503:- A visit or session is defined as a series of page requests or, in the case of tags, image requests from the same uniquely identified client. Usually, the number of Visits is more than Visitors (Unique Visitors). A unique client is commonly identified by an IP address or a unique ID that is placed in the browser cookie. A visit is considered ended when no requests have been recorded in some number of elapsed minutes. A 30-minute limit ("time out") is used by many analytics tools but can, in some tools (such as Google Analytics), be changed to another number of minutes. Analytics data collectors and analysis tools have no reliable way of knowing if a visitor has looked at other sites between page views; a visit is considered one visit as long as the events (page views, clicks, whatever is being recorded) are 30 minutes or less close together. A visit can consist of a one-page view or thousands. A unique visit session can also be extended if the time between page loads indicates that a visitor has been viewing the pages continuously.
491:- The uniquely identified client that is generating page views or hits within a defined period time (e.g. day, week or month). A uniquely identified client is usually a combination of a machine (one's desktop computer at work for example) and a browser (Firefox on that machine). The identification is usually via a persistent cookie that has been placed on the computer by the site page code. An older method, used in log file analysis, is the unique combination of the computer's IP address and the User-Agent (browser) information provided to the web server by the browser. The "Visitor" is not the same as the human being sitting at the computer at the time of the visit, since an individual human can use different computers or, on the same computer, can use different browsers, and will be seen as a different visitor in each circumstance. Increasingly, but still, somewhat rarely, visitors are uniquely identified by Flash LSO's (
483:- A request for a file, or sometimes an event such as a mouse click, that is defined as a page in the setup of the web analytics tool. Usually the number of pageview is more than Visits and Visitors (Unique Visitors). An occurrence of the script being run in page tagging. In log analysis, a single page view may generate multiple hits as all the resources required to view the page (images, .js and .css files) are also requested from the webserver. A "refresh" of same webpage can be counted as another pageview. For example, at time: 16:07, user viewed page A, 2 seconds later, the user clicks "refresh" button in the browser, the number of pageview of page A then is 2.
475:- A request for a file from the webserver. Available only in log analysis. The number of hits received by a website is frequently cited to assert its popularity, but this number is extremely misleading and dramatically overestimates popularity. A single web-page typically consists of multiple (often dozens) of discrete files, each of which is counted as a hit as the page is downloaded, so the number of hits is really an arbitrary number more reflective of the complexity of individual pages on the website than the website's actual popularity. The total number of visits or page views provides a more realistic and accurate assessment of popularity.
258:
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450:(The Joint Industry Committee for Web Standards in the UK and Ireland), and The DAA (Digital Analytics Association), formally known as the WAA (Web Analytics Association, US). However, many terms are used in consistent ways from one major analytics tool to another, so the following list, based on those conventions, can be a useful starting point:
841:-based solutions, an alternative to the use of an invisible image is to implement a call back to the server from the rendered page. In this case, when the page is rendered on the web browser, a piece of JavaScript code would call back to the server and pass information about the client that can then be aggregated by a web analytics company.
742:) made to the web server. This was a reasonable method initially since each website often consisted of a single HTML file. However, with the introduction of images in HTML, and websites that spanned multiple HTML files, this count became less useful. The first true commercial Log Analyzer was released by IPRO in 1994.
596:- The time a single page (or a blog, ad banner) is on the screen, measured as the calculated difference between the time of the request for that page and the time of the next recorded request. If there is no next recorded request, then the viewing time of that instance of that page is not included in reports.
573:- Frequency measures how often visitors come to a website in a given time period. It is calculated by dividing the total number of sessions (or visits) by the total number of unique visitors during a specified time period, such as a month or year. Sometimes it is used interchangeable with the term "loyalty."
614:- Average amount of time that visitors spend on the site each time they visit. It is calculated as the sum total of the duration of all the sessions divided by the total number of sessions. This metric can be complicated by the fact that analytics programs can not measure the length of the final page view.
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Third-party information gathering is subject to any network limitations and security applied. Countries, Service
Providers and Private Networks can prevent site visit data from going to third parties. All the methods described above (and some other methods not mentioned here, like sampling) have the
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There are no globally agreed definitions within web analytics as the industry bodies have been trying to agree on definitions that are useful and definitive for some time, that is saying, metrics in tools and products from different companies may have different ways to measure, counting, as a result,
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are not always unique to users and may be shared by large groups or proxies. In some cases, the IP address is combined with the user agent in order to more accurately identify a visitor if cookies are not available. However, this only partially solves the problem because often users behind a proxy
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IP Intelligence, or
Internet Protocol (IP) Intelligence, is a technology that maps the Internet and categorizes IP addresses by parameters such as geographic location (country, region, state, city and postcode), connection type, Internet Service Provider (ISP), proxy information, and more. The first
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The hotel problem is generally the first problem encountered by a user of web analytics. The problem is that the unique visitors for each day in a month do not add up to the same total as the unique visitors for that month. This appears to an inexperienced user to be a problem in whatever analytics
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Regardless of the vendor solution or data collection method employed, the cost of web visitor analysis and interpretation should also be included. That is, the cost of turning raw data into actionable information. This can be from the use of third party consultants, the hiring of an experienced web
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have therefore led a noticeable minority of users to block or delete third-party cookies. In 2005, some reports showed that about 28% of
Internet users blocked third-party cookies and 22% deleted them at least once a month. Most vendors of page tagging solutions have now moved to provide at least
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Actually only three visitors have been in the hotel over this period. The problem is that a person who stays in a room for two nights will get counted twice if they are counted once on each day, but are only counted once if the total for the period is looked at. Any software for web analytics will
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may happen real-time or "unreal"-time, depending on the type of information sought. Typically, front-page editors on high-traffic news media sites will want to monitor their pages in real-time, to optimize the content. Editors, designers or other types of stakeholders may analyze clicks on a wider
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were commonly seen — these were images included in a web page that showed the number of times the image had been requested, which was an estimate of the number of visits to that page. In the late 1990s, this concept evolved to include a small invisible image instead of a visible one, and, by
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also presented a problem for log file analysis. If a person revisits a page, the second request will often be retrieved from the browser's cache, and so no request will be received by the web server. This means that the person's path through the site is lost. Caching can be defeated by configuring
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As the internet has matured, the proliferation of automated bot traffic has become an increasing problem for the reliability of web analytics. As bots traverse the internet, they render web documents in ways similar to organic users, and as a result may incidentally trigger the same code that web
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Counting is activated by opening the page (given that the web client runs the tag scripts), not requesting it from the server. If a page is cached, it will not be counted by server-based log analysis. Cached pages can account for up to one-third of all page views, which can negatively impact many
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central problem of being vulnerable to manipulation (both inflation and deflation). This means these methods are imprecise and insecure (in any reasonable model of security). This issue has been addressed in several papers, but to date the solutions suggested in these papers remain theoretical.
