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In web analytics and website management, a pageview or page view, abbreviated in business to PV and occasionally called page impression, is a request to load a single HTML file (web page) of an Internet site.[1] On the World Wide Web, a page request would result from a web surfer clicking on a link on another page pointing to the page in question.

In contrast, a hit refers to a request for any file from a web server. Therefore, there may be many hits per page view since an HTML page can contain multiple files such as images, videos, JavaScripts, cascading style sheets (CSS), etc.[citation needed]

On balance, page views refer to a number of pages viewed or clicked on the site during the given time.[2]

Page views may be counted as part of web analytics. For the owner of the site, this information can be useful to see if any change in the "page" (such as the information or the way it is presented) results in more visits. If there are any advertisements on the page, the publishers would also be interested in the number of page views to determine their expected revenue from the ads. For this reason, it is a term that is used widely for Internet marketing and advertising.[3]


The page impression has long been a measure of user activity on a website. However, the activity is not necessarily associated with loading a complete HTML page. Modern programming techniques can serve pages by other means that don't show as HTTP requests.


Since page views help estimate the popularity of sites, it helps determine their value for advertising revenue. The most common metric is CPM. It stands for 'Cost per thousand'(the M is the Roman numeral for 1,000)[4] and it is commonly used metrics to measure page views divided by the thousands, that is, cost per 1000 views, used for the ad rates and thus, the less CPM is, the better deal it offers to advertisers.[5] However, there has been a growing concern that CPM is not as trustworthy as it looks in the advertising market because, although, with CPM arrangement, everyone who visits a site makes publishers’ money, for an advertiser's view, CPM is being challenged in comparison to CPC or CPA in terms of adverts’ efficiency because visiting does not mean clicking the ads.[6]


The preferred way to count page views is using a web analytics software. They can measure the number of pages on any site and therefore, it helps people to receive a rough estimate of page views on web sites.[7] There are also many other page view measurement tools available including open source ones as well as licensed products.

Hit ratio[edit]

Hit ratio refers to the percentage of computer memory accesses (number of HTTPS requests delivered per requests received) that are found in certain levels of the memory hierarchy. In other words, it is a measure of content requests that a web caching system can deliver successfully from its cache storage, compared to how many requests it receives.[8][9] There are two types of hit ratios:

  • Cache hit ratio, referring to number of requests made;[10]
  • Byte hit ratio, referring to amount of bandwidth that a browser's caching system has saved.[10][11]

Criticism and concerns[edit]

Despite a wide range of uses of page view, it has come in for criticisms.


Page view can be manipulated or boosted for specific purposes.[12] For example, a recent incident, called 'page view fraud', compromised the accuracy of measurement of page view by boosting the page view. Perpetrators used a tool called 'a bot' to buy fake page-views for attention, recognition, and feedback, increasing the site's value.[13] As a result, some people already started building alternatives to measure audiences, such as "Ophan", saying that the page view is becoming passe.[14]

Humans vs. machines[edit]

Fake page views can reflect bots instead of humans.[15]

Wikipedia pageviews[edit]

Wikipedia provides tools that allow one to see how many people have visited a Wikipedia article during a given time period. Such have been used for tools that for instance display the most popular articles of the day.[16] Wikipedia pageviews of certain types of articles correlate with changes in stock market prices,[17] box office success of movies,[18] spread of disease[19][20] among other applications of datamining. Since search engines directly influence what is popular on Wikipedia such statistics may provide a more unfiltered and real-time view into what people are searching for on the Web[21] and societal interests.[22] For instance they can be used to gain insights into public anxiety and information seeking after or during events[23] or for the identification of concepts with significant increase of interest from the public.[24] In 2015, a study conducted by the Association for the Advancement of Artificial Intelligence (AAAI) examined the influence of Reddit posts on Wikipedia pageviews.[25]

See also[edit]


