Front-end developers are tasked with keeping websites up-to-date while optimizing user experiences and interactions. Tools and systems have been developed to give these individuals granular analytic insight into who, with what, and how users are interacting with their sites. These systems maintain a historical record of user interactions that can be leveraged for design decisions. Developing a framework to aggregate those historical usage records and using it to anticipate user interactions on a webpage could automate the task of optimizing web pages. In this research a system called Active Analytics was created that takes Google Analytics historical usage data and provides a dynamic front-end system for automatically updating web page navigational elements. The previous year’s data is extracted from Google Analytics and transformed into a summarization of top navigation steps. Once stored, a responsive front-end system selects from this data a timespan of three weeks from the previous year: current, previous and next. The most frequently reached pages, or their parent pages, will have their navigational UI elements highlighted on a top-level or landing page to attempt to reduce the effort to reach those pages. The Active Analytics framework was evaluated by eliciting volunteers by randomly assigning two versions of a site, one with the framework, one without. It was found that users of the framework-enabled site were able to navigate a site more easily than the original.

Today, web sites are important communication channels that reach a wide group of people. Measuring the effectiveness of these web-sites has become a key issue for researchers as well as practitioners. However, there is no consensus on how to define web site effectiveness and which dimensions need to be used for the evaluation of these web sites. This problem is more noteworthy for information driven web sites like academic web sites. There is limited academic literature in this predominant application area. The existing studies measured the effectiveness of these academic web sites by taking into account their information architecture mostly using think-aloud methodology. However, there is limited study on web analytics tools which are capable of providing valuable information regarding the web site users such as their navigation behaviours and browser details. Although web analytics tools provide detailed and valuable information, the existing studies have utilized their very basic features. In this thesis, we have explored web analytic tools and think-aloud study method to improve information architecture of web sites. Taking METU Informatics Institute web site as a case study, we have used the reports of Google Analytics which is a commercial web analytics tool owned by Google and think-aloud study results to improve the information architecture of our case study web-site.

No description available.

This thesis has two purposes; emphasizing the importance of data quality of Big Data, and identifying and evaluating potential error sources in JavaScript tracking (a client side on - site online behavior clickstream data collection method commonly used in web analytics). The importance of data quality of Big Data is emphasized through the evaluation of JavaScript tracking. The Total Survey Error framework is applied to JavaScript tracking and 17 nonsampling error sources are identified and evaluated. The bias imposed by these error sources varies from large to small, but the major takeaway is the large number of error sources actually identified. More work is needed. Big Data has much to gain from quality work. Similarly, there is much that can be done with statistics in web analytics.

The subject of the thesis Online Propagation of Web Portal is formulation of recom-mendations for online campaigns for selected business entity. In the first chapter are defined basic concepts of Internet advertising as part of marketing and terms of web analytics. In the second chapter, there are internet campaigns analyzed using web analy-tics. On the basis of this analysis are formulated specific recommendations in the third chapter. The fourth chapter deals with the evaluation of modified campaigns. The fifth chapter deals with the evaluation of the results and the formulation of final recommen-dations.