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Data about clicks may be gathered in at least two ways. Ideally, a click is "logged" when it occurs, and this method requires some functionality that picks up relevant information when the event occurs. Alternatively, one may institute the assumption that a page view is a result of a click, and
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Another problem is cookie deletion. When web analytics depend on cookies to identify unique visitors, the statistics are dependent on a persistent cookie to hold a unique visitor ID. When users delete cookies, they usually delete both first- and third-party cookies. If this is done between
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However, third-party cookies in principle allow tracking an individual user across the sites of different companies, allowing the analytics vendor to collate the user's activity on sites where he provided personal information with his activity on other sites where he thought he was anonymous.
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Both logfile analysis programs and page tagging solutions are readily available to companies that wish to perform web analytics. In some cases, the same web analytics company will offer both approaches. The question then arises of which method a company should choose. There are advantages and
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Log files contain information on visits from search engine spiders, which generally are excluded from the analytics tools using JavaScript tagging. (Some search engines might not even execute JavaScript on a page.) Although these should not be reported as part of human activity, it is useful
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interactions with the site, the user will appear as a first-time visitor at their next interaction point. Without a persistent and unique visitor id, conversions, click-stream analysis, and other metrics dependent on the activities of a unique visitor over time, cannot be accurate.
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The web analytics service also manages the process of assigning a cookie to the user, which can uniquely identify them during their visit and in subsequent visits. Cookie acceptance rates vary significantly between websites and may affect the quality of data collected and reported.
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is a ratio of users who click on a specific link to the number of total users who view a page, email, or advertisement. It is commonly used to measure the success of an online advertising campaign for a particular website as well as the effectiveness of email campaigns. Another
459:- The percentage of visits that are single-page visits and without any other interactions (clicks) on that page. In other words, a single click in a particular session is called a bounce. A high bounce rate can indicate that the content or user experience needs improvement.
555:- (also called 'Absolute Unique Visitor' in some tools) A visit from a uniquely identified client that has theoretically not made any previous visits. Since the only way of knowing whether the uniquely identified client has been to the site before is the presence of a
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Logfile analysis is almost always performed in-house. Page tagging can be performed in-house, but it is more often provided as a third-party service. The economic difference between these two models can also be a consideration for a company deciding which to purchase.
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Which solution is cheaper to implement depends on the amount of technical expertise within the company, the vendor chosen, the amount of activity seen on the websites, the depth and type of information sought, and the number of distinct websites needing statistics.
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server have the same user agent. Other methods of uniquely identifying a user are technically challenging and would limit the trackable audience or would be considered suspicious. Cookies reach the lowest common denominator without using technologies regarded as
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the network traffic passing between the web server and the outside world. Packet sniffing involves no changes to the web pages or web servers. Integrating web analytics into the webserver software itself is also possible. Both these methods claim to provide better
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External data: can be combined with on-site data to help augment the website behavior data described above and interpret web usage. For example, IP addresses are usually associated with
Geographic regions and internet service providers, e-mail open and
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sent from the vendor's domain instead of the domain of the website being browsed. Third-party cookies can handle visitors who cross multiple unrelated domains within the company's site, since the cookie is always handled by the vendor's servers.
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is an instance of an advertisement appearing on a viewed page. An advertisement can be displayed on a viewed page below the area actually displayed on the screen, so most measures of impressions do not necessarily mean an advertisement has been
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In the past, web analytics has been used to refer to on-site visitor measurement. However, this meaning has become blurred, mainly because vendors are producing tools that span both categories. Many different vendors provide on-site
608:- A unique visitor with activity consisting of a visit to a site during a reporting period and where the unique visitor visited the site prior to the reporting period. The individual is counted only once during the reporting period.
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Logfile analysis typically involves a one-off software purchase; however, some vendors are introducing maximum annual page views with additional costs to process additional information. In addition to commercial offerings, several
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Each stage impacts or can impact (i.e., drives) the stage preceding or following it. So, sometimes the data that is available for collection impacts the online strategy. Other times, the online strategy affects the data collected.
549:- Web analytics tools allow data segmentation, which means breaking down data into smaller subsets based on criteria such as demographics, location, or behavior. This provides a deeper understanding of different audience segments.
