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Web analytics is the technology and method for the collection, measurement, analysis and reporting of websites and web applications usage data (Burby & Brown, 2007). Web analytics has been growing ever since the development of the World Wide Web. It has grown from a simple function of HTTP (Hypertext Transfer Protocol) traffic logging to a more com...
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In this report, we will cover the topic of Web Analytics. A huge number of businesses around the world has a Web presence and some of them conduct all or the majority of their business transactions online. That created the need to have tracking procedures in place to report and measure the different activities that are happening on the web, like us...
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... To address this limitation, the term "digital analytics" emerged as a more comprehensive concept. In fact, in 2012, the Web Analytics Association renamed itself the Digital Analytics Association to reflect this broader perspective (Zheng & Peltsverger, 2015). However, web analytics remains a fundamental component of digital analytics. ...
The current era has been going through significant transformations owing to the innovative technologies, digitalization, social media, and online business trends worldwide. In the rapid and dynamic environment, marketers are continuously focused on exploring new and digital ways to reach and engage customers in the agricultural industry. Therefore, digital marketing has been recognized as a critical tool for marketers, researchers, and customers to develop brand awareness, interact and build customer engagement over longer periods. Consequently, generating positive customer outcomes i.e., brand awareness, persuasion, customer satisfaction, brand loyalty, and positive word of mouth. The study aimed to evaluate the impact of digital marketing tools on the brand awareness of consumers in agricultural industry. By examining diverse social media channels, the study aimed to provide an analysis of quantitative techniques used to assess the effectiveness of digital marketing. The study furnishes insights for the practitioners to select effective social media tools according to their goal and objectives. The study enables social media marketers to optimize their digital marketing strategies by utilizing minimum organizational resources.
... Web analytics aims to collect and analyze web usage data and traffic [17]. Web analytics is the technology and method for the collection, measurement, analysis, and reporting of website and web application usage data [18][19]. Web analytics is under the umbrella of web mining, specifically web usage mining [20]. ...
... In 1993, WebTrends was one of the leading commercial software companies that utilized web server logs for data collection and analysis [21]. Log files have some downsides as they do not provide information about the size or resolution of the client's screen, keyboard pressing, or clicking behavior [18]. As a result, page tagging or JavaScript tagging became another method to collect data without using log files. ...
... On the other hand, web log analytics is less expensive and suitable for analyzing sensitive and historical data. Although web server logs and page tagging are the two main methods used to capture data, there are more comprehensive methods such as web beacons, event logs, application-level logs, and packet sniffers [18,23]. Cookies are the most common data collection method used in web analytics [18]. ...
In the era of data analytics, the use of web analytics tools is widely spread among Small and Medium Enterprises (SMEs), especially in the e-commerce sector, to analyze web usage data and measure website performance due to the several features it provides. Most web analytics studies were conducted based on marketing rather than a managerial point of view. Therefore, there is a necessity to study the impact from a managerial perspective by exploring the impact on financial and non-financial performance and the decision-making process. This study assessed the impact of web analytics tools on the overall performance of SMEs, targeting Saudi SMEs and considering the lack of web analytics studies in this sector in Saudi Arabia. The sample involved eight Saudi SMEs who participated by answering interview questions, which were analyzed using thematic analysis. The findings demonstrated four main themes: the current web analytics tools used by Saudi SMEs, the motivations behind their use, and their impact on SMEs' performance and decision-making. The results showed that these tools positively affect the overall performance of SMEs. Google Analytics (GA) was the tool most used by the sample. Seven motives were discovered that encourage SMEs to use web analytics tools. This study also addressed the common Key Performance Indicators (KPIs) used by the participants. Concerning decision-making, it was found that web analytics tools affected and supported SMEs' decisions. Furthermore, this study evaluated the role of Zid, the Saudi e-commerce platform for data analytics and performance measurement.