  1. ^ Doyle, C. (2011). A dictionary of marketing. Oxford: Oxford University Press. ISBN 9780191727962.
  2. ^ Carey, E. (2012). "Page View versus Page Visits - Atlantic Webworks Perspectives". Atlanticwebworks. Archived from the original on 30 October 2014. Retrieved 28 October 2014.
  3. ^ Bennett, L. (January 10, 2012). "Metrics that Matter & the Death of the Page View". Chartbeat Blog. Archived from the original on 13 January 2012. Retrieved 10 January 2012.
  4. ^ Heisel, C. (November 30, 2008). "What does CPM stand for?". Chris Heisel. Archived from the original on 19 October 2014. Retrieved 30 October 2014.
  5. ^ Scocco, D. (March 27, 2008). "How Much Should I Charge for my Advertising Space? : @ProBlogger". Problogger.net. Archived from the original on 30 October 2014. Retrieved 30 October 2014.
  6. ^ Johnston, M. (2013). "CPM vs CPC vs CPA: How to Sell Display Ads". Monetizepros.com. Archived from the original on 7 November 2014. Retrieved 30 October 2014.
  7. ^ Agarwal, A. (2008). "Measure the Number of Page Views on any Site". Digital Inspiration. Archived from the original on 30 October 2014. Retrieved 30 October 2014.
  8. ^ "What is Cache Hit Ratio?". www.stackpath.com. 24 May 2021. Archived from the original on 1 February 2022. Retrieved 1 February 2022.
  9. ^ McKinnon, Jenni (2 July 2019). "Hit and Miss Ratios, and how to calculate them". WP Rocket. Archived from the original on 2022-02-01. Retrieved 2022-02-01.
  10. ^ a b Wessels, Duane (June 2001). Web Caching. O'Reilly Media, Inc. pp. 193–200. ISBN 978-1-56592-536-6. OCLC 1100903884.
  11. ^ "Hit Ratios - Web Caching [Book]". www.oreilly.com. July 2001. Retrieved 12 March 2022.
  12. ^ Holiday, R. (2012). "What is Media Manipulation?—A Definition and Explanation". Forbes. Archived from the original on 30 October 2014. Retrieved 30 October 2014.
  13. ^ Seidel, L. (2014). "The Pageview Fraud, PLEASE READ! by Lilyas on deviantART". Lilyas.deviantart.com. Archived from the original on 11 November 2014. Retrieved 30 October 2014.
  14. ^ Fischer, M. (March 18, 2014). "The Pageview is Passé: New Metrics Emerge to Measure Audiences". American Journalism Review. Archived from the original on 30 October 2014. Retrieved 30 October 2014.
  15. ^ Akhtar, Omar (July 31, 2014). "No more fake page views from machines! Google Analytics introduces "bot-filtering"". The Hub. Archived from the original on February 20, 2019. Retrieved August 20, 2016.
  16. ^ "Making our pageview data easily accessible – Wikimedia Blog". Wikimedia Blog. 14 December 2015. Archived from the original on 11 April 2017. Retrieved 30 April 2017.
  17. ^ Moat, Helen Susannah; Curme, Chester; Avakian, Adam; Kenett, Dror Y.; Stanley, H. Eugene; Preis, Tobias (8 May 2013). "Quantifying Wikipedia Usage Patterns Before Stock Market Moves". Scientific Reports. 3: 1801. Bibcode:2013NatSR...3E1801M. doi:10.1038/srep01801. ISSN 2045-2322. PMC 3647164.
  18. ^ Mestyán, Márton; Yasseri, Taha; Kertész, János (21 August 2013). "Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data". PLOS ONE. 8 (8): e71226. arXiv:1211.0970. Bibcode:2013PLoSO...871226M. doi:10.1371/journal.pone.0071226. ISSN 1932-6203. PMC 3749192. PMID 23990938.
  19. ^ R., Laurent, Michaël; J., Vickers, Tim (1 July 2009). "Seeking Health Information Online: Does Wikipedia Matter?". Journal of the American Medical Informatics Association. 16 (4): 471–479. doi:10.1197/jamia.M3059. ISSN 1067-5027. PMC 2705249. PMID 19390105.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  20. ^ McIver, David J.; Brownstein, John S. (17 April 2014). "Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in the United States in Near Real-Time". PLOS Computational Biology. 10 (4): e1003581. Bibcode:2014PLSCB..10E3581M. doi:10.1371/journal.pcbi.1003581. ISSN 1553-7358. PMC 3990502. PMID 24743682.
  21. ^ Spoerri, Anselm (2 April 2007). "What is popular on Wikipedia and why?". First Monday. 12 (4). doi:10.5210/fm.v12i4.1765. Archived from the original on 5 May 2017. Retrieved 30 April 2017.
  22. ^ Huss, Jon W.; Lindenbaum, Pierre; Martone, Michael; Roberts, Donabel; Pizarro, Angel; Valafar, Faramarz; Hogenesch, John B.; Su, Andrew I. (1 January 2010). "The Gene Wiki: community intelligence applied to human gene annotation". Nucleic Acids Research. 38 (suppl_1): D633–D639. doi:10.1093/nar/gkp760. ISSN 0305-1048. PMC 2808918. PMID 19755503.
  23. ^ Tausczik, Yla; Faasse, Kate; Pennebaker, James W.; Petrie, Keith J. (1 February 2012). "Public Anxiety and Information Seeking Following the H1N1 Outbreak: Blogs, Newspaper Articles, and Wikipedia Visits". Health Communication. 27 (2): 179–185. doi:10.1080/10410236.2011.571759. ISSN 1041-0236. PMID 21827326. S2CID 3783651.
  24. ^ Ciglan, Marek; Nørv\a ag, Kjetil (1 January 2010). "WikiPop". Proceedings of the 19th ACM international conference on Information and knowledge management. pp. 1931–1932. doi:10.1145/1871437.1871769. ISBN 9781450300995. S2CID 15890386.
  25. ^ "Determining the influence of reddit posts on wikipedia pageviews, AAAI Workshop - Technical Report, 2015, WS-15-19 pp. 75 - 82". Archived from the original on 6 August 2020. Retrieved 11 May 2020. {{cite journal}}: Cite journal requires |journal= (help)

Further reading[edit]