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The data is on the company's servers and is in a standard, rather than a proprietary, format. This makes it easy for a company to switch programs later, use several different programs, and analyze historical data with a new
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Some companies produce solutions that collect data through both log files and page tagging and can analyze both kinds. By using a hybrid method, they aim to produce more accurate statistics than either method on its own.
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using JavaScript, to pass along with the image request certain information about the page and the visitor. This information can then be processed remotely by a web analytics company, and extensive statistics generated.
509:- Average amount of time that visitors spend actually interacting with content on a web page, based on mouse moves, clicks, hovers, and scrolls. Unlike session duration and page view duration/time on page, this metric
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Concerns about the accuracy of log file analysis in the presence of caching, and the desire to be able to perform web analytics as an outsourced service, led to the second data collection method, page tagging or
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exploration, and share of voice on web properties. It is usually used to understand how to market a site by identifying the keywords tagged to this site, either from social media or from other websites.
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analytics use to count traffic. Jointly, this incidental triggering of web analytics events impacts interpretability of data and inferences made upon that data. IPM provided a proof of concept of how
279:: This stage usually takes counts and makes them ratios, although there still may be some counts. The objective of this stage is to take the data and conform it into information, specifically metrics.
537:- A discrete action or class of actions that occur on a website. A page view is a type of event. Events also encapsulate clicks, form submissions, keypress events, and other client-side user actions.
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For
Logfile analysis data must be stored and archived, which often grows large quickly. Although the cost of hardware to do this is minimal, the overhead for an IT department can be considerable.
590:- A visitor that has not made any previous visits. This definition creates a certain amount of confusion (see common confusions below), and is sometimes substituted with analysis of first visits.
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focuses on on-site analytics. An editor of a website uses click analytics to determine the performance of his or her particular site, with regards to where the users of the site are clicking.
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lookup by the user's computer to determine the IP address of the collection server. On occasion, delays in completing successful or failed DNS lookups may result in data not being collected.
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Formulating online strategy: This stage is concerned with the online goals, objectives, and standards for the organization or business. These strategies are usually related to making a
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The script may have access to additional information on the web client or on the user, not sent in the query, such as visitors' screen sizes and the price of the goods they purchased.
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record some of their transactions in a log file. It was soon realized that these log files could be read by a program to provide data on the popularity of the website. Thus arose
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Marketing
Management: A Value-Creation Process (2nd Edition) by Alain Jolibert, Pierre-Louis Dubois, Hans Mühlbacher, Laurent Flores, Pierre-Louis Jolibert Dubois, 2012, p. 359.
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The web server reliably records every transaction it makes, e.g. serving PDF documents and content generated by scripts, and does not rely on the visitors' browsers cooperating.
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Customer lifecycle analytics is a visitor-centric approach to measuring. Page views, clicks and other events (such as API calls, access to third-party services, etc.) are all
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Network-level and server-generated data associated with HTTP requests: not part of an HTTP request, but it is required for successful request transmissions - for example, the
245:. It can be used to estimate how traffic to a website changes after launching a new advertising campaign. Web analytics provides information about the number of visitors to a
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are associated with online purchases. On-site web analytics measures the performance of a specific website in a commercial context. This data is typically compared against
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Data is gathered via a component ("tag") in the page, usually written in JavaScript. It is typically used in conjunction with a server-side scripting language (such as
390: are the most widely used on-site web analytics service; although new tools are emerging that provide additional layers of information, including
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a same metric name may represent different meaning of data. The main bodies who have had input in this area have been the IAB (Interactive
Advertising Bureau),
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Jansen, B. J. (2009). Understanding user-web interactions via web analytics. Synthesis
Lectures on Information Concepts, Retrieval, and Services, 1(1), 1-102.
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is the total numbers clicked divided by total number of
Impressions, as the metric of Click-Through Rate is to measure the ration of clicks and impressions,
543:- A statistic applied to an individual page, not a web site. The percentage of visits seeing a page where that page is the final page viewed in the visit.
467:- the chronological sequence of page views within a visit or session. Analysis of this path provides information about users' session goals and user goals.
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The goal of A/B testing is to identify and suggest changes to web pages that increase or maximize the effect of a statistically tested result of interest.
272:: This stage is the collection of the basic, elementary data. Usually, these data are counts of things. The objective of this stage is to gather the data.
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The fundamental goal of web analytics is to collect and analyze data related to web traffic and usage patterns. The data mainly comes from four sources:
602:- A visitor that has made at least one previous visit. The period between the last and current visit is called visitor recency and is measured in days.
990:, it is possible to track visitors' locations. Using an IP geolocation database or API, visitors can be geolocated to city, region, or country level.
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and the number of page views, or creates user behavior profiles. It helps gauge traffic and popularity trends, which is useful for market research.
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The page tagging service manages the process of assigning cookies to visitors; with log file analysis, the server has to be configured to do this.
519:- Page depth is the approximate "size" of an average visit, calculated by dividing the total number of page views by the total number of visits.
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Clickpath
Analysis with referring pages on the left and arrows and rectangles differing in thickness and expanse to symbolize movement quantity
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was defined as a sequence of requests from a uniquely identified client that expired after a certain amount of inactivity, usually 30 minutes.
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accurately measure the length of engagement in the final page view, but it is not available in many analytics tools or data collection methods.
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As the table shows, the hotel has two unique users each day over three days. The sum of the totals with respect to the days is therefore six.
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refers to web measurement and analysis regardless of whether a person owns or maintains a website. It includes the measurement of a website's
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is a report technique in which statistics (clicks) or hot spots are superimposed, by physical location, on a visual snapshot of the web page.
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Plaza, Beatriz (18 September 2009). "Monitoring web traffic source effectiveness with Google Analytics: An experiment with time series".