... It is important to note that audience metrics should be distinguished from related terms such as web metrics and audience feedback. While web metrics and audience metrics are sometimes used interchangeably (usher 2013), the former encompasses a broader scope, including not only audience metrics but also factors like web page performance, such as loading time (Zheng and Peltsverger 2014). In contrast, audience feedback is a narrower concept that focuses specifically on audience reactions to content (Lee and Tandoc 2017). ...
In recent decades, significant transformations in audience characteristics and the media environment have necessitated a reassessment of audience analysis. Communication scholars have increasingly recognized the value of utilizing digital traces as valuable resources to understand audience behaviors. This research presents a comprehensive review of 243 audience analyses that incorporate digital traces, covering the period from 2001 to 2022, as published in 19 prominent communication journals. Our analysis reveals a remarkable expansion in the variety of data sources and a diversification of research contexts within the field. The integration of digital traces has empowered researchers to enhance behavioral concepts and attain deeper insights into audience dynamics. By harnessing the temporal, semantic, and structural information embedded within digital traces, novel audience metrics have been developed. This review identifies noteworthy theoretical and methodological implications for future audience research, emphasizing the necessity to embrace the evolving landscape of digital media. Furthermore, it suggests avenues for further exploration and the refinement of existing methodologies. By capitalizing on the potential of digital traces, communication scholars can continue to advance our understanding of audience characteristics and behaviors in the everchanging media ecosystem.
... Duncan (2010) describes the humble beginnings of web analytics from server error logs employed by IT professionals to evaluate the user interface of websites to the introduction of enterprise web analytics by the year 2000, which were able to be deployed by non-technical professionals, especially marketing departments who utilized them to understand the audiences that they were speaking to. Zheng and Peltsverger (2015) show the growth from those humble beginnings to today's usage of web analytics in a variety of industries for different purposes that range from e-commerce optimization and website performance improvement to traffic monitoring. ...
Web analytics, which reference the collection and analysis of information via internet sites, are being increasingly adopted by media organizations in carrying out research on audiences. It is unclear if this same trend is visible in academia despite the adoption of online tools to carry out research. Web analytics provide a view of audience behavior online and may prove relevant in excavating data about audiences and their preferences in media and communication research. It is, however, important to understand the perception of media and communication researchers to this audience research method. The study utilized the survey method to investigate four research hypotheses on the adoption of web analytics, perceptions on the relevance of data derived from web analytics and perception of reliability and trustworthiness of web analytics as an audience research method. The results indicate that media and communication researchers in UNILAG were significantly familiar with web analytics, and perceived it as a trustworthy source for data gathering.
... Each new page transition is a request to the web server. Log files have been used to keep track of web requests, also called hits, since the WWW appeared, and the first browser Mosaic was released in 1993 [17]. There are various methods for collecting and storing user access data. ...
... While the data storage phase occurs on the servers (on-site or off-site), the data-obtaining step can be performed via client-side or server-side web technologies. Application-level user access data is commonly obtained using JavaScript (JS) snippets by the clientside page tagging method, and the logs are stored on remote servers off-site [17]. However, this method is unsuitable for organizations that prioritize freely applying web mining techniques to their data. ...
The underlying data source for web usage mining (WUM) is commonly thought to be server logs. However, access log files ensure quite limited data about the clients. Identifying sessions from this messy data takes considerable effort, and operations performed for this purpose do not always yield excellent results. Also, this data cannot be used for web analytics efficiently. This study proposes a method for user tracking, session management, and collecting web usage data. The method is mainly based on an innovative approach for using collected data for web analytics extraction as the data source in web usage mining. An application-based API has been developed with a different strategy from conventional client-side methods to obtain and process log data. The log data has been successfully gathered by integrating the technique into an enterprise web application. The results reveal that the homogeneous data collected and stored with this method is more convenient to browse, filter, and process than web server logs. This structured data can be used effortlessly as a reliable data source for high-performance web usage mining activity, real-time web analytics, machine learning algorithms, or a functional recommendation system. Ó 2023 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
... The monitoring leads to better organization of promotion, better adjustment of the offer and form of presentation to the needs of the recipients. Nowadays, web analytics can be used in many business areas and for different purposes, including traffic monitoring, e-commerce optimization, marketing/advertising, web development, information architecture, website performance improvement, web-based campaigns/programs (Zheng and Peltsverger, 2015). ...
