of several factors that are capable to quantify the performance of websites. Reliability analysis takes place for measuring the internal consistency and discriminant validity of the proposed factors and their included variables. For testing the reliability, cohesion, and consistency of the included metrics, Cronbach’s Alpha (a), McDonald’s ω and Guttman λ-2 and λ-6 are used.
    - For Cronbach’s, a range of .550 up to .750 indicates an acceptable level of reliability and .800 or higher a very good level (Ursachi, Horodnic, and Zait, 2015). - McDonald’s ω indicator has the advantage to measure the strength of the association between the proposed variables. More specifically, the closer to .999 the higher the strength association between the variables and vice versa (Şimşek and Noyan, 2013). - Gutman’s λ-2 and λ-6 work verifiably to Cronbach’s a as they estimate the trustworthiness of variance of the gathered web analytics metrics. Low values less than .450 indicate high bias among the harvested web metrics, while values higher than .600 and above increase the trustworthiness of the sample (Callender and Osburn, 1979). -Kaiser–Meyer–Olkin (KMO) and Bartlett’s Test of Sphericity indicators are used for measuring the cohesion of the involved metrics. KMO and Bartlett’s test indicates that the closer the value is to .999 amongst the involved items, the higher the cohesion and consistency of them for potential categorization (Dziuban and Shirkey, 1974). Both descriptive statistics and reliability analyses were performed via JASP 0.14.1.0 software.

    To this end, this report contributes to the knowledge expansion of all the interest parties and stakeholders related to the research topic of improving the visibility and findability of LAMs and their content on the Web. It constitutes a well-informed compass, that could be adopted by such organizations, in order to implement potential strategies that combine both domain knowledge and data-driven culture in terms of awareness optimization on the internet realm.

    The Research Team Behind the Project

    The whole project is managed and optimized on a weekly basis by a big young and smiley team of scientists (alphabetically referred in the next section). All of them are undergraduate students at the Department of Archival, Library and Information Studies of the University of West Attica.

    They are responsible for the overall process of publishing the Technical Report which includes the initial organizations’ identification, and subsequently, websites testing, data gathering, curation and pre-processing, analysis, validation and visualization. Of course, the Team will continue to expand the capabilities of this report while involving new features, metrics, and further information regarding Libraries, Archives and Museums websites from all over the world.

    Notice: includes a plurality of technical and behavioral factors and variables concerning the examined information organizations' websites. Potentially, more features will be included on the next versions.

    Report Version 0.9.6 Correspondence: Ioannis C. Drivas (PhDc) idrivas@uniwa.gr | http://users.uniwa.gr/idrivas/ Research Lab of Information Management Department of Archival, Library Science and Information Studies University of West Attica.

  19. A

    Ad Intelligence Software Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Aug 10, 2025
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    Data Insights Market (2025). Ad Intelligence Software Report [Dataset]. https://www.datainsightsmarket.com/reports/ad-intelligence-software-1946632
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Aug 10, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Ad Intelligence Software market is experiencing robust growth, driven by the increasing need for precise and actionable insights in the dynamic digital advertising landscape. The market's expansion is fueled by the rising adoption of programmatic advertising, the growing complexity of multi-channel marketing campaigns, and the demand for improved return on ad spend (ROAS). Key players like Pathmatics, SimilarWeb, and Sensor Tower are capitalizing on this demand, offering sophisticated solutions that analyze ad performance across various platforms, identify competitor strategies, and optimize marketing budgets. The market's segmentation reflects the diverse needs of advertisers, ranging from small businesses to large multinational corporations. While challenges remain, such as data privacy concerns and the need for continuous software updates to accommodate evolving advertising technologies, the overall market outlook remains positive. We estimate the 2025 market size to be approximately $5 billion, based on the observed growth of related digital marketing technologies and the increasing sophistication of ad buying strategies. A projected CAGR of 15% from 2025-2033 indicates a substantial market expansion. This growth will be fueled by increasing adoption in emerging markets and continued innovation within the software capabilities. The competitive landscape is characterized by a mix of established players and emerging companies, fostering innovation and driving the development of more advanced analytical tools. This competition benefits advertisers by providing a wider range of options and driving down costs. The integration of artificial intelligence (AI) and machine learning (ML) into ad intelligence software is a significant trend, enhancing the capabilities of these platforms to identify patterns, predict future performance, and automate campaign optimization. Growth in mobile advertising and the rise of connected TV (CTV) are also expanding the scope of ad intelligence software, requiring platforms to adapt and provide comprehensive cross-platform analysis. The global nature of the market necessitates solutions that cater to regional differences in advertising practices and regulations.

  20. Industry vertical of organization for 86 websites in study.

    • plos.figshare.com
    xls
    Updated Jun 15, 2023
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    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen (2023). Industry vertical of organization for 86 websites in study. [Dataset]. http://doi.org/10.1371/journal.pone.0268212.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Bernard J. Jansen; Soon-gyo Jung; Joni Salminen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Industry vertical of organization for 86 websites in study.

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(2025). similarweb.com Traffic Analytics Data [Dataset]. https://analytics.explodingtopics.com/website/similarweb.com

similarweb.com Traffic Analytics Data

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Dataset updated
Aug 1, 2025
Variables measured
Global Rank, Monthly Visits, Authority Score, US Country Rank, Online Services Category Rank
Description

Traffic analytics, rankings, and competitive metrics for similarweb.com as of August 2025

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