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Collecting website data using a third-party data collection server (or even an in-house data collection server) requires an additional
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Two units of measure were introduced in the mid-1990s to gauge more accurately the amount of human activity on web servers. These were
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Farris, P., Bendle, N.T., Pfeifer, P.E. Reibstein, D.J. (2009) Key Marketing Metrics The 50+ Metrics Every Manager needs to know,
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The web server normally already produces log files, so the raw data is already available. No changes to the website are required.
2203:, In book: Encyclopedia of Information Science and Technology, Third Edition, Publisher: IGI Global, Editors: Mehdi Khosrow-Pour
1574:, In book: Encyclopedia of Information Science and Technology, Third Edition, Publisher: IGI Global, Editors: Mehdi Khosrow-Pour
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embedded in the webpage to make image requests to a third-party analytics-dedicated server, whenever a webpage is rendered by a
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Developing KPI: This stage focuses on using the ratios (and counts) and infusing them with business strategies, referred to as
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Tullis, Tom & Albert, Bill (2008) Measuring the User Experience. Collecting, Analyzing and Presenting Usability Metrics.
2004:
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instead of being stored as separate data points. Customer lifecycle analytics attempts to connect all the data points into a
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can then be performed. For example, what revenue increase or cost savings can be gained by analyzing the web visitor data?
711:), including sessions and referrals. These are usually captured by internal logs rather than public web analytics services.
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During the period each room has had two unique users. The sum of the totals with respect to the rooms is therefore four.
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sum these correctly for the chosen time period, thus leading to the problem when a user tries to compare the totals.
1022:, online fraud detection, localized search, enhanced analytics, global traffic management, and content distribution.
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or, if desired, when a mouse click occurs. Both collect data that can be processed to produce web traffic reports.
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1799:"A Data Warehouse/Online Analytic Processing Framework for Web Usage Mining and Business Intelligence Reporting"
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Complex page tagging vendors charge a monthly fee based on volume i.e. number of page views per month collected.
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Page tagging can report on events that do not involve a request to the web server, such as interactions within
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Application-level data sent with HTTP requests: generated and processed by application-level programs (such as
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Another essential function developed by the analysts for the optimization of the websites are the experiments:
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Burby, Jason and Atchison, Shane (2007) Actionable Web Analytics: Using Data to Make Smart Business Decisions.
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effectiveness. Web analytics applications can also help companies measure the results of traditional print or
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1633:"Revisiting log file analysis versus page tagging": McGill University Web Analytics blog article (CMIS 530)
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1508:"From web analytics to digital marketing optimization: Increasing the commercial value of digital analytics"
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technology. This information is used by businesses for online audience segmentation in applications such as
885:. Thus there are no external server calls that can slow page load speeds, or result in uncounted page views.
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the web server, but this can result in degraded performance for the visitor and bigger load on the servers.
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Menasalvas, Ernestina; Millán, Socorro; Peña, José M.; Hadjimichael, Michael; Marbán, Oscar (July 2004).
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In the early 1990s, website statistics consisted primarily of counting the number of client requests (or
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The way to picture the situation is by imagining a hotel. The hotel has two rooms (Room A and Room B).
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1875:"Home News Access the Guide Tools Education Shopping Internet Cookies- Spyware or Neutral Technology?"
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WAA Standards Committee. "Web analytics definitions." Washington DC: Web Analytics Association (2008).
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286:(KPI). Many times, KPIs deal with conversion aspects, but not always. It depends on the organization.
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1713:"Advanced Customer Analytics: Strategic Value Through Integration of Relationship-Oriented Big Data"
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531:- "refers to a single instance of a user following a hyperlink from one page in a site to another".
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Arikan, Akin (2008) Multichannel Marketing. Metrics and Methods for On and Offline Success. Sybex.
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audience (opportunity), share of voice (visibility), and buzz (comments) that is happening on the
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Davis, J. (2006) ‘Marketing Metrics: How to create Accountable Marketing plans that really work’
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movies, partial form completion, mouse events such as onClick, onMouseOver, onFocus, onBlur, etc.
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Although web analytics companies deny doing this, other companies such as companies supplying
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time frame to help them assess performance of writers, design elements or advertisements etc.
411:. There are two main technical ways of collecting the data. The first and traditional method,
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was defined as a request made to the web server for a page, as opposed to a graphic, while a
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For Logfile analysis software need to be maintained, including updates and security patches.
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label is not reliable if the site's cookies have been deleted since their previous visit.
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Web analytics 2.0:: The Art of Online Accountability and Science of Customer Centricity
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as well as their competitors are easily triggered by common bot deployment strategies.
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Other methods of data collection are sometimes used. Packet sniffing collects data by
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Most web analytics processes come down to four essential stages or steps, which are:
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software they are using. In fact it is a simple property of the metric definitions.
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Page tagging is available to companies who do not have access to their web servers.
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1379:"Using mixed methods to study the historical use of web beacons in web tracking"
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Clifton, Brian (2010) Advanced Web Metrics with Google Analytics, 2nd edition,
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1435:"Study on Factors Associated With Bounce Rates on Consumer Product Websites"
525:- Average amount of time that visitors spend on an average page of the site.
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Kitchens, Brent; Dobolyi, David; Li, Jingjing; Abbasi, Ahmed (2018-04-03).
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The main advantages of page tagging over log file analysis are as follows:
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The main advantages of log file analysis over page tagging are as follows:
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Naor, M.; Pinkas, B. (1998). "Secure accounting and auditing on the Web".
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is a controlled experiment with two variants, in online settings, such as
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Sostre, Pedro and LeClaire, Jennifer (2007) Web Analytics for Dummies.