With the emergence of the Internet and of the World Wide Web, the Web site has become a key communication channel in organizations. To satisfy the objectives of the Web site and of its target audience, adapting the Web site content to the users' expectations has become a major concern. In this context, Web usage mining, a relatively new research area, and Web analytics, a part of Web usage mining that has most emerged in the corporate world, offer many Web communication analysis techniques. These techniques include prediction of the user's behaviour within the site, comparison between expected and actual Web site usage, adjustment of the Web site with respect to the users' interests, and mining and analyzing Web usage data to discover interesting metrics and usage patterns. However, Web usage mining and Web analytics suffer from significant drawbacks when it comes to support the decision-making process at the higher levels in the organization.<p><p>Indeed, according to organizations theory, the higher levels in the organizations need summarized and conceptual information to take fast, high-level, and effective decisions. For Web sites, these levels include the organization managers and the Web site chief editors. At these levels, the results produced by Web analytics tools are mostly useless. Indeed, most of these results target Web designers and Web developers. Summary reports like the number of visitors and the number of page views can be of some interest to the organization manager but these results are poor. Finally, page-group and directory hits give the Web site chief editor conceptual results, but these are limited by several problems like page synonymy (several pages contain the same topic), page polysemy (a page contains several topics), page temporality, and page volatility.<p><p>Web usage mining research projects on their part have mostly left aside Web analytics and its limitations and have focused on other research paths. Examples of these paths are usage pattern analysis, personalization, system improvement, site structure modification, marketing business intelligence, and usage characterization. A potential contribution to Web analytics can be found in research about reverse clustering analysis, a technique based on self-organizing feature maps. This technique integrates Web usage mining and Web content mining in order to rank the Web site pages according to an original popularity score. However, the algorithm is not scalable and does not answer the page-polysemy, page-synonymy, page-temporality, and page-volatility problems. As a consequence, these approaches fail at delivering summarized and conceptual results. <p><p>An interesting attempt to obtain such results has been the Information Scent algorithm, which produces a list of term vectors representing the visitors' needs. These vectors provide a semantic representation of the visitors' needs and can be easily interpreted. Unfortunately, the results suffer from term polysemy and term synonymy, are visit-centric rather than site-centric, and are not scalable to produce. Finally, according to a recent survey, no Web usage mining research project has proposed a satisfying solution to provide site-wide summarized and conceptual audience metrics. <p><p>In this dissertation, we present our solution to answer the need for summarized and conceptual audience metrics in Web analytics. We first described several methods for mining the Web pages output by Web servers. These methods include content journaling, script parsing, server monitoring, network monitoring, and client-side mining. These techniques can be used alone or in combination to mine the Web pages output by any Web site. Then, the occurrences of taxonomy terms in these pages can be aggregated to provide concept-based audience metrics. To evaluate the results, we implement a prototype and run a number of test cases with real Web sites. <p><p>According to the first experiments with our prototype and SQL Server OLAP Analysis Service, concept-based metrics prove extremely summarized and much more intuitive than page-based metrics. As a consequence, concept-based metrics can be exploited at higher levels in the organization. For example, organization managers can redefine the organization strategy according to the visitors' interests. Concept-based metrics also give an intuitive view of the messages delivered through the Web site and allow to adapt the Web site communication to the organization objectives. The Web site chief editor on his part can interpret the metrics to redefine the publishing orders and redefine the sub-editors' writing tasks. As decisions at higher levels in the organization should be more effective, concept-based metrics should significantly contribute to Web usage mining and Web analytics. <p> / Doctorat en sciences appliquées / info:eu-repo/semantics/nonPublished

This topic of this work is web analytics and customer knowledge methods that help small and medium sized businesses for decision support and are intended to yield higher e-commerce results. The main purpose of this thesis is to design and verify possible uses of advanced web analytics methods in a customer-oriented small business. The theoretical part conducts research into the current state of the web analytics industry. The conditions of small and medium enterprises are described and suitable web analytics tools are compared. Several web analytics maturity models are discussed. The practical part of the thesis states specific recommendations obtained from the pilot project for the company Baushop s.r.o. The project consists of a business analysis and use of analytics tools for optimizing internet campaigns and improving customer service. Specific data analysis methods are discussed and all supportive data are provided.

The aim of this master`s thesis is to analyze an existing website of a chosen company by testing user`s usability, examining Google Analytics data, conducting SEO analysis and analysing user behaviour according to heat maps. The theoretical part describes the positi-on of the website in a modern marketing, characterizes and compares main web designs, summarizes best-practices for web site development, methods of web analysis and methods for analyzing user behaviour. The practical part uses the knowledge presented in the theo-retical part and applies it in the analysis on the current website of the chosen company. The secondary aim is to define recommendations for creating new pages based on the results of analyses and best-practices of web design from the theoretical part.

This thesis deals with The Royal Mint and it's online strategy. Using web analytics tools and usability testing it analyzes a current state of website and e-shop of the company. From the obtained figures about visits of the website, keywords, conversion rate, traffic sources and others, the customers' behavior is analyzed and subsequent conversion rate and user friendliness-raising measures are evaluated. The thesis summarizes recommendations resulting from the carried analyses in order to increase the online sales, bring new customers online and increase the loyalty of the existing ones.

This diploma thesis' main subject is to design a service that automatically analyses (e-shop) data, interprets them and consequently provides users with results of this analysis via web service. Design of this service includes concept composition its technical solution and market verification. The main purpose of this thesis is to design an online service for small and medium sized e-shops, that will (based on provided data) deliver information for e-shop performance optimization. Aspects taken into account are service functionality, its technical solution and business plan destined for its market launch. Theoretical part focuses on analysis of online analytical tools that are available for users on market. It looks at internet e-shops market and analyses users' requirements for analytical tool/service either. This part delivers a list of currently available analytical platforms and services that are convenient for e-shops to be used. Then these tools are compared amongst each other. Criteria for comparison are the usability of service, its user experience, positive and negative aspects related to these predefined criteria. Practical part of this thesis specifies functional and non-functional requirements on service, its user interface. The whole concept is verified on market by interview. Discovered requirements are consequently applied in technical solution design and business plan composition. Overall view of functionality and feasibility of the newly designed service and its verification in real environment is the preoccupation of this part as well.