Purpose: The main aim of the article is to know the information needs of candidates for university courses and indicate the importance of web analytics tools in the university recruitment process. The authors present the recruitment process for data science high study programme that was conducted in the middle of 2021 at one of the biggest universities in eastern Poland. Theoretical background: Digital transformation is an irreversible process today. Data produced by people, things, administration units and business organizations can be the source of valuable information. That transformation causes new possibilities for fast development, but also creates challenges for education processes and professional work. Furthermore, the digital transformation resulted in creating new professions like data science (DS). Because of data volume and its importance DS professionals became one of the most wanted specialists in the 21st century, and therefore many universities try to launch new study programs related to automated data processing and try to get the attention of potential students. Design/methodology/approach: The process was supported with analytics tools Hotjar and Google Analytics. The results presented in the paper base on the analysis of 974 pageviews recorded by Hotjar and activity of 824 page users reported by Google Analytics. Findings: The analysis showed that web analytics tools are very easy to use in the recruitment process, and that gathered data allows for better understanding of candidates' needs and improving the future requirement processes and tools. Results indicated that the most important topics for candidates were study programme and payment. Form the technical point of view the responsiveness of applications used for the recruitment process is crucial because a lot of traffic was generated by both users of desktop computers and mobile devices. The greatest interest in the program was recorded before the holiday months. Originality/value: The research contributes to academia in the field of recruitment. Paper presents the data science high study programme and indicates the importance of web analytics tools in the university recruitment process.
... 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 [8] Direct HTTP request data: directly comes from HTTP request messages (HTTP request headers). 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, IP address of a requester. ...
Packet analysis is a primary trace back technique in network forensics, Packet analysis, often referred to as packet sniffing or protocol analysis, describes the process of capturing and interpreting live data as it flows across a network in order to better understand what is happening on that network. This can be used to find traces of nefarious online behavior, data breaches, unauthorized website access, malware infection, and intrusion attempts, and to reconstruct image files, documents, email attachments, etc. sent over the network .Packet analysis is typically performed using a packet sniffer, a tool used to capture raw network data going across the wire. Wireshark proves to be an effective open source tool in the study of network packets and their behavior. In this regard, Wireshark can be used in identifying and categorizing various types of attack signatures. It lets administrator to see what"s happening on network at a microscopic level. The purpose of this paper is to demonstrate how Wireshark is applied in network protocol diagnosis and can be used to find some basic indicators of compromise for a malware.
... Since the first browser and the World Wide Web emerged in 1993, log files have been used to track web requests. Subsequently, the analysis of these log files helped the emergence of Web Analytics to understand the interaction between a user and a website [6]. ...
... However, a limitation present in Web Analytics is the lack of qualitative understanding of the data collected in the user's interaction with the website [8]. Despite presenting this limitation, it is currently used mostly in traffic monitoring, e-commerce optimization, digital marketing, information architecture, among other uses [6]. ...
User experience is an essential software quality concept for companies nowadays. Development teams attempt to guarantee that their digital products provide a satisfying experience. Likewise, several evaluation methods have emerged to determine if the software product's interfaces are understandable, intuitive, and attractive to users. However, few of these methods suggest the use of data analytics for user experience evaluation. Many companies use tools that allow them to obtain multiple data about using their leading websites but do not use this information to generate relevant results that can be used to improve the design of their graphical interfaces. In this study, we present the results of conducting a systematic literature review to identify case studies that report web analytics usage to evaluate websites' user experience. The search retrieved a total of 315 papers. The databases used for this review were: Scopus, Web of Science, IEEExplore, and ACM Digital Library. After applying the inclusion and exclusion criteria, 18 relevant articles were obtained, which have allowed answering the research questions. The results show a tendency to incorporate data analysis to explain specific design problems or usability issues. Additionally, we have identified some methodological proposals that have been established on how to use data analytics for the user experience evaluation process and some metrics that could offer relevant information about the degree of ease of use of a website.