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1548:"How a web session is defined in Universal Analytics - Analytics Help"
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Historically, vendors of page-tagging analytics solutions have used
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is a special type of web analytics that gives special attention to
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Johnson, R.; Staddon, J. (2007). "Deflation-secure web metering".
1904:. Lecture Notes in Computer Science. Vol. 1403. p. 576.
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1977:. Lecture Notes in Computer Science. Vol. 1318. pp.
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Naor, M.; Pinkas, B. (1998). "Secure and efficient metering".
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and having cookies enabled/active leads to security concerns.
1094:. Common metrics used in customer lifecycle analytics include
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therefore log a simulated click that led to that page view.
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Lately, page tagging has become a standard in web analytics.
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Bradley N (2007) Marketing Research. Tools and Techniques.
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Measurement, collection, analysis and reporting of web data
2022:
International Journal of Information and Computer Security
1760:"Web analytics: more than website performance evaluation?"
965:
analyst, or the training of a suitable in-house person. A
906:
704:
1618:"Page Tagging vs. Log Analysis An Executive White Paper"
594:
Page time viewed/page visibility time/page view duration
1831:"Analytics Poisoning: A Short Review - IPM Corporation"
1710:
1660:
664:
Off-site web analytics is based on open data analysis,
1512:
Journal of Direct, Data and Digital Marketing Practice
1293:
423:
records file requests by browsers. The second method,
909:) to manipulate and (usually) store it in a database.
495:), which are less susceptible to privacy enforcement.
1854:"Study: Consumers Delete Cookies at Surprising Rate"
1790:
1241:
378:
for performance and is used to improve a website or
333:
There are at least two categories of web analytics,
226:. Web analytics is not just a process for measuring
2190:Peterson Eric T (2005) Web Site Measurement Hacks.
844:
1968:
1636:"Revisiting Log File Analysis versus Page tagging"
1090:that can offer insights into visitor behavior and
994:generation of IP Intelligence was referred to as
853:
685:data: directly comes from HTTP request messages (
517:Average page depth/page views per average session
2208:
563:that had been received on a previous visit, the
2147:
1577:
1071:
794:, and by ignoring requests from known spiders.
723:
2019:
1970:"Auditable metering with lightweight security"
1959:
1758:Önder, Irem; Berbekova, Adiyukh (2022-08-10).
1757:
1605:Increasing Accuracy for Online Business Growth
1584:Web Traffic Data Sources and Vendor Comparison
1274:(cookies assigned from the client subdomain).
1505:
892:
672:
188:
1803:International Journal of Intelligent Systems
1586:by Brian Clifton and Omega Digital Media Ltd
1481:International Journal of Intelligent Systems
1131:Common sources of confusion in web analytics
1383:International Journal of Digital Humanities
346:
328:
230:but can be used as a tool for business and
1932:
1899:
1797:Hu, Xiaohua; Cercone, Nick (1 July 2004).
1506:Chaffey, Dave; Patron, Mark (2012-07-01).
981:
645:the number of users (who clicked and saw).
362:
195:
181:
2148:Kaushik, Avinash; Raybould, Dave (2007).
2067:
2033:
1986:
1814:
1796:
1717:Journal of Management Information Systems
1662:"Page Tagging (cookies) vs. Log Analysis"
1523:
774:and robots in the late 1990s, along with
649:
2199:Zheng, J. G. and Peltsverger, S. (2015)
1685:
1029:
440:
256:
253:Basic steps of the web analytics process
2128:
1764:International Journal of Tourism Cities
1376:
14:
2209:
1851:
1570:Zheng, G. & Peltsverger S. (2015)
1441:, WORLD SCIENTIFIC, pp. 526–546,
1228:
2093:
1902:Advances in Cryptology – EUROCRYPT'98
1706:
1704:
1607:- a web analytics accuracy whitepaper
1135:
261:Basic Steps of Web Analytics Process
1432:
1294:Secure analytics (metering) methods
932:
24:
1935:Computer Networks and ISDN Systems
1701:
1025:
945:open-source logfile analysis tools
837:With the increasing popularity of
488:Visitor/unique visitor/unique user
25:
2243:
1242:Problems with third-party cookies
972:
780:dynamically assigned IP addresses
579:- The most common definition of
1113:
877:Log files require no additional
850:disadvantages to each approach.
845:Logfile analysis vs page tagging
53:Local search engine optimisation
2054:
2013:
1953:
1926:
1893:
1867:
1845:
1823:
1751:
1679:
1654:
1627:
1610:
1598:
1589:
805:
612:Session duration/visit duration
1564:
1540:
1499:
1468:
1426:
1417:
1370:
1361:
1309:List of web analytics software
1267:Privacy concerns about cookies
1248:Web tracking § Prevention
854:Advantages of logfile analysis
13:
1:
2068:Mortensen, Dennis R. (2009).
1947:10.1016/S0169-7552(98)00116-0
1852:McGann, Rob (14 March 2005).
1729:10.1080/07421222.2018.1451957
1377:Nielsen, Janne (2021-04-27).
1354:
1084:tied to an individual visitor
1078:Customer lifecycle management
947:are available free of charge.
2152:. Indianapolis, Ind: Wiley.
2150:Web analytics: an hour a day
2072:. Indianapolis, Ind: Wiley.