... Web analytics provides a tactical approach to track key metrics and analyze visitors' activity and traffic flow and generate reports. [45][46][47] Thus, it is an indispensable technique for e-commerce merchants. ...
... While existing Web analytics studies 45,47,50-55,127 provide a tactical approach to track key metrics, analyze visitors' activity and traffic flow, and generate reports, [45][46][47] our study aligns with the position held by Kimball and Merz 127 of the immense value in clickstream analysis and reinforces the criticality of web content usage data mining process that could capture and accurately analyze the interactions between Web users and the sites they access. This information could dramatically improve an organization's understanding of its relationship with users, and radically improve the strategic knowledge of customer activities (motives and actions) and, thus, web content usage data mining is an indispensable technique for e-commerce merchants, thereby adding to the body of knowledge in the domain. ...
A successful business intelligence solution can help organizations improve the quality and speed of their decision‐making processes by analyzing the consolidated information collected from their websites. Using the current Web server log standard, which indicates only the locations of served Web pages, may lead to inaccurate business analysis for data driven and frequently updated static content Web pages. A properly defined Web content usage data warehouse that captures both dynamic and static contents of web pages provides rich data source for discovering interesting business rules among users' activities. This paper demonstrates the simplicity of data extract, transform and load procedures to import raw Web content usage log to various data models for data analysis, reporting and data mining tools. In this paper, we use two data mining techniques (expected maximization and the prefixspan algorithms) for visitor grouping and path analysis to find interesting patterns in Web content usage log data, an important component of e‐commerce Web sites traffic analysis. Visitor grouping uses data clustering to group visitors/sessions with similar selected attributes' value. Path analysis mines common visiting path sequence. The ultimate goal is to enable the online merchant provide enhanced and differentiated marketing services generally to its existing and potential customers and tell what items customers are interested in instead of ambiguous URLs.
... (page number not for citation purposes) [7]. A high bounce rate implies that users are uninterested in the site's content or that the design is unsuitable for the user [8]. The bounce rate and other web analytical tools are underutilized in graduate medical education (GME). ...
BACKGROUND
Web analytics is the measurement, collection, analysis, and reporting of websites’ and web applications’ usage data. While common in the e-commerce arena, web analytics are underutilized in graduate medical education.
OBJECTIVE
The UAMS Department of Surgery website was revamped with input from in-house surgeons in August 2017. This study investigated the use of web analytics to gauge the impact of our department’s website redesign project.
METHODS
Google Analytics software was used to measure website performance before and after implementation of the new website. Eight-month matched periods were compared. Factors tracked included total users, new users, total sessions, sessions per user, pages per session, average session duration, total page views, and bounce rate (the percentage of visitors who visit a site then leave [i.e. bounce] without continuing to another page on the same site).
RESULTS
Analysis using a non-paired Student’s t-test demonstrated a statistically significant increase for total page views (33,065 vs 81,852; p<0.0001) and decrease for bounce rate (50.70% vs 0.23%; p<0.0001). Total users, new users, total sessions, sessions per user, and pages per sessions showed improvement; average session duration was unchanged. Sub-group analysis showed that after the main page, the next three most frequently visited pages relate to GME programs in our department.
CONCLUSIONS
Web analytics are practical measures of a website’s efficacy. Our data suggest that a modern website significantly improves user engagement. An up-to-date website is essential for contemporary GME recruitment, will likely enhance engagement of residency applicants with our GME programs, and warrants further investigation.