1072:Customer lifecycle analytics
724:Web server log file analysis
571:Frequency/session per unique
7:
1433:Sng, Yun Fei (2016-08-22),
1302:
1010:, content localization (or
618:Single page visit/singleton
507:Active time/engagement time
222:to understand and optimize
10:
2248:
1447:10.1142/9789813149311_0019
1395:10.1007/s42803-021-00033-4
1245:
1075:
893:Advantages of page tagging
872:search engine optimization
673:Web analytics data sources
653:
523:Average page view duration
376:key performance indicators
284:key performance indicators
48:Search engine optimization
2129:Kaushik, Avinash (2009).
2108:10.1108/00012530910989625
2044:10.1504/IJICS.2007.012244
1776:10.1108/IJTC-03-2021-0039
1688:"IP geolocation database"
1334:Web log analysis software
1281:Cookies are used because
1127:data than other methods.
1096:customer acquisition cost
1016:digital rights management
733:web log analysis software
553:First visit/first session
309:Experiments and testing:
1997:10.1007/3-540-63594-7_75
782:for large companies and
639:click-through rate (CTR)
413:server log file analysis
329:Web analytics Categories
275:Processing of data into
2168:Oxford University Press
1686:IPInfoDB (2009-07-10).
1666:Logaholic Web Analytics
1329:Session (web analytics)
1100:customer lifetime value
982:Geolocation of visitors
234:and assess and improve
218:, and reporting of web
87:Search engine marketing
2201:Web Analytics Overview
1975:Financial Cryptography
1572:Web Analytics Overview
1319:Online video analytics
1035:
650:Off-site web analytics
561:digital fingerprinting
405:web analytics software
382:'s audience response.
347:Off-site web analytics
262:
134:Contextual advertising
58:Social media marketing
2185:John Wiley & Sons
1525:10.1057/dddmp.2012.20
1108:customer satisfaction
1033:
967:cost-benefit analysis
797:The extensive use of
772:search engine spiders
441:On-site web analytics
384:Google Analytics
368:on a specific website
363:On-site web analytics
260:
243:advertising campaigns
2222:Audience measurement
1324:Post-click marketing
1314:Mobile Web Analytics
1270:the option of using
1092:website optimization
1012:website localization
1008:behavioral targeting
687:HTTP request headers
660:Targeted advertising
493:Local Shared Objects
480:Page view (pageview)
210:is the measurement,
139:Behavioral targeting
1272:first-party cookies
1254:third-party cookies
1229:Analytics Poisoning
717:click-through rates
148:Affiliate marketing
120:Display advertising
101:Cost per impression
33:Part of a series on
1910:10.1007/BFb0054155
1881:. February 2, 2005
1552:support.google.com
1439:Business Analytics
1036:
1004:online advertising
818:In the mid-1990s,
630:Click-through rate
380:marketing campaign
270:Collection of data
263:
171:Mobile advertising
78:Native advertising
68:Referral marketing
39:Internet marketing
2227:Digital marketing
2096:ASLIB Proceedings
2006:978-3-540-63594-9
1919:978-3-540-64518-4
1833:. 5 December 2020
1816:10.1002/int.v19:7
1493:10.1002/int.20014
1456:978-981-314-929-8
1216:
1215:
1136:The hotel problem
770:The emergence of
557:persistent cookie
547:Data Segmentation
205:
204:
73:Content marketing
16:(Redirected from
2239:
2163:
2144:
2125:, Burlington MA.
2111:
2083:
2048:
2047:
2037:
2017:
2011:
2010:
1990:
1972:
1957:
1951:
1950:
1941:(1–7): 541–550.
1930:
1924:
1923:
1897:
1891:
1890:
1888:
1886:
1871:
1865:
1864:
1862:
1860:
1849:
1843:
1842:
1840:
1838:
1827:
1821:
1820:
1818:
1794:
1788:
1787:
1755:
1749:
1748:
1708:
1699:
1698:
1696:
1695:
1683:
1677:
1676:
1674:
1673:
1658:
1652:
1651:
1649:
1647:
1638:. Archived from
1631:
1625:
1624:
1623:. sawmill. 2008.
1622:
1614:
1608:
1602:
1596:
1593:
1587:
1581:
1575:
1568:
1562:
1561:
1559:
1558:
1544:
1538:
1537:
1527:
1503:
1497:
1496:
1472:
1466:
1465:
1464:
1463:
1430:
1424:
1421:
1415:
1414:
1374:
1368:
1365:
1236:Google Analytics
1147:
1146:
1102:(CLV), customer
1088:marketing funnel
1041:, also known as
933:Economic factors
870:information for
656:Keyword research
541:Exit rate/% exit
297:, or increasing
197:
190:
183:
106:Search analytics
30:
29:
21:
2247:
2246:
2242:
2241:
2240:
2238:
2237:
2236:
2232:Market research
2207:
2206:
2160:
2141:
2119:Morgan Kaufmann
2080:
2057:
2052:
2051:
2035:10.1.1.116.3451
2018:
2014:
2007:
1961:Franklin, M. K.
1958:
1954:
1931:
1927:
1920:
1898:
1894:
1884:
1882:
1873:
1872:
1868:
1858:
1856:
1850:
1846:
1836:
1834:
1829:
1828:
1824:
1795:
1791:
1756:
1752:
1709:
1702:
1693:
1691:
1684:
1680:
1671:
1669:
1659:
1655:
1645:
1643:
1642:on July 6, 2011
1634:
1632:
1628:
1620:
1616:
1615:
1611:
1603:
1599:
1594:
1590:
1582:
1578:
1569:
1565:
1556:
1554:
1546:
1545:
1541:
1504:
1500:
1473:
1469:
1461:
1459:
1457:
1431:
1427:
1422:
1418:
1375:
1371:
1366:
1362:
1357:
1344:Web performance
1305:
1296:
1250:
1244:
1231:
1195:2 Unique Users
1178:2 Unique Users
1138:
1133:
1116:
1080:
1074:
1061:click analytics
1054:click analytics
1039:Click analytics
1028:
1026:Click analytics
1020:personalization
984:
975:
935:
895:
883:TCP slow starts
856:
847:
808:
726:
696:of a requester.
675:
662:
652:
443:
388:Adobe Analytics
341:web analytics.
331:
315:web development
255:
232:market research
201:
162:Revenue sharing
157:Cost per action
63:Email marketing
28:
23:
22:
15:
12:
11:
5:
2245:
2235:
2234:
2229:
2224:
2219:
2205:
2204:
2196:
2195:
2188:
2181:
2178:
2171:
2164:
2158:
2145:
2139:
2126:
2115:
2112:
2102:(5): 474–482.
2091:
2084:
2079:978-0470424247
2078:
2065:
2056:
2053:
2050:
2049:
2012:
2005:
1988:10.1.1.46.7786
1952:
1925:
1918:
1892:
1866:
1844:
1822:
1809:(7): 585–606.
1789:
1770:(3): 603–615.
1750:
1723:(2): 540–574.
1700:
1678:
1653:
1626:
1609:
1597:
1588:
1576:
1563:
1539:
1498:
1487:(7): 619–637.
1467:
1455:
1425:
1416:
1389:(1–3): 65–88.
1369:
1359:
1358:
1356:
1353:
1352:
1351:
1346:
1341:
1336:
1331:
1326:
1321:
1316:
1311:
1304:
1301:
1295:
1292:
1265:have done so.
1243:
1240:
1230:
1227:
1214:
1213:
1210:
1207:
1204:
1201:
1197:
1196:
1193:
1190:
1187:
1184:
1180:
1179:
1176:
1173:
1170:
1167:
1163:
1162:
1159:
1156:
1153:
1150:
1137:
1134:
1132:
1129:
1115:
1112:
1073:
1070:
1027:
1024:
988:IP geolocation
983:
980:
974:
973:Hybrid methods
971:
958:
957:
954:
951:
948:
934:
931:
930:
929:
926:
923:
920:
913:
910:
903:
894:
891:
890:
889:
886:
875:
867:
863:
855:
852:
846:
843:
807:
804:
725:
722:
721:
720:
712:
697:
690:
674:
671:
651:
648:
647:
646:
637:definition of
627:
621:
615:
609:
606:Return visitor
603:
600:Repeat visitor
597:
591:
585:
574:
568:
550:
544:
538:
532:
526:
520:
514:
504:
496:
484:
476:
468:
460:
442:
439:
400:
399:
396:session replay
359:
330:
327:
319:
318:
303:
302:
287:
280:
273:
254:
251:
203:
202:
200:
199:
192:
185:
177:
174:
173:
167:
166:
165:
164:
159:
151:
150:
144:
143:
142:
141:
136:
131:
123:
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116:
115:
114:
113:
108:
103:
98:
90:
89:
83:
82:
81:
80:
75:
70:
65:
60:
55:
50:
42:
41:
35:
34:
26:
9:
6:
4:
3:
2:
2244:
2233:
2230:
2228:
2225:
2223:
2220:
2218:
2217:Web analytics
2215:
2214:
2212:
2202:
2198:
2197:
2193:
2189:
2186:
2182:
2179:
2176:
2172:
2169:
2165:
2161:
2159:9780470130650
2155:
2151:
2146:
2142:
2140:9780470529393
2136:
2132:
2127:
2124:
2120:
2116:
2113:
2109:
2105:
2101:
2097:
2092:
2089:
2088:Prentice Hall
2085:
2081:
2075:
2071:
2066:
2063:
2059:
2058:
2045:
2041:
2036:
2031:
2027:
2023:
2016:
2008:
2002:
1998:
1994:
1989:
1984:
1980:
1976:
1971:
1966:
1962:
1956:
1948:
1944:
1940:
1936:
1929:
1921:
1915:
1911:
1907:
1903:
1896:
1880:
1876:
1870:
1855:
1848:
1832:
1826:
1817:
1812:
1808:
1804:
1800:
1793:
1785:
1781:
1777:
1773:
1769:
1765:
1761:
1754:
1746:
1742:
1738:
1734:
1730:
1726:
1722:
1718:
1714:
1707:
1705:
1689:
1682:
1667:
1663:
1657:
1641:
1637:
1630:
1619:
1613:
1606:
1601:
1592:
1585:
1580:
1573:
1567:
1553:
1549:
1543:
1535:
1531:
1526:
1521:
1517:
1513:
1509:
1502:
1494:
1490:
1486:
1482:
1478:
1471:
1458:
1452:
1448:
1444:
1440:
1436:
1429:
1420:
1412:
1408:
1404:
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1396:
1392:
1388:
1384:
1380:
1373:
1364:
1360:
1350:
1347:
1345:
1342:
1340:
1337:
1335:
1332:
1330:
1327:
1325:
1322:
1320:
1317:
1315:
1312:
1310:
1307:
1306:
1300:
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1289:
1284:
1279:
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1273:
1268:
1264:
1258:
1255:
1249:
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1237:
1226:
1222:
1219:
1211:
1208:
1205:
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1198:
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1191:
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1185:
1182:
1181:
1177:
1174:
1171:
1168:
1165:
1164:
1160:
1157:
1154:
1151:
1149:
1148:
1145:
1142:
1128:
1126:
1121:
1114:Other methods
1111:
1109:
1105:
1101:
1097:
1093:
1089:
1085:
1079:
1069:
1065:
1062:
1057:
1055:
1050:
1048:
1044:
1040:
1032:
1023:
1021:
1017:
1013:
1009:
1005:
1001:
997:
991:
989:
979:
970:
968:
962:
955:
952:
949:
946:
941:
940:
939:
927:
924:
921:
918:
914:
911:
908:
904:
902:site metrics.
900:
899:
898:
887:
884:
880:
876:
873:
868:
864:
861:
860:
859:
851:
842:
840:
835:
833:
828:
824:
821:
816:
814:
803:
800:
795:
793:
789:
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781:
777:
773:
768:
766:
762:
761:
756:
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748:
743:
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730:
718:
713:
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702:
698:
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691:
688:
684:
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631:
628:
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622:
619:
616:
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610:
607:
604:
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589:
586:
582:
578:
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572:
569:
566:
562:
558:
554:
551:
548:
545:
542:
539:
536:
533:
530:
527:
524:
521:
518:
515:
512:
508:
505:
502:
501:
500:Visit/session
497:
494:
490:
489:
485:
482:
481:
477:
474:
473:
469:
466:
465:
461:
458:
457:
453:
452:
451:
449:
438:
436:
432:
428:
427:
422:
419:in which the
418:
414:
410:
406:
397:
393:
389:
385:
381:
377:
373:
372:landing pages
369:
365:
364:
360:
357:
353:
349:
348:
344:
343:
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326:
322:
316:
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308:
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306:
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296:
292:
288:
285:
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278:
274:
271:
268:
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259:
250:
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244:
241:
237:
233:
229:
225:
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217:
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209:
208:Web analytics
198:
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179:
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155:
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140:
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125:
124:
121:
118:
117:
112:
111:Web analytics
109:
107:
104:
102:
99:
97:
96:Pay-per-click
94:
93:
92:
91:
88:
85:
84:
79:
76:
74:
71:
69:
66:
64:
61:
59:
56:
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51:
49:
46:
45:
44:
43:
40:
37:
36:
32:
31:
19:
2149:
2130:
2099:
2095:
2069:
2064:(Paperback.)
2055:Bibliography
2025:
2021:
2015:
1974:
1955:
1938:
1934:
1928:
1901:
1895:
1883:. Retrieved
1878:
1869:
1857:. Retrieved
1847:
1835:. Retrieved
1825:
1806:
1802:
1792:
1767:
1763:
1753:
1720:
1716:
1692:. Retrieved
1681:
1670:. Retrieved
1668:. 2018-04-25
1665:
1656:
1646:February 26,
1644:. Retrieved
1640:the original
1629:
1612:
1600:
1591:
1579:
1566:
1555:. Retrieved
1551:
1542:
1518:(1): 30–45.
1515:
1511:
1501:
1484:
1480:
1470:
1460:, retrieved
1438:
1428:
1419:
1386:
1382:
1372:
1363:
1297:
1283:IP addresses
1280:
1276:
1259:
1251:
1232:
1223:
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996:geotargeting
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848:
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820:Web counters
817:
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683:HTTP request
676:
666:social media
663:
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635:common known
634:
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624:Site overlay
623:
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424:
415:, reads the
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320:
304:
299:market share
295:saving money
264:
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110:
1349:Web traffic
1043:Clickstream
1000:geolocation
881:lookups or
813:web beacons
776:web proxies
729:Web servers
588:New visitor
565:First Visit
456:Bounce rate
435:web browser
358:as a whole.
311:A/B testing
228:web traffic
129:Ad blocking
2211:Categories
1965:Malkhi, D.
1694:2009-07-19
1690:. IPInfoDB
1672:2023-07-21
1557:2023-08-11
1462:2023-08-11
1355:References
1339:Web mining
1263:banner ads
1246:See also:
1104:churn rate
1076:See also:
1052:Commonly,
799:web caches
790:visits by
747:page views
701:JavaScript
694:IP address
654:See also:
584:view-able.
581:impression
577:Impression
464:Click path
431:JavaScript
421:web server
386: and
212:collection
2170:, Oxford.
2133:. Sybex.
2090:, London.
2030:CiteSeerX
1983:CiteSeerX
1784:2056-5607
1737:0742-1222
1534:1746-0174
1411:233416836
1403:2524-7832
1125:real-time
760:page view
392:heat maps
352:potential
240:broadcast
224:web usage
2192:O'Reilly
2123:Elsevier
1967:(1997).
1885:24 April
1837:July 29,
1745:49681142
1303:See also
1120:sniffing
1110:scores.
866:program.
788:tracking
755:sessions
417:logfiles
409:services
356:Internet
335:off-site
216:analysis
18:Web Hits
2187:(Asia).
1859:3 April
1288:spyware
1183:Room B
1166:Room A
1098:(CAC),
792:cookies
709:ASP.Net
681:Direct
559:or via
448:JICWEBS
429:, uses
339:on-site
277:metrics
247:website
236:website
2194:ebook.
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1200:Total
1161:Total
1158:Day 03
1155:Day 02
1152:Day 01
1106:, and
1059:Also,
1047:clicks
751:visits
707:, and
291:profit
2175:Wiley
2062:Sybex
1741:S2CID
1621:(PDF)
1407:S2CID
986:With
917:Flash
765:visit
757:). A
535:Event
529:Click
2154:ISBN
2135:ISBN
2074:ISBN
2001:ISBN
1914:ISBN
1887:2017
1879:CNET
1861:2014
1839:2022
1780:ISSN
1733:ISSN
1648:2010
1530:ISSN
1451:ISBN
1399:ISSN
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784:ISPs
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740:hits
658:and
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